Spaces:

VIDraft
/

AI

Running

AI / index.html

Show derivative-variant stat (1,200+ quant variants) on models page; Darwin subtitle reflects B+C (file-level + sibling family)

57975cb verified about 17 hours ago

Raw

History Blame Contribute Delete

356 kB

	<!doctype html>
	<html lang="ko">
	<title data-i18n="page-title">VIDRAFT — Pre-AGI Model Development</title>
	<meta charset="utf-8">
	<meta name="viewport" content="width=device-width,initial-scale=1">
	<meta http-equiv="Cache-Control" content="no-cache, no-store, must-revalidate">
	<meta http-equiv="Pragma" content="no-cache">
	<meta http-equiv="Expires" content="0">
	<!-- ===== SEO ===== -->
	<meta name="description" content="비드래프트(VIDRAFT)는 24대의 GPU로 거대 자본에 맞서는 한국 토종 Pre-AGI 모델 개발사입니다. Darwin 모델 패밀리(GPQA 세계 상위), AETHER 아키텍처, QuantumOS 양자 암호분석, FINAL-Bench 메타인지 벤치마크.">
	<meta name="keywords" content="비드래프트,VIDRAFT,Darwin,다윈,AETHER,에테르,QuantumOS,양자컴퓨터,양자 암호분석,메타인지,FINAL-Bench,K-AI,GPQA,한국 AI,Pre-AGI,LLM,온디바이스 AI,지니젠AI">
	<meta name="author" content="VIDRAFT (지니젠AI)">
	<meta name="robots" content="index,follow,max-image-preview:large,max-snippet:-1,max-video-preview:-1">
	<link rel="canonical" href="https://vidraft.net/">
	<link rel="icon" href="/favicon.png">
	<link rel="alternate" hreflang="ko" href="https://vidraft.net/">
	<link rel="alternate" hreflang="en" href="https://vidraft.net/?lang=en">
	<link rel="alternate" hreflang="x-default" href="https://vidraft.net/">
	<!-- ===== Open Graph (카톡·페북·링크 미리보기) ===== -->
	<meta property="og:type" content="website">
	<meta property="og:site_name" content="VIDRAFT">
	<meta property="og:title" content="VIDRAFT — 한국 토종 Pre-AGI 모델 개발사">
	<meta property="og:description" content="24대의 GPU로 거대 자본에 맞서는 비드래프트. Darwin 모델 패밀리·AETHER 아키텍처·QuantumOS 양자 암호분석·FINAL-Bench 메타인지 벤치마크.">
	<meta property="og:url" content="https://vidraft.net/">
	<meta property="og:image" content="https://vidraft.net/darwin-family-infographic.png">
	<meta property="og:image:alt" content="VIDRAFT Darwin 모델 패밀리">
	<meta property="og:locale" content="ko_KR">
	<meta property="og:locale:alternate" content="en_US">
	<!-- ===== Twitter Card ===== -->
	<meta name="twitter:card" content="summary_large_image">
	<meta name="twitter:title" content="VIDRAFT — 한국 토종 Pre-AGI 모델 개발사">
	<meta name="twitter:description" content="24대의 GPU로 거대 자본에 맞서는 비드래프트. Darwin·AETHER·QuantumOS·FINAL-Bench.">
	<meta name="twitter:image" content="https://vidraft.net/darwin-family-infographic.png">
	<!-- ===== JSON-LD 구조화 데이터 (AEO: AI 답변엔진·구글 리치결과) ===== -->
	<script type="application/ld+json">
	{"@context":"https://schema.org","@type":"Organization","name":"VIDRAFT","alternateName":["비드래프트","지니젠AI","VIDraft"],"url":"https://vidraft.net/","logo":"https://vidraft.net/favicon.png","image":"https://vidraft.net/darwin-family-infographic.png","description":"한국 토종 Pre-AGI 모델 개발사. Darwin 모델 패밀리, AETHER 아키텍처, QuantumOS 양자 암호분석, FINAL-Bench 메타인지 벤치마크.","foundingDate":"2024","knowsAbout":["Pre-AGI","Large Language Models","Metacognition","Quantum Cryptanalysis","On-device AI","Korean NLP","Drug Discovery AI"],"sameAs":["https://huggingface.co/VIDraft","https://huggingface.co/FINAL-Bench"]}
	</script>
	<script type="application/ld+json">
	{"@context":"https://schema.org","@type":"WebSite","name":"VIDRAFT","alternateName":"비드래프트","url":"https://vidraft.net/","inLanguage":["ko","en"],"publisher":{"@type":"Organization","name":"VIDRAFT"}}
	</script>
	<style>
	:root{
	--ind:#4338CA;--ind-l:#6366F1;--ind-xl:#EEF2FF;--ind-xxl:#F5F3FF;
	--cyn:#06B6D4;--cyn-l:#CFFAFE;
	--em:#10B981;--em-l:#D1FAE5;
	--amb:#F59E0B;--amb-l:#FEF3C7;
	--ros:#F43F5E;--ros-l:#FFE4E6;
	--pur:#7C3AED;--pur-l:#EDE9FE;
	--text:#0F172A;--muted:#64748B;--light:#94A3B8;
	--bg:#F8FAFF;--card:#FFFFFF;--border:#E2E8F0;
	--sh:0 2px 12px rgba(67,56,202,.07);--sh-lg:0 8px 32px rgba(67,56,202,.13);
	--r:14px;--r-sm:8px;
	}
	*{box-sizing:border-box;margin:0;padding:0}
	body{font-family:-apple-system,BlinkMacSystemFont,'Segoe UI','Apple SD Gothic Neo',sans-serif;background:var(--bg);color:var(--text);line-height:1.6}

	/* ── NAV ── */
	nav{position:fixed;top:0;left:0;right:0;z-index:200;background:rgba(255,255,255,.95);backdrop-filter:blur(20px);border-bottom:1px solid var(--border);height:58px;display:flex;align-items:center;padding:0 20px;gap:0}
	.nav-logo{font-size:1.15rem;font-weight:800;color:#D01E3C;letter-spacing:-.5px;margin-right:28px;cursor:pointer;white-space:nowrap;user-select:none}
	.nav-logo span{color:#1B2A5C}
	.nav-links{display:flex;gap:2px;flex:1;overflow-x:auto;overflow-y:hidden;scrollbar-width:none;-ms-overflow-style:none}.nav-links::-webkit-scrollbar{display:none}
	.nav-links a{padding:6px 12px;border-radius:6px;font-size:.85rem;font-weight:500;color:var(--muted);text-decoration:none;transition:all .16s;cursor:pointer;white-space:nowrap;user-select:none}
	.nav-links a:hover,.nav-links a.active{color:var(--ind);background:var(--ind-xl)}
	.nav-cta{background:var(--ind);color:#fff;padding:7px 16px;border-radius:8px;font-size:.83rem;font-weight:700;text-decoration:none;white-space:nowrap;transition:background .16s;flex-shrink:0}
	.nav-cta:hover{background:var(--ind-l)}
	.lang-sw{display:flex;gap:2px;margin:0 8px;flex-shrink:0}
	.nav-burger{display:none;background:none;border:none;font-size:1.6rem;line-height:1;cursor:pointer;color:var(--text);padding:2px 6px;flex-shrink:0}
	@media(max-width:1280px){.nav-links a{padding:6px 9px;font-size:.8rem}.nav-logo{margin-right:16px}}
	@media(max-width:1024px){
	.nav-logo{margin-right:auto}
	.nav-burger{display:block}
	.nav-cta{display:none}
	.nav-links{position:fixed;top:58px;left:0;right:0;flex:none;flex-direction:column;gap:0;background:var(--card);border-bottom:1px solid var(--border);box-shadow:0 12px 28px rgba(15,23,42,.14);padding:6px 14px 16px;max-height:calc(100vh - 58px);overflow-y:auto;overflow-x:hidden;display:none}
	nav.nav-open .nav-links{display:flex}
	.nav-links a{padding:13px 8px;font-size:.98rem;border-bottom:1px solid var(--border);border-radius:0;width:100%;color:var(--text)}
	.nav-links a:last-child{border-bottom:none}
	}
	.ls-btn{border:none;padding:4px 9px;border-radius:5px;font-size:.74rem;font-weight:700;cursor:pointer;background:transparent;color:var(--muted);transition:all .16s;line-height:1}
	.ls-btn.active{background:var(--ind);color:#fff}

	/* ── PAGE ── */
	.page{display:none;padding-top:58px;min-height:100vh}
	.page.active{display:block}

	/* ── i18n language blocks (EN default → hide Korean-only content) ── */
	body:not(.lang-ko) .ko-only{display:none}
	body.lang-ko .en-only{display:none}
	.container{max-width:1100px;margin:0 auto;padding:0 22px}
	.section{padding:56px 0}
	.section-sm{padding:36px 0}
	h2.st{font-size:1.8rem;font-weight:800;color:var(--text);letter-spacing:-.4px;margin-bottom:6px}
	h2.st span{color:var(--ind)}
	p.ss{color:var(--muted);font-size:.95rem;margin-bottom:32px;max-width:580px}

	/* ── HERO ── */
	.hero{background:linear-gradient(135deg,#EEF2FF 0%,#F0FDFF 55%,#ECFDF5 100%);padding:72px 0 64px;text-align:center;position:relative;overflow:hidden}
	.hero::before{content:'';position:absolute;inset:0;background:radial-gradient(ellipse 70% 50% at 50% 0%,rgba(99,102,241,.1),transparent);pointer-events:none}
	.hero .container{position:relative;z-index:1}
	.badge{display:inline-block;background:var(--ind);color:#fff;font-size:.75rem;font-weight:700;padding:4px 12px;border-radius:100px;margin-bottom:18px;letter-spacing:.4px}
	.hero h1{font-size:clamp(1.9rem,4.5vw,3rem);font-weight:900;letter-spacing:-1px;line-height:1.15;margin-bottom:14px}
	.hero h1 span{color:var(--ind)}
	.hero-sub{font-size:1rem;color:var(--muted);margin:0 auto 32px;max-width:560px}
	.btns{display:flex;gap:10px;justify-content:center;flex-wrap:wrap}
	.btn{display:inline-block;padding:11px 26px;border-radius:10px;font-size:.92rem;font-weight:700;text-decoration:none;transition:all .18s;cursor:pointer;user-select:none}
	.btn-p{background:var(--ind);color:#fff;box-shadow:0 4px 14px rgba(99,102,241,.28)}
	.btn-p:hover{background:var(--ind-l);transform:translateY(-1px)}
	.btn-o{background:#fff;color:var(--ind);border:2px solid var(--ind)}
	.btn-o:hover{background:var(--ind-xl)}

	/* ── PAGE HERO ── */
	.ph{padding:48px 0 40px}
	.ph .badge{margin-bottom:10px}
	.ph h1{font-size:clamp(1.5rem,3.5vw,2.4rem);font-weight:900;letter-spacing:-.4px;margin-bottom:8px}
	.ph p{font-size:.95rem;color:var(--muted);max-width:580px}

	/* ── SUB-TABS ── */
	.subtab-bar{background:#fff;border-bottom:1px solid var(--border);position:sticky;top:58px;z-index:100;overflow-x:auto}
	.subtab-bar::-webkit-scrollbar{height:3px}
	.subtab-bar::-webkit-scrollbar-thumb{background:var(--border)}
	.subtab-inner{display:flex;gap:0;padding:0 22px;max-width:1100px;margin:0 auto}
	.stab{padding:12px 18px;font-size:.85rem;font-weight:600;color:var(--muted);cursor:pointer;white-space:nowrap;border-bottom:2px solid transparent;transition:all .16s;user-select:none}
	.stab:hover{color:var(--ind)}
	.stab.active{color:var(--ind);border-bottom-color:var(--ind)}
	.stab-content{display:none}
	.stab-content.active{display:block}

	/* ── STATS BAR ── */
	.stats{background:#fff;border:1px solid var(--border);border-radius:var(--r);padding:28px;display:grid;grid-template-columns:repeat(4,1fr);gap:20px;box-shadow:var(--sh)}
	.si{text-align:center}
	.sn{font-size:1.85rem;font-weight:900;color:var(--ind);letter-spacing:-1px;line-height:1}
	.sl{font-size:.78rem;color:var(--muted);margin-top:4px;font-weight:500}

	/* ── CARDS ── */
	.grid{display:grid;gap:18px}
	.g3{grid-template-columns:repeat(3,1fr)}
	.g2{grid-template-columns:repeat(2,1fr)}
	.g4{grid-template-columns:repeat(4,1fr)}
	@media(max-width:900px){.g4{grid-template-columns:repeat(2,1fr)}}
	@media(max-width:700px){.g3,.g2,.g4{grid-template-columns:1fr}.stats{grid-template-columns:repeat(2,1fr)}}
	.card{background:var(--card);border:1px solid var(--border);border-radius:var(--r);padding:24px;box-shadow:var(--sh);transition:all .18s}
	.card:hover{box-shadow:var(--sh-lg);transform:translateY(-2px)}
	.ci{width:42px;height:42px;border-radius:10px;display:flex;align-items:center;justify-content:center;font-size:1.25rem;margin-bottom:12px}
	.ci-ind{background:var(--ind-xl)} .ci-cyn{background:var(--cyn-l)} .ci-em{background:var(--em-l)} .ci-amb{background:var(--amb-l)} .ci-ros{background:var(--ros-l)} .ci-pur{background:var(--pur-l)}
	.card h3{font-size:.95rem;font-weight:700;margin-bottom:5px}
	.card p{font-size:.84rem;color:var(--muted);line-height:1.6}
	.tag{display:inline-block;font-size:.72rem;font-weight:700;padding:3px 9px;border-radius:100px;margin-bottom:8px}
	.t-ind{background:var(--ind-xl);color:var(--ind)} .t-cyn{background:var(--cyn-l);color:#0891B2}
	.t-em{background:var(--em-l);color:#059669} .t-amb{background:var(--amb-l);color:#D97706}
	.t-ros{background:var(--ros-l);color:#E11D48} .t-pur{background:var(--pur-l);color:var(--pur)}

	/* ── SERVICE CARD ── */
	.sc{background:#fff;border:1px solid var(--border);border-radius:var(--r);padding:20px;display:flex;flex-direction:column;gap:8px;box-shadow:var(--sh);transition:all .18s;text-decoration:none;color:inherit}
	.sc:hover{box-shadow:var(--sh-lg);transform:translateY(-2px);border-color:var(--ind-l)}
	.sc-icon{font-size:1.5rem;line-height:1}
	.sc h3{font-size:.9rem;font-weight:700}
	.sc p{font-size:.79rem;color:var(--muted);flex:1;line-height:1.55}
	.sc-link{font-size:.75rem;color:var(--ind);font-weight:600;margin-top:auto;word-break:break-all}
	.sc-sub{font-size:.72rem;color:var(--light);margin-top:2px}

	/* ── ALL SERVICES COMPACT GRID ── */
	.all-grid{display:grid;grid-template-columns:repeat(5,1fr);gap:12px}
	@media(max-width:900px){.all-grid{grid-template-columns:repeat(3,1fr)}}
	@media(max-width:600px){.all-grid{grid-template-columns:repeat(2,1fr)}}
	.ag-item{background:#fff;border:1px solid var(--border);border-radius:var(--r-sm);padding:14px;text-align:center;text-decoration:none;color:inherit;transition:all .16s;display:block}
	.ag-item:hover{box-shadow:var(--sh);border-color:var(--ind-l);transform:translateY(-1px)}
	.ag-item .ag-icon{font-size:1.6rem;margin-bottom:6px}
	.ag-item h4{font-size:.78rem;font-weight:700;margin-bottom:3px}
	.ag-item p{font-size:.7rem;color:var(--muted)}

	/* ── SECTION DIVIDER ── */
	.div{height:1px;background:var(--border);margin:40px 0}

	/* ── HF COLLECTION CARD ── */
	.hf-card{background:#fff;border:1px solid var(--border);border-radius:var(--r);padding:24px;box-shadow:var(--sh);display:flex;flex-direction:column;gap:12px;transition:all .18s;text-decoration:none;color:inherit}
	.hf-card:hover{box-shadow:var(--sh-lg);transform:translateY(-2px);border-color:#FF6B35}
	.hf-logo{width:36px;height:36px;background:#FFE4D6;border-radius:8px;display:flex;align-items:center;justify-content:center;font-size:1.1rem}
	.hf-card h3{font-size:.95rem;font-weight:700}
	.hf-card p{font-size:.82rem;color:var(--muted);line-height:1.6}
	.hf-models{display:flex;flex-wrap:wrap;gap:5px;margin-top:4px}
	.hf-model-tag{font-size:.68rem;background:var(--ind-xl);color:var(--ind);padding:2px 8px;border-radius:100px;font-weight:600}
	.hf-meta{font-size:.75rem;color:var(--light);display:flex;gap:12px}

	/* ── LEADERBOARD TABLE ── */
	.tw{overflow-x:auto;border-radius:var(--r);border:1px solid var(--border);box-shadow:var(--sh)}
	table{width:100%;border-collapse:collapse;background:#fff}
	th{background:var(--ind);color:#fff;padding:11px 14px;font-size:.8rem;font-weight:700;text-align:left;white-space:nowrap}
	td{padding:11px 14px;font-size:.85rem;border-bottom:1px solid var(--border)}
	tr:last-child td{border-bottom:none}
	tr:nth-child(even){background:#FAFBFF}
	tr:hover{background:var(--ind-xl)}
	.rb{display:inline-flex;align-items:center;justify-content:center;width:24px;height:24px;border-radius:50%;font-size:.72rem;font-weight:800;background:var(--border);color:var(--text)}
	.rb-g{background:#FEF3C7;color:#B45309} .rb-s{background:#F1F5F9;color:#475569}
	.rb-v{background:var(--ind-xl);color:var(--ind)}

	/* ── AGI STAGES ── */
	.agi{display:flex;overflow-x:auto;padding-bottom:4px}
	.agi-s{flex:1;min-width:130px;padding:18px 12px;text-align:center;border-right:2px solid var(--border)}
	.agi-s:last-child{border-right:none}
	.agi-s.cur{background:linear-gradient(180deg,var(--ind-xl),transparent)}
	.agi-n{font-size:1.4rem;font-weight:900;color:var(--border);margin-bottom:5px}
	.agi-s.cur .agi-n{color:var(--ind)}
	.agi-s h4{font-size:.8rem;font-weight:700;margin-bottom:3px}
	.agi-s p{font-size:.72rem;color:var(--muted)}
	.cur-b{display:inline-block;background:var(--ind);color:#fff;font-size:.62rem;font-weight:700;padding:2px 7px;border-radius:100px;margin-top:6px}

	/* ── ROADMAP ── */
	.rm-item{display:flex;gap:18px;padding:18px 0;border-bottom:1px solid var(--border)}
	.rm-item:last-child{border-bottom:none}
	.rm-dot{flex-shrink:0;width:38px;height:38px;border-radius:50%;display:flex;align-items:center;justify-content:center;font-weight:800;font-size:.82rem}
	.rm-done{background:var(--em);color:#fff}
	.rm-act{background:var(--ind);color:#fff;box-shadow:0 0 0 4px var(--ind-xl)}
	.rm-pend{background:var(--border);color:var(--muted)}
	.rm-content h4{font-weight:700;margin-bottom:3px}
	.rm-content p{font-size:.83rem;color:var(--muted)}

	/* ── PILLARS ── */
	.pillars{display:grid;grid-template-columns:repeat(5,1fr);gap:10px}
	@media(max-width:800px){.pillars{grid-template-columns:repeat(3,1fr)}}
	.pil{background:#fff;border:1px solid var(--border);border-radius:var(--r-sm);padding:16px 12px;text-align:center}
	.pil-n{font-size:1.5rem;font-weight:900;color:var(--ind);line-height:1;margin-bottom:5px}
	.pil h4{font-size:.8rem;font-weight:700;margin-bottom:3px}
	.pil p{font-size:.72rem;color:var(--muted)}

	/* ── HIGHLIGHT BOX ── */
	.hl{background:linear-gradient(135deg,var(--ind-xl),var(--cyn-l));border:1px solid rgba(99,102,241,.18);border-radius:var(--r);padding:24px;margin:20px 0}
	.hl h3{color:var(--ind);font-size:.95rem;font-weight:800;margin-bottom:6px}
	.hl p{font-size:.85rem;color:var(--muted)}

	/* ── PRESS ── */
	.pl{display:flex;flex-direction:column;gap:10px}
	.pi{background:#fff;border:1px solid var(--border);border-radius:var(--r-sm);padding:14px 18px;display:flex;gap:14px;align-items:center}
	.pd{width:7px;height:7px;border-radius:50%;background:var(--ind);flex-shrink:0}
	.pi-date{font-size:.73rem;color:var(--light);white-space:nowrap;flex-shrink:0}
	.pi-media{font-size:.73rem;font-weight:700;color:var(--ind);white-space:nowrap;flex-shrink:0;min-width:68px}
	.pi-title{font-size:.86rem;font-weight:600;flex:1}
	.pi a{font-size:.75rem;color:var(--ind);text-decoration:none;font-weight:600;white-space:nowrap}

	/* ── PATENT ── */
	.patent-grid{display:grid;grid-template-columns:repeat(2,1fr);gap:14px}
	@media(max-width:600px){.patent-grid{grid-template-columns:1fr}}
	.pat{background:#fff;border:1px solid var(--border);border-radius:var(--r-sm);padding:16px;display:flex;gap:12px}
	.pat-n{flex-shrink:0;background:var(--ind);color:#fff;width:26px;height:26px;border-radius:6px;display:flex;align-items:center;justify-content:center;font-size:.72rem;font-weight:800}
	.pat h4{font-size:.82rem;font-weight:700;margin-bottom:2px}
	.pat p{font-size:.75rem;color:var(--muted)}

	/* ── 4-LAYER ── */
	.layers{display:grid;grid-template-columns:repeat(4,1fr);gap:16px}
	@media(max-width:700px){.layers{grid-template-columns:repeat(2,1fr)}}

	/* ── VIDEO ── */
	.vid-wrap{background:linear-gradient(135deg,#0F172A,#1E1B4B);border-radius:var(--r);padding:48px 22px;text-align:center;margin:40px 0}
	.vid-wrap h2{color:#fff;font-size:1.5rem;font-weight:800;margin-bottom:8px}
	.vid-wrap p{color:#94A3B8;margin-bottom:28px}
	.vid-box{max-width:820px;margin:0 auto;border-radius:12px;overflow:hidden;box-shadow:0 8px 40px rgba(0,0,0,.5)}
	.vid-box video{width:100%;display:block;background:#000}

	/* ── DOCKER CARD ── */
	.docker-card{background:#fff;border:1px solid var(--border);border-radius:var(--r);padding:24px;box-shadow:var(--sh)}
	.docker-row{display:flex;align-items:center;gap:12px;padding:10px 0;border-bottom:1px solid var(--border)}
	.docker-row:last-child{border-bottom:none}
	.docker-name{font-size:.85rem;font-weight:700;min-width:160px}
	.docker-desc{font-size:.8rem;color:var(--muted);flex:1}
	.docker-speed{font-size:.8rem;font-weight:700;color:var(--em);white-space:nowrap}

	/* ── ATTN GRID ── */
	.attn-g{display:grid;grid-template-columns:repeat(4,1fr);gap:10px}
	@media(max-width:700px){.attn-g{grid-template-columns:repeat(2,1fr)}}

	/* ── FOOTER ── */
	footer{background:var(--text);color:#94A3B8;padding:44px 0 28px;margin-top:72px}
	.fi{display:grid;grid-template-columns:2fr 1fr 1fr 1fr;gap:36px}
	@media(max-width:768px){.fi{grid-template-columns:1fr 1fr}}
	.fb .fl{font-size:1.2rem;font-weight:900;color:#fff;margin-bottom:8px}
	.fb p{font-size:.79rem;line-height:1.7}
	.fc h4{font-size:.76rem;font-weight:700;color:#CBD5E1;margin-bottom:10px;text-transform:uppercase;letter-spacing:.5px}
	.fc a{display:block;font-size:.79rem;color:#94A3B8;text-decoration:none;margin-bottom:5px;transition:color .14s}
	.fc a:hover{color:#fff}
	.fb2{border-top:1px solid #1E293B;margin-top:28px;padding-top:20px;display:flex;justify-content:space-between;flex-wrap:wrap;gap:6px;font-size:.75rem}

	/* ── METRIC BOX ── */
	.mb{background:linear-gradient(135deg,var(--ind),var(--ind-l));border-radius:var(--r);padding:28px;color:#fff;text-align:center}
	.mb-n{font-size:2.6rem;font-weight:900;letter-spacing:-2px;line-height:1}
	.mb-l{font-size:.82rem;opacity:.8;margin-top:3px}
	.two{display:grid;grid-template-columns:1fr 1fr;gap:20px;align-items:start}
	@media(max-width:650px){.two{grid-template-columns:1fr}}
	.warn{background:#FFF7ED;border:1px solid #FED7AA;border-radius:var(--r-sm);padding:12px 16px;font-size:.8rem;color:#92400E;display:flex;gap:8px;align-items:flex-start}

	/* ── Team page ── */
	.team-hero{background:linear-gradient(135deg,var(--ind-xxl),var(--pur-l))}
	.team-grid{display:grid;grid-template-columns:repeat(auto-fit,minmax(240px,1fr));gap:20px;padding:12px 0 8px}
	.team-card{background:var(--card);border:1px solid var(--border);border-radius:18px;padding:22px 20px 20px;text-align:center;transition:transform .18s,box-shadow .18s,border-color .18s;box-shadow:var(--sh)}
	.team-card:hover{transform:translateY(-4px);box-shadow:var(--sh-lg);border-color:var(--ind-l)}
	.team-card img{width:140px;height:140px;border-radius:50%;object-fit:cover;background:var(--ind-xxl);border:3px solid var(--ind-xl);display:block;margin:0 auto 14px}
	.team-role{font-family:"JetBrains Mono",monospace;font-size:.68rem;font-weight:600;letter-spacing:1.4px;color:var(--muted);text-transform:uppercase;margin-bottom:4px}
	.team-name{font-size:1.12rem;font-weight:800;color:var(--ind);margin-bottom:10px;letter-spacing:-.3px}
	.team-quote{font-size:.86rem;color:var(--muted);line-height:1.55;font-style:italic;min-height:2.6em}
	@media(max-width:520px){.team-card img{width:120px;height:120px}}
	</style>

	<!-- NAV -->
	<nav>
	<div class="nav-logo" onclick="showPage('home')" title="VI(非) + DRAFT — 비드래프트">VI<span>DRAFT</span></div>
	<div class="nav-links">
	<a href="javascript:void(0)" onclick="showPage('home')" class="active" id="nav-home" data-i18n="nav-home">Home</a>
	<a href="javascript:void(0)" onclick="showPage('darwin')" id="nav-darwin">Darwin</a>
	<a href="javascript:void(0)" onclick="showPage('models')" id="nav-models" data-i18n="nav-models">Models</a>
	<a href="javascript:void(0)" onclick="showPage('aether')" id="nav-aether">AETHER</a>
	<a href="javascript:void(0)" onclick="showPage('vkae')" id="nav-vkae" data-i18n="nav-vkae">VKAE</a>
	<a href="javascript:void(0)" onclick="showPage('quantum')" id="nav-quantum" data-i18n="nav-quantum">Quantum</a>
	<a href="javascript:void(0)" onclick="showPage('chitos')" id="nav-chitos" data-i18n="nav-chitos">Chitos</a>
	<a href="javascript:void(0)" onclick="showPage('proof')" id="nav-proof" data-i18n="nav-proof">Achievements</a>
	<a href="javascript:void(0)" onclick="showPage('solutions')" id="nav-solutions" data-i18n="nav-solutions">Solutions</a>
	<a href="javascript:void(0)" onclick="showPage('services')" id="nav-services" data-i18n="nav-services">Services</a>
	<a href="javascript:void(0)" onclick="showPage('about')" id="nav-about" data-i18n="nav-about">Company</a>
	<a href="javascript:void(0)" onclick="showPage('blog')" id="nav-blog" data-i18n="nav-blog">Blog</a>
	<a href="javascript:void(0)" onclick="openSpotModal()" id="nav-spot" style="background:linear-gradient(90deg,#6366F1,#818CF8);color:#fff;padding:5px 13px;border-radius:100px;font-weight:700" data-i18n="nav-spot">🤖 Talk with Spot</a>
	</div>
	<div class="lang-sw">
	<button id="btn-en" class="ls-btn" onclick="setLang('en')">EN</button>
	<button id="btn-ko" class="ls-btn active" onclick="setLang('ko')">한</button>
	</div>
	<a class="nav-cta" href="https://huggingface.co/VIDraft" target="_blank">HuggingFace →</a>
	<button class="nav-burger" onclick="toggleNav()" aria-label="메뉴 열기/닫기" aria-expanded="false">☰</button>
	</nav>

	<!-- 🤖 스팟과 대화하기 — 영상 팝업(음성 자동 ON) -->
	<div id="spotModal" onclick="if(event.target===this)closeSpotModal()" style="display:none;position:fixed;inset:0;z-index:99999;background:rgba(6,10,20,.88);backdrop-filter:blur(4px);align-items:center;justify-content:center;padding:20px">
	<div style="max-width:900px;width:100%;position:relative">
	<button onclick="closeSpotModal()" aria-label="닫기" style="position:absolute;top:-44px;right:0;background:rgba(255,255,255,.14);color:#fff;border:1px solid rgba(255,255,255,.32);border-radius:50%;width:38px;height:38px;font-size:1.1rem;cursor:pointer">✕</button>
	<div style="border-radius:16px;overflow:hidden;box-shadow:0 24px 70px rgba(0,0,0,.6);background:#000">
	<video id="spotVideo" playsinline controls loop preload="none" style="width:100%;display:block;background:#000" src="https://vidraft-physical-ai-spot.static.hf.space/spot.mp4"></video>
	</div>
	<div style="text-align:center;color:#CBD5E1;font-size:.82rem;margin-top:10px" data-i18n="spot-cap">VIDRAFT on-device VLM on Boston Dynamics Spot — voice command & conversation</div>
	</div>
	</div>
	<script>
	function openSpotModal(){
	var m=document.getElementById('spotModal'), v=document.getElementById('spotVideo');
	if(!m\|\|!v) return;
	m.style.display='flex'; document.body.style.overflow='hidden';
	v.muted=false; v.currentTime=0;
	v.play().catch(function(){ v.muted=true; v.play().catch(function(){}); }); // 음성 우선, 차단 시 음소거 폴백
	if(typeof closeNav==='function') closeNav();
	}
	function closeSpotModal(){
	var m=document.getElementById('spotModal'), v=document.getElementById('spotVideo');
	if(!m\|\|!v) return;
	m.style.display='none'; document.body.style.overflow=''; v.pause();
	}
	document.addEventListener('keydown', function(e){ if(e.key==='Escape') closeSpotModal(); });
	</script>

	<!-- ═══════════ HOME ═══════════ -->
	<div class="page active" id="page-home">
	<div class="hero">
	<div class="container">
	<div class="badge" data-i18n="hero-badge">🇰🇷 K-AI #1 · GPQA Diamond 90.9% · Polaris 14× Champion · KAIT GPU Support Award</div>
	<h1 data-i18n="hero-h1">Evolving AI.<br><span>Thinking AGI.</span></h1>
	<p class="hero-sub" data-i18n="hero-sub">Pre-AGI platform made in Korea — Darwin delivers results, AETHER designs the future.</p>
	<!-- 더브이씨(TheVC) 주간 조회수 배지 (확대·히어로 CTA 대체) -->
	<div style="margin-top:34px">
	<a href="https://thevc.kr/vidraft" target="_blank" rel="noopener noreferrer" style="display:inline-block;line-height:0;transition:transform .15s ease" onmouseover="this.style.transform='translateY(-3px)'" onmouseout="this.style.transform='none'" aria-label="더브이씨 비드래프트 주간 조회수">
	<img src="https://thevc.kr/api/interaction/widget/badge/299a68af70776efd906fe8b0?year=2026&week=28&theme=light" alt="2026년 28째주 더브이씨 조회수" loading="lazy" style="height:72px;width:auto;border-radius:14px;box-shadow:0 8px 28px rgba(67,56,202,.22)">
	</a>
	</div>
	</div>
	</div>

	<!-- ═══════════ LIVE ECOSYSTEM DASHBOARD ═══════════ -->
	<section class="dash">
	<style>
	.dash{background:linear-gradient(180deg,#F4F6FF 0%,#FFFFFF 100%);border-top:1px solid var(--border);border-bottom:1px solid var(--border);padding:32px 0 38px;margin-top:6px}
	.dash-head{display:flex;justify-content:space-between;align-items:flex-end;gap:16px;flex-wrap:wrap;margin-bottom:20px}
	.dash-kicker{display:flex;align-items:center;gap:7px;font-size:.72rem;font-weight:800;letter-spacing:1.1px;color:var(--ind);text-transform:uppercase}
	.live-dot{width:8px;height:8px;border-radius:50%;background:var(--em);animation:lpulse 1.8s infinite}
	@keyframes lpulse{0%{box-shadow:0 0 0 0 rgba(16,185,129,.45)}70%{box-shadow:0 0 0 7px rgba(16,185,129,0)}100%{box-shadow:0 0 0 0 rgba(16,185,129,0)}}
	.dash-title{font-size:clamp(1.3rem,3vw,1.85rem);font-weight:900;letter-spacing:-.5px;margin-top:6px}
	.dash-title span{color:var(--ind)}
	.dash-upd{font-size:.72rem;color:var(--light)}
	.kpi-grid{display:grid;grid-template-columns:repeat(6,1fr);gap:12px;margin-bottom:16px}
	.kpi{background:var(--card);border:1px solid var(--border);border-radius:14px;padding:14px 15px;box-shadow:var(--sh);position:relative;overflow:hidden;display:block;text-decoration:none;color:inherit;transition:transform .15s ease,box-shadow .15s ease}
	a.kpi:hover{transform:translateY(-3px);box-shadow:var(--sh-lg)}
	a.kpi:hover .kpi-go{opacity:1}
	.kpi-go{position:absolute;top:9px;right:10px;font-size:.8rem;color:var(--kc,var(--ind));opacity:.28;transition:opacity .15s ease}
	.kpi::before{content:'';position:absolute;left:0;top:0;bottom:0;width:3px;background:var(--kc,var(--ind))}
	.kpi-ic{font-size:1.1rem;margin-bottom:6px;line-height:1}
	.kpi-num{font-size:1.5rem;font-weight:900;color:var(--text);line-height:1}
	.kpi-lb{font-size:.7rem;color:var(--muted);margin-top:6px;font-weight:600;line-height:1.25}
	.chart-grid{display:grid;grid-template-columns:repeat(2,1fr);gap:14px}
	.chart-card{background:var(--card);border:1px solid var(--border);border-radius:16px;padding:16px 18px;box-shadow:var(--sh)}
	.chart-h{font-size:.83rem;font-weight:800;color:var(--text);margin-bottom:14px;display:flex;align-items:center;gap:6px}
	.bar-row{display:flex;align-items:center;gap:10px;margin-bottom:9px}
	.bar-label{flex:0 0 42%;font-size:.75rem;color:var(--text);font-weight:600;white-space:nowrap;overflow:hidden;text-overflow:ellipsis}
	.bar-track{flex:1;height:15px;background:var(--ind-xxl);border-radius:8px;overflow:hidden}
	.bar-fill{height:100%;border-radius:8px;transition:width .9s cubic-bezier(.2,.8,.2,1)}
	.bar-val{flex:0 0 auto;font-size:.73rem;font-weight:800;color:var(--muted);min-width:48px;text-align:right}
	.vbar-wrap{display:flex;align-items:flex-end;justify-content:space-around;height:150px;gap:10px;padding-top:16px}
	.vbar-col{flex:1;display:flex;flex-direction:column;align-items:center;height:100%;justify-content:flex-end}
	.vbar-v{font-size:.74rem;font-weight:800;color:var(--ind);margin-bottom:4px}
	.vbar-bar{width:100%;max-width:44px;background:linear-gradient(180deg,var(--ind-l),var(--ind));border-radius:7px 7px 0 0;transition:height .9s cubic-bezier(.2,.8,.2,1);min-height:4px}
	.vbar-l{font-size:.71rem;color:var(--muted);margin-top:7px;font-weight:700}
	.donut-wrap{display:flex;align-items:center;gap:18px;flex-wrap:wrap}
	.donut-svg{width:118px;height:118px;flex:0 0 118px}
	.donut-c1{font-size:15px;font-weight:900;fill:var(--text)}
	.donut-c2{font-size:8px;fill:var(--light);font-weight:600}
	.donut-lg{flex:1;min-width:130px}
	.lg-row{font-size:.76rem;color:var(--muted);margin-bottom:8px;display:flex;align-items:center;gap:7px}
	.lg-dot{width:10px;height:10px;border-radius:3px;flex:0 0 10px}
	.lg-row b{color:var(--text);margin-left:auto}
	@media(max-width:820px){ .kpi-grid{grid-template-columns:repeat(3,1fr)} .chart-grid{grid-template-columns:1fr} }
	@media(max-width:440px){ .kpi-grid{grid-template-columns:repeat(2,1fr)} }
	</style>
	<div class="container">
	<div class="dash-head">
	<div>
	<div class="dash-kicker"><span class="live-dot"></span><span data-i18n="dash-kicker">Live Ecosystem Dashboard</span></div>
	<div class="dash-title" data-i18n="dash-title">The Darwin <span>Ecosystem</span> at a glance</div>
	</div>
	<div class="dash-upd"><span data-i18n="dash-upd">Updated</span> <span id="dash-gen"></span></div>
	</div>
	<div class="kpi-grid" id="kpi-grid"></div>
	<div class="chart-grid">
	<div class="chart-card"><div class="chart-h">📈 <span data-i18n="ch-top">Top Official Models by Downloads</span></div><div id="ch-top"></div></div>
	<div class="chart-card"><div class="chart-h">🚀 <span data-i18n="ch-mo">Model Release Momentum (2026)</span></div><div id="ch-mo"></div></div>
	<div class="chart-card"><div class="chart-h">💎 <span data-i18n="ch-gpqa">GPQA Diamond — Darwin Family</span></div><div id="ch-gpqa"></div></div>
	<div class="chart-card"><div class="chart-h">🌐 <span data-i18n="ch-eco">Downloads by Source</span></div><div id="ch-eco"></div></div>
	</div>
	</div>
	</section>
	<script>
	(function(){
	function fmt(n){return (n\|\|0).toLocaleString('en-US');}
	function fmtK(n){n=n\|\|0;return n>=1e6?(n/1e6).toFixed(2)+'M':n>=1e3?(Math.round(n/100)/10)+'K':''+n;}
	function L(){return localStorage.getItem('vd-lang')\|\|'ko';}
	var MON=['','Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'];
	function hbars(id,items,accent,maxOv){
	var el=document.getElementById(id); if(!el)return;
	var max=maxOv\|\|Math.max.apply(null,items.map(function(x){return x.v;}))\|\|1;
	el.innerHTML=items.map(function(x){var pct=Math.max(4,x.v/max*100);
	return '<div class="bar-row"><div class="bar-label" title="'+x.l+'">'+x.l+'</div>'
	+'<div class="bar-track"><div class="bar-fill" style="width:'+pct+'%;background:'+(x.c\|\|accent)+'"></div></div>'
	+'<div class="bar-val">'+x.d+'</div></div>';}).join('');
	}
	function vbars(id,items){
	var el=document.getElementById(id); if(!el)return;
	var max=Math.max.apply(null,items.map(function(x){return x.v;}))\|\|1;
	el.innerHTML='<div class="vbar-wrap">'+items.map(function(x){var h=Math.max(5,x.v/max*100);
	return '<div class="vbar-col"><div class="vbar-v">'+x.v+'</div><div class="vbar-bar" style="height:'+h+'%"></div><div class="vbar-l">'+x.l+'</div></div>';}).join('')+'</div>';
	}
	function donut(id,segs){
	var el=document.getElementById(id); if(!el)return;
	var total=segs.reduce(function(a,b){return a+b.v;},0)\|\|1,r=52,cx=60,cy=60,circ=2Math.PIr,off=0;
	var arcs=segs.map(function(s){var len=s.v/total*circ;
	var a='<circle cx="'+cx+'" cy="'+cy+'" r="'+r+'" fill="none" stroke="'+s.c+'" stroke-width="15" stroke-dasharray="'+len+' '+(circ-len)+'" stroke-dashoffset="'+(-off)+'" transform="rotate(-90 '+cx+' '+cy+')"/>';
	off+=len;return a;}).join('');
	var lg=segs.map(function(s){return '<div class="lg-row"><span class="lg-dot" style="background:'+s.c+'"></span><span data-i18n="'+s.k+'">'+s.l+'</span> <b>'+Math.round(s.v/total*100)+'%</b></div>';}).join('');
	el.innerHTML='<div class="donut-wrap"><svg viewBox="0 0 120 120" class="donut-svg">'+arcs+'<text x="60" y="57" text-anchor="middle" class="donut-c1">'+fmtK(total)+'</text><text x="60" y="72" text-anchor="middle" class="donut-c2">DL</text></svg><div class="donut-lg">'+lg+'</div></div>';
	}
	fetch('./darwin_models.json?v='+Date.now()).then(function(r){return r.json();}).then(function(d){
	var s=d.summary;
	var totalDL=(s.grand.dl_all\|\|0)+((s.other&&s.other.dl_all)\|\|0)+((s.datasets&&s.datasets.dl_all)\|\|0);
	var LK_KAI='https://news.google.com/rss/articles/CBMibkFVX3lxTFB3RlFEX3VYNGlfcno2ekRTQW94SHVxanhTazhTN3pqcF9sMEtIa1ZrTUtNYmQxaGtPWlFUS2hoR3NadEE2VEtrUllJaG9Rb3p3Uk5WZkh6dG4yTFhMMnpONEo1VkNUczNNdHhKbWVR?oc=5';
	var LK_GPQA='https://news.google.com/rss/articles/CBMibkFVX3lxTE83SHZGYXllSUdXYTg3a3pGaUViUUhfQmNuZ280RmtuSl9YeU9sLU01c1prMHBnSi1Lb2lsWnpmYnRQeXRDemJKS3ZNdzk3WS1WYW40cXdlbmhsbjhTd1JKSjkxdmxBOERDUWVndlBR?oc=5';
	var kpis=[
	{ic:'🏆',num:'#1',k:'kpi-kai',c:'var(--amb)',href:LK_KAI,ext:1},
	{ic:'💎',num:'90.9%',k:'kpi-gpqa',c:'var(--pur)',href:LK_GPQA,ext:1},
	{ic:'🧬',num:fmt(s.grand.count),k:'kpi-models',c:'var(--ind)',page:'models'},
	{ic:'⬇️',num:fmtK(totalDL),k:'kpi-dl',c:'var(--cyn)',href:'https://huggingface.co/VIDraft',ext:1},
	{ic:'🚀',num:fmt((s.spaces&&s.spaces.total)\|\|s.spaces.count),k:'kpi-spaces',c:'var(--em)',href:'https://huggingface.co/VIDraft',ext:1},
	{ic:'📊',num:fmt((s.datasets&&s.datasets.total)\|\|s.datasets.count),k:'kpi-datasets',c:'var(--ros)',href:'https://huggingface.co/VIDraft',ext:1}
	];
	document.getElementById('kpi-grid').innerHTML=kpis.map(function(k){
	var a='class="kpi" style="--kc:'+k.c+'" href="'+(k.href\|\|'javascript:void(0)')+'"'
	+(k.ext?' target="_blank" rel="noopener"':'')
	+(k.page?' onclick="showPage(\''+k.page+'\');return false;"':'');
	return '<a '+a+'><div class="kpi-ic">'+k.ic+'</div><div class="kpi-num">'+k.num+'</div><div class="kpi-lb" data-i18n="'+k.k+'"></div><span class="kpi-go">↗</span></a>';}).join('');
	var off6=(d.official\|\|[]).slice().sort(function(a,b){return b.d-a.d;}).slice(0,6);
	hbars('ch-top',off6.map(function(m){return {l:m.n,v:m.d,d:fmtK(m.d)};}),'linear-gradient(90deg,var(--ind-l),var(--ind))');
	var mo={}; (d.official\|\|[]).concat(d.community\|\|[]).forEach(function(m){if(m.c){var k=m.c.slice(0,7);mo[k]=(mo[k]\|\|0)+1;}});
	var keys=Object.keys(mo).sort();
	vbars('ch-mo',keys.map(function(k){return {l:MON[parseInt(k.slice(5),10)]\|\|k.slice(5),v:mo[k]};}));
	hbars('ch-gpqa',[
	{l:'Darwin-28B-Opus',v:88.9,d:'88.9'},{l:'Darwin-36B-Opus',v:88.4,d:'88.4'},
	{l:'Darwin-27B-Opus',v:86.9,d:'86.9'},{l:'Darwin-31B-Opus',v:85.9,d:'85.9'},
	{l:'Darwin-9B-NEG',v:84.3,d:'84.3'}],'linear-gradient(90deg,#A78BFA,var(--pur))',100);
	donut('ch-eco',[
	{l:'Community',k:'src-com',v:s.community.dl_all,c:'#4338CA'},
	{l:'Datasets',k:'src-ds',v:(s.datasets&&s.datasets.dl_all)\|\|0,c:'#06B6D4'},
	{l:'Other',k:'src-oth',v:(s.other&&s.other.dl_all)\|\|0,c:'#10B981'},
	{l:'Official',k:'src-off',v:s.official.dl_all,c:'#F59E0B'}]);
	var g=document.getElementById('dash-gen'); if(g)g.textContent=d.generated;
	if(window.setLang) setLang(localStorage.getItem('vd-lang')\|\|'ko');
	}).catch(function(e){});
	})();
	</script>

	<div class="container">
	<!-- (기존 4-스탯 → 상단 라이브 대시보드로 승격) -->

	<div class="section">
	<h2 class="st" data-i18n="home-news-h">Latest <span>Achievements</span></h2>
	<p class="ss" data-i18n="home-news-s">Key achievements by VIDraft in 2026.</p>
	<!-- KAIT 우수 판정 하이라이트 -->
	<div style="background:linear-gradient(135deg,#FEF3C7,#ECFDF5);border:2px solid var(--em);border-radius:var(--r);padding:20px 24px;margin-bottom:18px;display:flex;align-items:center;gap:20px;flex-wrap:wrap">
	<div style="font-size:2.2rem;line-height:1">🏆</div>
	<div style="flex:1;min-width:200px">
	<div style="display:flex;gap:10px;align-items:center;margin-bottom:4px;flex-wrap:wrap">
	<span style="font-size:.72rem;font-weight:700;color:#059669;background:var(--em-l);padding:2px 9px;border-radius:100px" data-i18n="kait-date">2026.6 · KAIT Project Review</span>
	<span style="font-size:.72rem;font-weight:700;color:#92400E;background:var(--amb-l);padding:2px 9px;border-radius:100px" data-i18n="kait-ref">Ref. No. RQT-25-090162</span>
	</div>
	<div style="font-size:1rem;font-weight:800;color:var(--text);margin-bottom:2px" data-i18n="kait-title">"AI Computing Resource Infrastructure Enhancement (GPU Lease Support)" — <span style="color:var(--em)">Excellent</span></div>
	<div style="font-size:.82rem;color:var(--muted)" data-i18n="kait-desc">Korea Association for ICT Promotion (KAIT) · GPU Lease Support Project rated <strong>Excellent</strong>.</div>
	</div>
	<div style="background:var(--em);color:#fff;font-size:1.5rem;font-weight:900;padding:10px 22px;border-radius:10px;letter-spacing:.5px;flex-shrink:0" data-i18n="kait-badge">Excellent</div>
	</div>
	<div class="grid g3">
	<div class="card">
	<div style="display:flex;justify-content:space-between"><span style="font-size:.75rem;font-weight:700;color:var(--ind)" data-i18n="news1-media">Edaily</span><span style="font-size:.73rem;color:var(--light)">2026.06.16</span></div>
	<div class="tag t-ind">BREAKING</div>
	<h3 data-i18n="news1-title">Darwin-398B-JGOS, GPQA Diamond 90.9%</h3>
	<p data-i18n="news1-desc">180 of 198 correct. World-class performance through pure reasoning. MoE + Darwin V9 method.</p>
	<a href="https://edaily.co.kr/News/Read?mediaCodeNo=257&newsId=04513286645482376" target="_blank" style="font-size:.78rem;color:var(--ind);font-weight:600" data-i18n="news-link">Read →</a>
	</div>
	<div class="card">
	<div style="display:flex;justify-content:space-between"><span style="font-size:.75rem;font-weight:700;color:var(--ind)" data-i18n="news2-media">Seoul Shinmun</span><span style="font-size:.73rem;color:var(--light)">2026.06.09</span></div>
	<div class="tag t-em">BREAKING</div>
	<h3 data-i18n="news2-title">JGOS-31B-Citizen, K-AI Leaderboard Overall #1</h3>
	<p data-i18n="news2-desc">MSIT·NIA certified score 0.621, ranked #1. 8 of top 12 are Darwin derivatives (67%).</p>
	<a href="https://www.seoul.co.kr/news/economy/2026/06/09/20260609500152" target="_blank" style="font-size:.78rem;color:var(--ind);font-weight:600" data-i18n="news-link">Read →</a>
	</div>
	<div class="card">
	<div style="display:flex;justify-content:space-between"><span style="font-size:.75rem;font-weight:700;color:var(--ind)" data-i18n="news3-media">Tencent News</span><span style="font-size:.73rem;color:var(--light)">2026.05.21</span></div>
	<div class="tag t-cyn">GLOBAL</div>
	<h3 data-i18n="news3-title">Tencent (China’s #1 Portal) Spotlights Darwin</h3>
	<p data-i18n="news3-desc">China’s largest portal features Darwin’s “genetic recombination” merging — smarter AI without retraining.</p>
	<a href="https://news.qq.com/rain/a/20260521A05E8900" target="_blank" style="font-size:.78rem;color:var(--ind);font-weight:600" data-i18n="news-link">Read →</a>
	</div>
	</div>
	</div>

	<div class="section">
	<style>
	.press-wrap{border:1px solid var(--border);border-radius:16px;overflow:hidden;box-shadow:var(--sh);background:var(--card)}
	.press-scroll{max-height:520px;overflow:auto}
	.press-item{display:flex;align-items:center;gap:12px;padding:11px 16px;border-top:1px solid var(--border);text-decoration:none;color:inherit;transition:background .12s}
	.press-item:first-child{border-top:none}
	.press-item:hover{background:var(--ind-xxl)}
	.press-date{flex:0 0 84px;font-size:.72rem;color:var(--light);font-weight:600;font-variant-numeric:tabular-nums}
	.press-src{flex:0 0 auto;min-width:82px;max-width:130px;font-size:.7rem;font-weight:700;color:var(--ind);background:var(--ind-xl);padding:2px 9px;border-radius:100px;text-align:center;white-space:nowrap;overflow:hidden;text-overflow:ellipsis}
	.press-flag{flex:0 0 auto;width:22px;height:15px;border-radius:3px;overflow:hidden;box-shadow:0 0 0 .5px var(--border);line-height:0}
	.press-flag svg{width:100%;height:100%;display:block}
	.press-title{flex:1;font-size:.86rem;color:var(--text);font-weight:600;line-height:1.35;min-width:0}
	@media(max-width:600px){ .press-src{display:none} .press-date{flex:0 0 62px} }
	</style>
	<h2 class="st" data-i18n="press-h">In the <span>Press</span></h2>
	<p class="ss"><span data-i18n="press-s">VIDraft across Korean tech media & the founder's essays.</span> <span class="sec-cnt" id="cnt-press"></span></p>
	<div class="press-wrap"><div class="press-scroll" id="press-list"></div></div>
	</div>
	<script>
	(function(){
	function esc(s){return (s\|\|'').replace(/</g,'<').replace(/>/g,'>');}
	function isBrunch(a){ var s=(a.s\|\|''); return s.indexOf('브런치')>=0 \|\| s.toLowerCase().indexOf('brunch')>=0; }
	var FLAG={
	kr:'<svg viewBox="0 0 22 15"><rect width="22" height="15" fill="#fff"/><path d="M7 7.5A4 4 0 0 1 15 7.5Z" fill="#CD2E3A"/><path d="M7 7.5A4 4 0 0 0 15 7.5Z" fill="#0047A0"/></svg>',
	cn:'<svg viewBox="0 0 22 15"><rect width="22" height="15" fill="#DE2910"/><polygon points="6,3.2 6.85,5.15 8.9,5.15 7.25,6.5 7.85,8.5 6,7.3 4.15,8.5 4.75,6.5 3.1,5.15 5.15,5.15" fill="#FFDE00"/></svg>',
	ru:'<svg viewBox="0 0 22 15"><rect width="22" height="5" fill="#fff"/><rect y="5" width="22" height="5" fill="#0039A6"/><rect y="10" width="22" height="5" fill="#D52B1E"/></svg>',
	tw:'<svg viewBox="0 0 22 15"><rect width="22" height="15" fill="#FE0000"/><rect width="11" height="7.5" fill="#000095"/><circle cx="5.5" cy="3.75" r="2.1" fill="#fff"/><circle cx="5.5" cy="3.75" r="1.2" fill="#000095"/></svg>',
	jp:'<svg viewBox="0 0 22 15"><rect width="22" height="15" fill="#fff"/><circle cx="11" cy="7.5" r="4" fill="#BC002D"/></svg>',
	br:'<svg viewBox="0 0 22 15"><rect width="22" height="15" fill="#009C3B"/><polygon points="11,2 20,7.5 11,13 2,7.5" fill="#FFDF00"/><circle cx="11" cy="7.5" r="2.6" fill="#002776"/></svg>',
	es:'<svg viewBox="0 0 22 15"><rect width="22" height="15" fill="#AA151B"/><rect y="3.75" width="22" height="7.5" fill="#F1BF00"/></svg>',
	uz:'<svg viewBox="0 0 22 15"><rect width="22" height="5" fill="#0099B5"/><rect y="5" width="22" height="5" fill="#fff"/><rect y="10" width="22" height="5" fill="#1EB53A"/><rect y="4.6" width="22" height="0.7" fill="#CE1126"/><rect y="9.7" width="22" height="0.7" fill="#CE1126"/></svg>',
	il:'<svg viewBox="0 0 22 15"><rect width="22" height="15" fill="#fff"/><rect y="2.2" width="22" height="1.9" fill="#0038B8"/><rect y="10.9" width="22" height="1.9" fill="#0038B8"/><path d="M11 4.7 12.8 7.8 9.2 7.8Z" fill="none" stroke="#0038B8" stroke-width=".7"/><path d="M11 10.3 9.2 7.2 12.8 7.2Z" fill="none" stroke="#0038B8" stroke-width=".7"/></svg>',
	it:'<svg viewBox="0 0 22 15"><rect width="7.33" height="15" fill="#009246"/><rect x="7.33" width="7.34" height="15" fill="#fff"/><rect x="14.67" width="7.33" height="15" fill="#CE2B37"/></svg>',
	gl:'<svg viewBox="0 0 22 15"><rect width="22" height="15" fill="#E9F1FB"/><g fill="none" stroke="#1C7293" stroke-width=".8"><circle cx="11" cy="7.5" r="4.2"/><ellipse cx="11" cy="7.5" rx="1.8" ry="4.2"/><line x1="6.8" y1="7.5" x2="15.2" y2="7.5"/></g></svg>'
	};
	function flagFor(s){ s=s\|\|''; var M=[['러시아','ru'],['우즈베키스탄','uz'],['우즈벡','uz'],['중국','cn'],['중화권','cn'],['대만','tw'],['일본','jp'],['브라질','br'],['포르투갈','br'],['스페인','es'],['이탈리아','it'],['이스라엘','il'],['영문','gl'],['글로벌','gl'],['배포','gl']]; for(var i=0;i<M.length;i++){ if(s.indexOf(M[i][0])>=0) return FLAG[M[i][1]]\|\|FLAG.gl; } return FLAG.kr; }
	function srcName(s){ return (s\|\|'').replace(/\s$[^)]$\s*$/,''); }
	function item(a){
	return '<a class="press-item" href="'+a.u+'" target="_blank" rel="noopener">'
	+'<span class="press-date">'+(a.d\|\|'')+'</span>'
	+'<span class="press-flag" title="'+esc(a.s)+'">'+flagFor(a.s)+'</span>'
	+'<span class="press-src">'+esc(srcName(a.s))+'</span>'
	+'<span class="press-title">'+esc(a.t)+'</span></a>';
	}
	function paint(elId, cntId, list){
	var el=document.getElementById(elId); if(!el)return;
	el.innerHTML=list.map(item).join('');
	var c=cntId&&document.getElementById(cntId); if(c)c.textContent=list.length;
	}
	fetch('./news.json?v='+Date.now()).then(function(r){return r.json();}).then(function(d){
	var items=d.items\|\|[];
	paint('press-list','cnt-press', items.filter(function(a){return !isBrunch(a);})); // 홈: 브런치(창업자 블로그) 제외 = 제3자 매체만
	paint('press-list-proof','cnt-press-proof', items); // 성과: 전체(브런치 포함)
	}).catch(function(){});
	})();
	</script>

	<div class="section">
	<h2 class="st" data-i18n="home-agi-h">Journey to <span>AGI</span></h2>
	<p class="ss" data-i18n="home-agi-s">AGI is achieved step by step. VIDraft is now at the Pre-AGI stage.</p>
	<div class="agi">
	<div class="agi-s"><div class="agi-n">1</div><h4>Partial</h4><p data-i18n="agi-p1">Single-task specialization</p></div>
	<div class="agi-s"><div class="agi-n">2</div><h4>Proto</h4><p data-i18n="agi-p2">Multi-task combination</p></div>
	<div class="agi-s cur"><div class="agi-n">3</div><h4>Pre-AGI</h4><p data-i18n="agi-p3">Metacognition + Self-correction + Swarm collaboration</p><div class="cur-b" data-i18n="agi-now">▶ Now</div></div>
	<div class="agi-s"><div class="agi-n">4</div><h4>Pass</h4><p data-i18n="agi-p4">True AGI</p></div>
	<div class="agi-s"><div class="agi-n">5</div><h4>Post</h4><p data-i18n="agi-p5">Post AGI</p></div>
	</div>
	</div>

	<div class="section">
	<h2 class="st" data-i18n="home-sys-h">4-Layer Integrated <span>System</span></h2>
	<p class="ss" data-i18n="home-sys-s">Not a single model — four layers organically integrated to design Embodied AGI.</p>
	<div class="layers">
	<div class="card"><div class="ci ci-ind">🧬</div><div class="tag t-ind">LAYER 01 · NOW</div><h3>Darwin</h3><p data-i18n="layer-darwin-p">Evolutionary model family. K-AI #1 + GPQA 90.9%</p></div>
	<div class="card"><div class="ci ci-cyn">⚡</div><div class="tag t-cyn">LAYER 02 · NEXT</div><h3>AETHER</h3><p data-i18n="layer-aether-p">5/7/11-way heterogeneous attention Pre-AGI architecture</p></div>
	<div class="card"><div class="ci ci-em">🌍</div><div class="tag t-em">LAYER 03 · WORLD</div><h3>PROMETHEUS</h3><p data-i18n="layer-prom-p">World model. Sole Track C pass on WM Bench (726 pts)</p></div>
	<div class="card"><div class="ci ci-amb">🤖</div><div class="tag t-amb">LAYER 04 · BODY</div><h3>HEPHAESTUS</h3><p data-i18n="layer-heph-p">Embodied AI · 4 Jetson platforms operationally verified</p></div>
	</div>
	<div style="text-align:center;margin-top:20px;font-size:.88rem;color:var(--muted);font-weight:600" data-i18n="layer-chain">
	LLM → AETHER → PROMETHEUS → HEPHAESTUS = <strong style="color:var(--ind)">Embodied AGI</strong>
	</div>
	</div>

	</div>

	</div>

	<!-- ═══════════ DARWIN ═══════════ -->
	<div class="page" id="page-darwin">
	<div class="ph" style="background:linear-gradient(135deg,#EEF2FF,#F0FDFF)">
	<div class="container">
	<div class="badge">DARWIN PLATFORM</div>
	<h1 data-i18n="darwin-h1">Korea's #1 AI Platform Delivering Measurable Results</h1>
	<p data-i18n="darwin-sub">K-AI #1 · GPQA Diamond 90.9% · Polaris Global 14× Champion · Metacognition Leaderboard #1</p>
	</div>
	</div>

	<!-- YouTube 소개 영상 — Darwin 페이지 (메인페이지에서 이동) -->
	<div class="container" style="padding-top:28px;padding-bottom:0">
	<div style="max-width:820px;margin:0 auto;border-radius:14px;overflow:hidden;box-shadow:0 16px 48px rgba(99,102,241,.18)">
	<div style="position:relative;padding-bottom:56.25%;height:0">
	<iframe src="https://www.youtube.com/embed/ICRUj3ZqP2E?autoplay=1&mute=1&loop=1&playlist=ICRUj3ZqP2E"
	style="position:absolute;top:0;left:0;width:100%;height:100%;border:none"
	allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
	allowfullscreen></iframe>
	</div>
	</div>
	</div>

	<div class="subtab-bar">
	<div class="subtab-inner">
	<div class="stab active" onclick="switchTab('darwin','leaderboard',this)" data-i18n="darwin-tab1">📊 Leaderboard</div>
	<div class="stab" onclick="switchTab('darwin','models',this)" data-i18n="darwin-tab2">🧬 Model Family</div>
	</div>
	</div>

	<div class="container">
	<!-- 리더보드 성과 -->
	<div class="stab-content active" id="darwin-leaderboard">
	<div class="section">
	<div class="grid g3" style="margin-bottom:36px">
	<div class="mb"><div class="mb-n">90.9%</div><div class="mb-l">Darwin-398B-JGOS · GPQA Diamond</div></div>
	<div class="card" style="text-align:center"><div class="sn" style="font-size:2.2rem;color:var(--em)">#1</div><div class="sl" style="margin-top:6px" data-i18n="darwin-lb-kai">K-AI Leaderboard Overall #1<br><small>JGOS-31B-Citizen 0.621</small></div></div>
	<div class="card" style="text-align:center"><div class="sn" style="font-size:2.2rem;color:var(--cyn)" data-i18n="darwin-lb-pol-n">14×</div><div class="sl" style="margin-top:6px" data-i18n="darwin-lb-pol">Polaris Global Drug Discovery<br><small>ADMET + Efficacy + Kinase</small></div></div>
	</div>

	<h2 class="st" data-i18n="darwin-gpqa-h">GPQA Diamond <span>Global Leaderboard</span></h2>
	<p class="ss" data-i18n="darwin-gpqa-s">HuggingFace certified · As of June 2026</p>
	<div class="tw" style="margin-bottom:40px">
	<table>
	<thead><tr><th data-i18n="th-rank">Rank</th><th data-i18n="th-model">Model</th><th data-i18n="th-score">Score</th><th data-i18n="th-note">Note</th></tr></thead>
	<tbody>
	<tr style="background:#FFF7ED"><td><span class="rb rb-g">★</span></td><td><strong>Darwin-398B-JGOS</strong></td><td><strong>90.9%</strong></td><td><span class="tag t-ind" data-i18n="tag-vid-latest">VIDraft Latest</span></td></tr>
	<tr><td><span class="rb rb-v">1</span></td><td>Darwin-28B-Opus</td><td>88.89%</td><td><span class="tag t-ind" data-i18n="tag-vid">VIDraft</span></td></tr>
	<tr><td><span class="rb rb-s">2</span></td><td>Qwen3.5-397B-A17B</td><td>88.40%</td><td>Alibaba</td></tr>
	<tr><td>3</td><td>Kimi-K2.5</td><td>87.60%</td><td>Moonshot</td></tr>
	<tr><td><span class="rb rb-v">5</span></td><td>Darwin-36B-Opus</td><td>88.40%</td><td><span class="tag t-ind" data-i18n="tag-vid">VIDraft</span></td></tr>
	<tr><td><span class="rb rb-v">11</span></td><td>Darwin-27B-Opus</td><td>86.90%</td><td><span class="tag t-ind" data-i18n="tag-vid">VIDraft</span></td></tr>
	<tr><td><span class="rb rb-v">16</span></td><td>Darwin-31B-Opus</td><td>85.90%</td><td><span class="tag t-ind" data-i18n="tag-vid">VIDraft</span></td></tr>
	<tr><td><span class="rb rb-v">21</span></td><td>Darwin-9B-NEG</td><td>84.34%</td><td><span class="tag t-ind" data-i18n="tag-vid">VIDraft</span></td></tr>
	</tbody>
	</table>
	</div>

	<h2 class="st" data-i18n="darwin-kai-h">K-AI <span>Leaderboard</span></h2>
	<p class="ss" data-i18n="darwin-kai-s">MSIT·NIA certified · Blind evaluation · As of June 2026</p>
	<div class="tw" style="margin-bottom:24px">
	<table>
	<thead><tr><th data-i18n="th-rank">Rank</th><th data-i18n="th-model">Model</th><th data-i18n="th-score">Score</th><th data-i18n="th-cat">Category</th></tr></thead>
	<tbody>
	<tr style="background:#F0FDF4"><td><span class="rb rb-g">1</span></td><td><strong>JGOS-31B-Citizen</strong></td><td><strong>0.621</strong></td><td><span class="tag t-ind" data-i18n="tag-vid-official">VIDraft Official</span></td></tr>
	<tr><td>2</td><td>AWAXIS-KR-31B-v5</td><td>—</td><td><span class="tag t-cyn" data-i18n="tag-darwin-der">Darwin Derivative</span></td></tr>
	<tr><td>6</td><td>Rogue-28B-MIX</td><td>—</td><td><span class="tag t-cyn" data-i18n="tag-darwin-der">Darwin Derivative</span></td></tr>
	<tr><td>7</td><td>AWAXIS-Hybrid-28B</td><td>—</td><td><span class="tag t-cyn" data-i18n="tag-darwin-der">Darwin Derivative</span></td></tr>
	<tr><td>8</td><td>Warecube-KO-27B-v3</td><td>—</td><td><span class="tag t-cyn" data-i18n="tag-darwin-der">Darwin Derivative</span></td></tr>
	<tr><td>9</td><td>Rogue-27B-KR</td><td>—</td><td><span class="tag t-cyn" data-i18n="tag-darwin-der">Darwin Derivative</span></td></tr>
	<tr><td>11</td><td>AWAXIS-Think-28B</td><td>—</td><td><span class="tag t-cyn" data-i18n="tag-darwin-der">Darwin Derivative</span></td></tr>
	<tr><td>12</td><td>TenOS-Ko-28B-v3</td><td>—</td><td><span class="tag t-cyn" data-i18n="tag-darwin-der">Darwin Derivative</span></td></tr>
	</tbody>
	</table>
	</div>
	<div class="hl"><h3 data-i18n="darwin-kai-hl-h">📊 11 of the K-AI Top 20 are Darwin models</h3><p data-i18n="darwin-kai-hl-p">A result that emerged naturally in the MSIT·NIA blind evaluation. Third-party certified figures, not self-reported.</p></div>
	</div>
	</div>

	<!-- 모델 패밀리 -->
	<div class="stab-content" id="darwin-models">
	<div class="section">
	<h2 class="st" data-i18n="darwin-models-h">Darwin <span>Official Model Family</span></h2>
	<p class="ss" data-i18n="darwin-models-s">20+ official · 1,200+ derivatives & quant variants · 1M+ all-time downloads (HF-verified 2026-07)</p>
	<div class="grid g3" style="margin-bottom:12px">
	<div class="card"><div class="tag t-ros">★ Most Downloaded</div><h3>Darwin-9B-NEG <span style="font-size:.66rem;font-weight:800;color:var(--ros);background:rgba(244,63,94,.12);padding:2px 7px;border-radius:100px;margin-left:4px;white-space:nowrap;vertical-align:middle">⬇️ 575K</span></h3><p data-i18n="m-9bneg-p">9B NEG single-pass evolution. Most-downloaded model in the Darwin family — 575K+ all-time.</p></div>
	<div class="card"><div class="tag t-ind">GPQA 88.4%</div><h3>Darwin-36B-Opus <span style="font-size:.66rem;font-weight:800;color:var(--ros);background:rgba(244,63,94,.12);padding:2px 7px;border-radius:100px;margin-left:4px;white-space:nowrap;vertical-align:middle">⬇️ 102K</span></h3><p data-i18n="m-36bopus-p">GPQA Diamond 88.4%. Community-favorite flagship, widely quantized and redistributed.</p></div>
	<div class="card"><div class="tag t-ind">MoE Multimodal</div><h3>Darwin-35B-A3B-Opus <span style="font-size:.66rem;font-weight:800;color:var(--ros);background:rgba(244,63,94,.12);padding:2px 7px;border-radius:100px;margin-left:4px;white-space:nowrap;vertical-align:middle">⬇️ 71.2K</span></h3><p data-i18n="m-35b-p">35B MoE flagship. GPQA Diamond 90.0%. Multimodal support.</p></div>
	<div class="card"><div class="tag t-cyn">KR Flagship</div><h3>Darwin-31B-Opus <span style="font-size:.66rem;font-weight:800;color:var(--ros);background:rgba(244,63,94,.12);padding:2px 7px;border-radius:100px;margin-left:4px;white-space:nowrap;vertical-align:middle">⬇️ 34.3K</span></h3><p data-i18n="m-31bopus-p">Korean flagship. CLIcK 84.5 · KMMLU 76. Top Korean-language Darwin.</p></div>
	<div class="card"><div class="tag t-em">Coding</div><h3>Darwin-28B-Coder <span style="font-size:.66rem;font-weight:800;color:var(--ros);background:rgba(244,63,94,.12);padding:2px 7px;border-radius:100px;margin-left:4px;white-space:nowrap;vertical-align:middle">⬇️ 32.2K</span></h3><p data-i18n="m-coder-p">Coding specialist. Top official GGUF download in the Darwin family.</p></div>
	<div class="card"><div class="tag t-pur">Cross-Arch</div><h3>Darwin-4B-Genesis <span style="font-size:.66rem;font-weight:800;color:var(--ros);background:rgba(244,63,94,.12);padding:2px 7px;border-radius:100px;margin-left:4px;white-space:nowrap;vertical-align:middle">⬇️ 21.7K</span></h3><p data-i18n="m-genesis-p">Transformer × Mamba cross-breeding. CLIcK 92%. World-first heterogeneous crossbreed verified.</p></div>
	<div class="card"><div class="tag t-ind">Global GPQA #1</div><h3>Darwin-28B-Opus <span style="font-size:.66rem;font-weight:800;color:var(--ros);background:rgba(244,63,94,.12);padding:2px 7px;border-radius:100px;margin-left:4px;white-space:nowrap;vertical-align:middle">⬇️ 14.3K</span></h3><p data-i18n="m-darwin28-p">GPQA Diamond 88.89%. Surpasses 400B class with no extra training. arXiv 2605.14386.</p></div>
	<div class="card"><div class="tag t-em">Reasoning</div><h3>Darwin-28B-REASON <span style="font-size:.66rem;font-weight:800;color:var(--ros);background:rgba(244,63,94,.12);padding:2px 7px;border-radius:100px;margin-left:4px;white-space:nowrap;vertical-align:middle">⬇️ 13.3K</span></h3><p data-i18n="m-reason-p">Reasoning-enhanced specialist. Optimized for math·code·science reasoning.</p></div>
	<div class="card"><div class="tag t-cyn">Gen-2 Evolution</div><h3>Darwin-4B-David <span style="font-size:.66rem;font-weight:800;color:var(--ros);background:rgba(244,63,94,.12);padding:2px 7px;border-radius:100px;margin-left:4px;white-space:nowrap;vertical-align:middle">⬇️ 10.9K</span></h3><p data-i18n="m-david-p">31B-class at 4.5B. GPQA 85.0%. Cumulative +26.4%p. Fit for embodied AI & mobile.</p></div>
	<div class="card"><div class="tag t-em">K-AI Overall #1</div><h3>JGOS-31B-Citizen <span style="font-size:.66rem;font-weight:800;color:var(--ros);background:rgba(244,63,94,.12);padding:2px 7px;border-radius:100px;margin-left:4px;white-space:nowrap;vertical-align:middle">⬇️ 6.0K</span></h3><p data-i18n="m-jgos31-p">Public administration Korean. CLIcK 0.987 · KMMLU-Pro 0.725 · Com2 0.742.</p></div>
	<div class="card"><div class="tag t-cyn">KR Legal</div><h3>Darwin-28B-KR-Legal <span style="font-size:.66rem;font-weight:800;color:var(--ros);background:rgba(244,63,94,.12);padding:2px 7px;border-radius:100px;margin-left:4px;white-space:nowrap;vertical-align:middle">⬇️ 2.6K</span></h3><p data-i18n="m-legal-p">27B BF16 legal specialist. B200 load 9.7s. TPS 22.3 tok/s.</p></div>
	<div class="card"><div class="tag t-ros">TTS Voice</div><h3>Darwin-TTS-1.7B-Cross <span style="font-size:.66rem;font-weight:800;color:var(--ros);background:rgba(244,63,94,.12);padding:2px 7px;border-radius:100px;margin-left:4px;white-space:nowrap;vertical-align:middle">⬇️ 809</span></h3><p data-i18n="m-tts-p">1.7B Korean speech synthesis. Cross-architecture evolution.</p></div>
	<div class="card"><div class="tag t-amb">★ GPQA 90.9%</div><h3>Darwin-398B-JGOS <span style="font-size:.66rem;font-weight:800;color:var(--ros);background:rgba(244,63,94,.12);padding:2px 7px;border-radius:100px;margin-left:4px;white-space:nowrap;vertical-align:middle">⬇️ 404</span></h3><p data-i18n="m-jgos398-p">MoE structure, 17B active params. Darwin V9 method. World-class pure reasoning.</p></div>
	</div>
	<p style="font-size:.75rem;color:var(--muted);margin:0 0 26px" data-i18n="darwin-dl-note">⬇️ = HuggingFace all-time downloads (official + community redistributions), verified 2026-07. Darwin family total: 1M+.</p>
	<div class="hl"><h3>🧬 Darwin Family Collection</h3><p data-i18n="darwin-coll-p">Browse and download all 20 models in the HuggingFace FINAL-Bench collection.</p></div>
	<div style="margin-top:16px"><a class="btn btn-p" href="https://huggingface.co/collections/FINAL-Bench/darwin-family" target="_blank" data-i18n="darwin-coll-btn">View Darwin Family Collection →</a></div>
	</div>
	</div>

	<!-- 메타인지 -->
	</div>
	</div>

	<!-- ═══════════ AETHER ═══════════ -->
	<div class="page" id="page-aether">
	<div class="ph" style="background:linear-gradient(135deg,#EDE9FE,#E0F2FE)">
	<div class="container">
	<div class="badge" style="background:var(--pur)">AETHER ARCHITECTURE</div>
	<h1 data-i18n="aether-h1">End of single-attention era.<br><span style="color:var(--pur)">Dawn of 5/7/11-way Hybrid.</span></h1>
	<p><strong>A</strong>daptive <strong>M</strong>ulti-way <strong>T</strong>riple-symmetric <strong>H</strong>ybrid att<strong>E</strong>ntion <strong>R</strong>outing</p>
	</div>
	</div>

	<!-- MP4 소개 영상 — AETHER 페이지 (다윈 메뉴에서 이동) -->
	<div class="container" style="padding-top:28px;padding-bottom:0">
	<div style="max-width:820px;margin:0 auto;border-radius:14px;overflow:hidden;box-shadow:0 16px 48px rgba(124,58,237,.18)">
	<video id="aetherVideo" autoplay muted playsinline preload="auto" controls
	style="width:100%;display:block;background:#000"
	src="https://vidraft-ai.static.hf.space/VD1.mp4"></video>
	</div>
	</div>
	<script>
	(function(){
	var v = document.getElementById('aetherVideo');
	if(!v) return;
	var list = ['https://vidraft-ai.static.hf.space/VD1.mp4','https://vidraft-ai.static.hf.space/vd2.mp4'];
	var idx = 0;
	v.addEventListener('ended', function(){ idx = (idx + 1) % list.length; v.src = list[idx]; v.play(); });
	})();
	</script>
	<div class="container">
	<div class="section">
	<div class="grid g3" style="margin-bottom:40px">
	<div class="mb" style="background:linear-gradient(135deg,var(--pur),var(--ind-l))"><div class="mb-n" data-i18n="aether-stat-first">World First</div><div class="mb-l" data-i18n="aether-stat-first-l">5/7/11-way heterogeneous attention integrated into a single LLM</div></div>
	<div class="card" style="text-align:center"><div class="sn" style="font-size:2.2rem;color:var(--pur)">186</div><div class="sl" style="margin-top:6px" data-i18n="aether-stat-claims-l">Patent claims (KR priority + PCT)</div></div>
	<div class="card" style="text-align:center"><div class="sn" style="font-size:2.2rem;color:var(--cyn)">n³</div><div class="sl" style="margin-top:6px" data-i18n="aether-stat-n3-l">Triple Symmetry expressiveness gain</div></div>
	</div>
	<h2 class="st" data-i18n="aether-train-h"><span>3 Models</span> in Training</h2>
	<div class="grid g3" style="margin-bottom:40px">
	<div class="card"><div class="tag t-em" data-i18n="aether-m1-tag">✓ Verified</div><h3>Aether-14B-5Attn</h3><p data-i18n="aether-m1-p">5×5 Latin Square · 25 layers · 14.09B params · 5-way attention</p></div>
	<div class="card" style="border-color:var(--ind-l)"><div class="tag t-ind" data-i18n="aether-m2-tag">⏳ Training</div><h3>Aether-1B-7Attn</h3><p data-i18n="aether-m2-p">7×7 Latin Square · 49 layers · 30.6B params · 7-way attention</p></div>
	<div class="card" style="border-color:var(--cyn)"><div class="tag t-cyn" data-i18n="aether-m3-tag">⏳ Training</div><h3>Aether-30B-11Attn</h3><p data-i18n="aether-m3-p">11×11 Latin Square · 121 layers · World-first 11-way attention</p></div>
	</div>
	<h2 class="st" data-i18n="aether-attn-h">11-way <span>Heterogeneous Attention Ensemble</span></h2>
	<p class="ss" data-i18n="aether-attn-s">Integrating the latest research into a single LLM.</p>
	<div class="attn-g" style="margin-bottom:40px">
	<div class="card"><div class="tag t-ind">⭐ ACL'25</div><h3>NSA</h3><p>DeepSeek</p></div>
	<div class="card"><div class="tag t-ind">⭐ ICLR'25</div><h3>Differential</h3><p>Microsoft</p></div>
	<div class="card"><div class="tag t-cyn" data-i18n="attn-full-t">Standard</div><h3>Full Attention</h3><p>Vaswani 2017</p></div>
	<div class="card"><div class="tag t-cyn" data-i18n="attn-slide-t">Efficient</div><h3>MLA</h3><p>DeepSeek-V2</p></div>
	<div class="card"><div class="tag t-em" data-i18n="attn-gdn-t">Length</div><h3>Sliding Window</h3><p>Longformer</p></div>
	<div class="card"><div class="tag t-em" data-i18n="attn-nsa-t">Compress</div><h3>Compress</h3><p data-i18n="attn-nsa-d">Native Sparse Attention · Sequence compression</p></div>
	<div class="card"><div class="tag t-amb" data-i18n="attn-diff-t">Adaptive</div><h3>Hybrid Gate</h3><p data-i18n="attn-diff-d">Differential Attention · Adaptive noise cancellation</p></div>
	<div class="card"><div class="tag t-amb" data-i18n="attn-lin-t">Linear</div><h3>Linear</h3><p>ICML 2020</p></div>
	<div class="card"><div class="tag t-ros">SSM</div><h3>Mamba2</h3><p>Gu & Dao 2024</p></div>
	<div class="card"><div class="tag t-ros" data-i18n="attn-gate-t">Gate</div><h3>GDN</h3><p>Delta Network</p></div>
	<div class="card"><div class="tag t-pur" data-i18n="attn-hi-t">High-eff.</div><h3>Hyena</h3><p>Poli ICML 2023</p></div>
	</div>
	<h2 class="st" data-i18n="aether-road-h">Development <span>Roadmap</span></h2>
	<div style="margin-bottom:40px">
	<div class="rm-item"><div class="rm-dot rm-done">✓</div><div class="rm-content"><h4>Stage 1 — Aether-14B-5Attn <span style="color:var(--em);font-size:.8rem" data-i18n="road1-span">(Done)</span></h4><p data-i18n="road1-p">5×5 · 5-way attention · In operation</p></div></div>
	<div class="rm-item"><div class="rm-dot rm-act">2</div><div class="rm-content"><h4>Stage 2·3 — Aether-1B·30B <span style="color:var(--ind);font-size:.8rem" data-i18n="road2-span">(Training)</span></h4><p data-i18n="road2-p">7-way & 11-way parallel verification · World-first 11-way integration</p></div></div>
	<div class="rm-item"><div class="rm-dot rm-pend">5</div><div class="rm-content"><h4>Stage 5·6 — Aether-70B·150B <span style="color:var(--muted);font-size:.8rem" data-i18n="road3-span">(Q3·Q4 2026)</span></h4><p data-i18n="road3-p">Frontier challenge · KMMLU 75-85% · GPQA 75-85%</p></div></div>
	<div class="rm-item"><div class="rm-dot rm-pend">7</div><div class="rm-content"><h4>Stage 7 — Aether-300B-13Attn <span style="color:var(--muted);font-size:.8rem" data-i18n="road4-span">(Next year)</span></h4><p data-i18n="road4-p">ICLR 2027 / NeurIPS 2026 academic presentation planned</p></div></div>
	</div>
	<h2 class="st" data-i18n="aether-prin-h">AGI 5 Core <span>Design Principles</span></h2>
	<div class="pillars">
	<div class="pil"><div class="pil-n">01</div><h4 data-i18n="pil1-h">Emergence</h4><p data-i18n="pil1-p">9 emergence engines + MARL runtime</p></div>
	<div class="pil"><div class="pil-n">02</div><h4 data-i18n="pil2-h">Metacognition</h4><p data-i18n="pil2-p">8-type self-error detection · TICOS</p></div>
	<div class="pil"><div class="pil-n">03</div><h4 data-i18n="pil3-h">Self-evolution</h4><p data-i18n="pil3-p">Closed-loop perpetual learning · SLAI</p></div>
	<div class="pil"><div class="pil-n">04</div><h4 data-i18n="pil4-h">Swarm Collaboration</h4><p data-i18n="pil4-p">Multi-agent · SOMA/MOUSE</p></div>
	<div class="pil"><div class="pil-n">05</div><h4 data-i18n="pil5-h">Mutual Reinforcement</h4><p data-i18n="pil5-p">Five-element enhance/suppress · Hallucination control</p></div>
	</div>
	</div>

	<!-- 메타인지 (Darwin에서 AETHER 하부로 이전) -->
	<div class="section">
	<h2 class="st" data-i18n="darwin-meta-h">Metacognition <span>Leaderboard</span></h2>
	<p class="ss" data-i18n="darwin-meta-s">JinigenAI · VIDraft joint development · 24 AI models evaluated · Published 2026.07.01</p>
	<div class="hl" style="margin-bottom:32px">
	<h3 data-i18n="meta-quote">🧠 "AI is dangerous not when it makes an error, but when it doesn't know it has."</h3>
	<p data-i18n="meta-quote-s">JGOS-31B-Citizen avoids 398 of 400 trap questions (99.5%, #1). Metacognition = an essential AGI capability.</p>
	</div>
	<div class="grid g3" style="margin-bottom:32px">
	<div class="card"><div class="ci ci-ind">🎯</div><div class="tag t-ind" data-i18n="meta-c1-tag">World First</div><h3 data-i18n="meta-c1-h">FINAL Bench</h3><p data-i18n="meta-c1-p">World's first metacognition benchmark. 100 tasks × 15 domains × 8 types (TICOS) × 3 difficulty levels.</p></div>
	<div class="card"><div class="ci ci-em">📊</div><div class="tag t-em" data-i18n="meta-c2-tag">400 Questions</div><h3 data-i18n="meta-c2-h">Trap-Question Evaluation</h3><p data-i18n="meta-c2-p">400 questions designed to induce plausible-but-wrong answers. Measures self-error recognition.</p></div>
	<div class="card"><div class="ci ci-amb">🔌</div><div class="tag t-amb" data-i18n="meta-c3-tag">Non-invasive</div><h3 data-i18n="meta-c3-h">Metacognition Adapter</h3><p data-i18n="meta-c3-p">Analyzes internal signals to detect self-errors in advance without altering the original model's structure or weights.</p></div>
	</div>
	<div class="grid g2">
	<a class="sc" href="https://huggingface.co/collections/FINAL-Bench/metacognition-adapters" target="_blank" rel="noopener">
	<div class="sc-icon">🧩</div>
	<div class="tag t-ind" data-i18n="meta-coll-tag">11 Models</div>
	<h3>Metacognition Adapters Collection</h3>
	<p data-i18n="meta-coll-p">11 individual metacognition adapters for major models like Darwin-28B-Opus, Darwin-9B-NEG, and JGOS-31B-Citizen.</p>
	<div class="sc-link">huggingface.co/collections/FINAL-Bench/metacognition-adapters</div>
	</a>
	<a class="sc" href="https://huggingface.co/spaces/FINAL-Bench/all-bench-leaderboard" target="_blank" rel="noopener">
	<div class="sc-icon">📊</div>
	<div class="tag t-em" data-i18n="meta-lb-tag">Leaderboard</div>
	<h3>Metacognition Leaderboard</h3>
	<p data-i18n="meta-lb-p">Metacognition performance comparison leaderboard. 24 AI models evaluated across trap avoidance and self-error detection.</p>
	<div class="sc-link">huggingface.co/spaces/FINAL-Bench/all-bench-leaderboard</div>
	</a>
	</div>
	</div>
	</div>
	</div>

	<!-- ═══════════ PROOF ═══════════ -->
	<div class="page" id="page-proof">
	<div class="ph" style="background:linear-gradient(135deg,#ECFDF5,#EEF2FF)">
	<div class="container">
	<div class="badge" style="background:var(--em)">PROOF</div>
	<h1 data-i18n="proof-h1">Benchmarks. Papers. Patents. <span style="color:var(--ind)">Press Coverage.</span></h1>
	<p data-i18n="proof-sub">Results are measured, recorded, and protected.</p>
	</div>
	</div>
	<div class="subtab-bar">
	<div class="subtab-inner">
	<div class="stab active" onclick="switchTab('proof','bench',this)" data-i18n="proof-tab1">🏆 Benchmarks</div>
	<div class="stab" onclick="switchTab('proof','papers',this)" data-i18n="proof-tab2">📄 Papers</div>
	<div class="stab" onclick="switchTab('proof','patents',this)" data-i18n="proof-tab3">🔒 Patents (11)</div>
	<div class="stab" onclick="switchTab('proof','press',this)" data-i18n="proof-tab4">📰 Press</div>
	</div>
	</div>
	<div class="container">
	<div class="stab-content active" id="proof-bench">
	<div class="section">
	<!-- KAIT 우수 판정 -->
	<div style="background:linear-gradient(135deg,#ECFDF5,#FEF3C7);border:2px solid var(--em);border-radius:var(--r);padding:18px 22px;margin-bottom:22px;display:flex;align-items:center;gap:18px;flex-wrap:wrap">
	<div style="font-size:2rem">🏆</div>
	<div style="flex:1;min-width:200px">
	<div style="font-size:.72rem;font-weight:700;color:#059669;margin-bottom:3px" data-i18n="kait2-date">2026.6 · KAIT (Korea Association for ICT Promotion) · Ref. No. RQT-25-090162</div>
	<div style="font-size:.98rem;font-weight:800;color:var(--text)" data-i18n="kait2-title">"AI Computing Resource Infrastructure Enhancement (GPU Lease Support)" — <span style="color:var(--em)">Excellent</span></div>
	<div style="font-size:.8rem;color:var(--muted);margin-top:2px" data-i18n="kait2-desc">GPU Lease Support Project rated Excellent.</div>
	</div>
	<div style="background:var(--em);color:#fff;font-size:1.4rem;font-weight:900;padding:8px 20px;border-radius:8px;flex-shrink:0" data-i18n="kait2-badge">Excellent</div>
	</div>
	<div class="grid g2">
	<div class="card"><div class="ci ci-ind">🏆</div><div class="tag t-ind">Global Record</div><h3>GPQA Diamond</h3><p data-i18n="bench1-p">Darwin-398B-JGOS 90.9%. Darwin-28B-Opus 88.89% #1. 5 Darwin models in Top 21. HuggingFace certified.</p></div>
	<div class="card"><div class="ci ci-em">🇰🇷</div><div class="tag t-em">MSIT·NIA Certified</div><h3>K-AI Leaderboard</h3><p data-i18n="bench2-p">JGOS-31B-Citizen overall #1 (0.621). 11 Darwin derivatives in the Top 20. Blind evaluation.</p></div>
	<div class="card"><div class="ci ci-cyn">🧠</div><div class="tag t-cyn">World First</div><h3>FINAL Bench — Metacognition</h3><p data-i18n="bench3-p">HF Global Top 5. 100 tasks × 15 domains × 8 types × 3 difficulty. TICOS quantitative measurement.</p></div>
	<div class="card"><div class="ci ci-amb">🌐</div><div class="tag t-amb">Sole Track C Pass</div><h3>WM Bench</h3><p data-i18n="bench4-p">World model benchmark. Sole model to pass Track C. Real-time interactive world simulation.</p></div>
	</div>

	<!-- Polaris 글로벌 신약발굴 벤치마크 14관왕 (세부) -->
	<div style="background:linear-gradient(135deg,#EEF2FF,#F0FDFF);border:2px solid var(--ind);border-radius:var(--r);padding:20px 24px;margin-top:22px">
	<div style="display:flex;align-items:center;gap:14px;flex-wrap:wrap;margin-bottom:12px">
	<div style="font-size:2rem">💊</div>
	<div style="flex:1;min-width:200px">
	<div style="font-size:.72rem;font-weight:700;color:var(--ind);letter-spacing:.3px" data-i18n="pol-kicker">Polaris Hub · Global Drug-Discovery ML Benchmark</div>
	<div style="font-size:1.05rem;font-weight:800;color:var(--text)" data-i18n="pol-h">14 First-Place Finishes — ADMET · Potency · Kinase</div>
	</div>
	<div style="background:var(--ind);color:#fff;font-size:1.3rem;font-weight:900;padding:8px 18px;border-radius:8px">14× #1</div>
	</div>
	<p style="font-size:.85rem;color:var(--muted);margin-bottom:14px" data-i18n="pol-desc">Structure-only prediction — no cell-imaging or external experimental data — topped 14 public Polaris leaderboards across absorption, distribution, metabolism, excretion, toxicity, potency and kinase selectivity.</p>
	<div id="pol-list"></div>
	<script>
	(function(){
	var CAT=[
	{k:'potency', ko:'💊 약효 예측', en:'💊 Potency'},
	{k:'solub', ko:'💧 용해도', en:'💧 Solubility'},
	{k:'tox', ko:'☠️ 독성 예측', en:'☠️ Toxicity'},
	{k:'kinase', ko:'🎯 항암 키나아제 표적', en:'🎯 Anticancer Kinase'},
	{k:'adme', ko:'🧬 약물성·ADME', en:'🧬 Drug-likeness · ADME'}
	];
	var D=[
	{c:'potency', id:'moleculeace-chembl236-ki', ko:'약이 표적에 얼마나 강하게 듣는가', en:'Binding potency vs. target', u:'https://polarishub.io/benchmarks/molecularml/moleculeace-chembl236-ki'},
	{c:'potency', id:'moleculeace-chembl234-ki', ko:'도파민 D3 수용체 결합 약효', en:'Dopamine D3 receptor binding', u:'https://polarishub.io/benchmarks/molecularml/moleculeace-chembl234-ki'},
	{c:'solub', id:'solubility-aqsoldb', ko:'약이 물에 얼마나 잘 녹는가', en:'Aqueous solubility', u:'https://polarishub.io/benchmarks/tdcommons/solubility-aqsoldb'},
	{c:'tox', id:'dili', ko:'약물 유발 간손상 예측', en:'Drug-induced liver injury', u:'https://polarishub.io/benchmarks/tdcommons/dili'},
	{c:'tox', id:'ames', ko:'DNA 변이·발암 가능성 예측', en:'Mutagenicity / carcinogenic risk', u:'https://polarishub.io/benchmarks/tdcommons/ames'},
	{c:'kinase', id:'pkis1-egfr-wt-mut-r-1', ko:'EGFR + L858R 변이 저해 예측', en:'EGFR + L858R mutant inhibition', u:'https://polarishub.io/benchmarks/polaris/pkis1-egfr-wt-mut-r-1'},
	{c:'kinase', id:'pkis2-egfr-wt-reg-v2', ko:'EGFR 저해 예측', en:'EGFR inhibition (regression)', u:'https://polarishub.io/benchmarks/polaris/pkis2-egfr-wt-reg-v2'},
	{c:'kinase', id:'pkis2-egfr-wt-r-1', ko:'EGFR 신규 탈환 리더보드', en:'EGFR (reclaimed)', u:'https://polarishub.io/benchmarks/polaris/pkis2-egfr-wt-r-1'},
	{c:'kinase', id:'pkis1-egfr-wt-mut-c-1', ko:'EGFR 변이 분류 예측', en:'EGFR mutant classification', u:'https://polarishub.io/benchmarks/polaris/pkis1-egfr-wt-mut-c-1'},
	{c:'kinase', id:'pkis2-lok-slk-r-1', ko:'LOK·SLK 키나아제 저해 예측', en:'LOK/SLK kinase inhibition', u:'https://polarishub.io/benchmarks/polaris/pkis2-lok-slk-r-1'},
	{c:'kinase', id:'pkis1-kit-wt-mut-r-1', ko:'KIT 변이 저해 예측', en:'KIT mutant inhibition', u:'https://polarishub.io/benchmarks/polaris/pkis1-kit-wt-mut-r-1'},
	{c:'adme', id:'bioavailability-ma', ko:'먹는 약이 혈류에 도달하는 정도', en:'Oral bioavailability', u:'https://polarishub.io/benchmarks/tdcommons/bioavailability-ma'},
	{c:'adme', id:'vdss-lombardo', ko:'약물이 체내 조직에 퍼지는 정도', en:'Volume of distribution', u:'https://polarishub.io/benchmarks/tdcommons/vdss-lombardo'},
	{c:'adme', id:'cyp2d6-substrate-carbonmangels', ko:'CYP2D6 대사·약물상호작용 예측', en:'CYP2D6 metabolism / DDI', u:'https://polarishub.io/benchmarks/tdcommons/cyp2d6-substrate-carbonmangels'}
	];
	function draw(){
	var ko=(localStorage.getItem('vd-lang')\|\|'ko')==='ko', h='';
	CAT.forEach(function(cat){
	var rows=D.filter(function(x){return x.c===cat.k;});
	h+='<div style="margin-top:14px"><div style="font-size:.83rem;font-weight:800;color:var(--ind);margin-bottom:5px">'+(ko?cat.ko:cat.en)+' <span style="color:var(--light);font-weight:600">('+rows.length+')</span></div>';
	rows.forEach(function(r){
	h+='<a href="'+r.u+'" target="_blank" rel="noopener" style="display:flex;gap:10px;align-items:baseline;padding:7px 8px;border-radius:8px;text-decoration:none;color:inherit;border-top:1px solid var(--border)" onmouseover="this.style.background=\'var(--ind-xxl)\'" onmouseout="this.style.background=\'transparent\'">'
	+'<span style="flex:0 0 auto;font-family:monospace;font-size:.71rem;color:var(--ind);font-weight:700;word-break:break-all">'+r.id+'</span>'
	+'<span style="flex:1;min-width:0;font-size:.78rem;color:var(--muted)">'+(ko?r.ko:r.en)+'</span>'
	+'<span style="flex:0 0 auto;font-size:.74rem;color:var(--ind);font-weight:700">→</span></a>';
	});
	h+='</div>';
	});
	var el=document.getElementById('pol-list'); if(el) el.innerHTML=h;
	}
	document.addEventListener('DOMContentLoaded', function(){
	draw();
	var _sl=window.setLang;
	if(_sl && !_sl._polWrapped){ window.setLang=function(l){_sl(l);draw();}; window.setLang._polWrapped=true; }
	});
	})();
	</script>
	<p style="font-size:.72rem;color:var(--light);margin-top:14px" data-i18n="pol-note">All results are computational predictions on public blind-submission leaderboards, submitted under the VIDraft account. VIDraft has since filed its first drug-substance patent from this autonomous discovery system.</p>
	</div>
	</div>
	</div>
	<div class="stab-content" id="proof-papers">
	<div class="section">
	<div class="grid g2">
	<div class="card"><div class="tag t-cyn">arXiv 2605.14386</div><h3>Darwin Family</h3><p data-i18n="paper1-p">MRI-Trust-Weighted Evolutionary Merging for Training-Free Scaling. 45 days after release: 300K+ downloads, 500 derivatives.</p><br><a href="https://arxiv.org/abs/2605.14386" target="_blank" style="color:var(--ind);font-size:.82rem;font-weight:600" data-i18n="paper-link">View Paper →</a></div>
	<div class="card"><div class="tag t-em">HF Global #5</div><h3>FINAL Bench</h3><p data-i18n="paper2-p">Measuring Functional Metacognitive Reasoning in LLMs. MetaCog scaffold +14.05 pts. 94.8% Error Recovery. Under conference review.</p></div>
	<div class="card"><div class="tag t-amb">WM Bench</div><h3>PROMETHEUS</h3><p data-i18n="paper3-p">The sole WM-passing world model v1.0. 263-joint skeleton. Track C 726 pts Grade B 47 FPS.</p></div>
	<div class="card"><div class="tag t-ros">Hallucination Control</div><h3>MARL Runtime</h3><p data-i18n="paper4-p">Model-Agnostic Runtime Middleware for LLMs. Reduces GPT/Claude/Gemini hallucination by 70%+. One line of code.</p></div>
	</div>
	</div>
	</div>
	<div class="stab-content" id="proof-patents">
	<div class="section">
	<p class="ss" data-i18n="pat-sub">KR priority filing + PCT · 186 claims total</p>
	<h3 style="margin-bottom:16px;color:var(--ind);font-size:1rem" data-i18n="pat-darwin-h">🧬 Darwin Evolutionary · 3 patents</h3>
	<div class="patent-grid" style="margin-bottom:32px">
	<div class="pat"><div class="pat-n">D1</div><div><h4 data-i18n="pat-d1-h">MRI-Based Adaptive Reliability Meta-learning</h4><p data-i18n="pat-d1-p">Neural-network parameter merging based on Model-layer Response Importance (MRI)</p></div></div>
	<div class="pat"><div class="pat-n">D2</div><div><h4 data-i18n="pat-d2-h">Compatibility-Assessed Heterogeneous Crossbreeding</h4><p>Compatibility-Based Crossbreeding for Heterogeneous Neural Networks</p></div></div>
	<div class="pat"><div class="pat-n">D3</div><div><h4 data-i18n="pat-d3-h">Recursive Generational Inheritance Evolution</h4><p>Recursive Generational Inheritance in Evolutionary Neural Network Merging</p></div></div>
	</div>
	<h3 style="margin-bottom:16px;color:var(--pur);font-size:1rem" data-i18n="pat-aether-h">⚡ AETHER Architecture · 8 patents · 186 claims</h3>
	<div class="patent-grid">
	<div class="pat"><div class="pat-n" style="background:var(--pur)">P1</div><div><h4 data-i18n="pat-a1-h">Latin-Square Hybrid Multi-Type Attention</h4><p data-i18n="pat-a1-p">5/7/11-way heterogeneous attention Latin Square integration</p></div></div>
	<div class="pat"><div class="pat-n" style="background:var(--pur)">P2</div><div><h4 data-i18n="pat-a2-h">Automatic Causal Safety Verification</h4><p>Causal Safety Verification for Multi-Type Attention</p></div></div>
	<div class="pat"><div class="pat-n" style="background:var(--pur)">P6</div><div><h4 data-i18n="pat-a3-h">Metacognition Signal Head</h4><p data-i18n="pat-a3-p">Self-error detection signal head</p></div></div>
	<div class="pat"><div class="pat-n" style="background:var(--pur)">P8</div><div><h4 data-i18n="pat-a4-h">Perpetual Closed-Loop Learning</h4><p>Single Sigmoid Gate Convex Combination Fusion</p></div></div>
	<div class="pat"><div class="pat-n" style="background:var(--pur)">P0</div><div><h4 data-i18n="pat-a5-h">Multi-Agent Swarm Coordination</h4><p>Prime-Order Cyclic Group Weight Transfer</p></div></div>
	<div class="pat"><div class="pat-n" style="background:var(--pur)">P3</div><div><h4 data-i18n="pat-a6-h">Triple-Symmetric MoE Routing</h4><p>Per-Attention-Type Gradient Clipping</p></div></div>
	<div class="pat"><div class="pat-n" style="background:var(--pur)">P4</div><div><h4 data-i18n="pat-a7-h">Adaptive Noise-Cancelling Attention</h4><p>Prime-Based Mixture-of-Experts Routing</p></div></div>
	<div class="pat"><div class="pat-n" style="background:var(--pur)">P7</div><div><h4 data-i18n="pat-a8-h">Hallucination-Suppression Gate</h4><p>Causal Safety CI/CD for Neural Network Models</p></div></div>
	</div>
	</div>
	</div>
	<div class="stab-content" id="proof-press">
	<div class="section">
	<h2 class="st" data-i18n="proof-allpress-h">All <span>Press Coverage</span></h2>
	<p class="ss"><span data-i18n="proof-allpress-s">Full media archive including founder essays — auto-updated.</span> <span class="sec-cnt" id="cnt-press-proof"></span></p>
	<div class="press-wrap"><div class="press-scroll" id="press-list-proof"></div></div>
	</div>
	</div>
	</div>
	</div>

	<!-- ═══════════ ABOUT (회사) ═══════════ -->
	<div class="page" id="page-about">
	<div class="ph" style="background:linear-gradient(135deg,#064E3B 0%,#065F46 45%,#1E3A5F 100%)">
	<div class="container">
	<div class="badge" style="background:#059669">🌱 COMPANY</div>
	<h1 style="color:#fff" data-i18n="ab-h1">Intelligence is not made — it is grown.</h1>
	<p style="color:#D1FAE5" data-i18n="ab-sub">A small Korean Proto-AGI startup (since 2024) with one belief: don't exaggerate — speak only what is verified.</p>
	</div>
	</div>
	<div class="container">
	<div class="section">
	<h2 class="st" data-i18n="ab-phil-h">Our <span>Philosophy</span></h2>
	<p class="ss" data-i18n="ab-phil-s">Great life was never designed all at once. Seed → sprout → tree → forest. AGI is grown by nature's law, not built by force.</p>
	<div class="grid g2">
	<div class="card"><div class="ci ci-em">🌱</div><div class="tag t-em" data-i18n="ab-p1-tag">Grow, not make</div><h3 data-i18n="ab-p1-h">기르다 · Cultivate</h3><p data-i18n="ab-p1-p">We do not build intelligence in one giant step; we grow it across generations, the way nature evolves great life. 씨앗 → 새싹 → 나무 → 숲.</p></div>
	<div class="card"><div class="ci ci-ind">🔍</div><div class="tag t-ind" data-i18n="ab-p2-tag">Honesty & verification</div><h3 data-i18n="ab-p2-h">정직과 검증</h3><p data-i18n="ab-p2-p">Our founding spirit: do not exaggerate; speak only what has been verified. Real trust comes from honestly stating what we have NOT done.</p></div>
	<div class="card"><div class="ci ci-cyn">🧬</div><div class="tag t-cyn">DARWIN</div><h3 data-i18n="ab-p3-h">Grow by evolution</h3><p data-i18n="ab-p3-p">Crossbreed the strengths of different models to raise a stronger next generation — inheriting a lineage of intelligence, like a craft passed down through generations.</p></div>
	<div class="card"><div class="ci ci-amb">☯️</div><div class="tag t-amb">AETHER</div><h3 data-i18n="ab-p4-h">Harmony of diversity (조화)</h3><p data-i18n="ab-p4-p">Not one method — 5·7·11 kinds of attention coexist. When diversity harmonizes, higher intelligence awakens. This is how we look beyond the Transformer.</p></div>
	<div class="card"><div class="ci ci-ind">⚛️</div><div class="tag t-ind">QuantumOS</div><h3 data-i18n="ab-p5-h">Soil for the next era (길)</h3><p data-i18n="ab-p5-p">We do not claim to have 'completed' the quantum computer. We till the soil for the next era, verifying step by step on real hardware. AGI is a road, not a destination.</p></div>
	<div class="card"><div class="ci ci-em">🌏</div><div class="tag t-em" data-i18n="ab-p6-tag">Tech for people</div><h3 data-i18n="ab-p6-h">Philosophy on the ground</h3><p data-i18n="ab-p6-p">Technology for people and society — the same dream as Society 5.0. From Jeonnam·Gwangju (3.2M citizens) to across borders.</p></div>
	</div>
	</div>
	<div class="section">
	<h2 class="st" data-i18n="ab-hist-h">Major <span>Milestones</span></h2>
	<div id="about-timeline"></div>
	<script>
	(function(){
	var TL=[
	{y:'2024', ko:'지니젠(GiniGEN) — 온디바이스 적응형 AI · GENIE 3D, 세계가 주목', en:'GiniGEN — on-device adaptive AI · GENIE 3D, noticed worldwide'},
	{y:'2025.10', ko:'NIPA AI컴퓨팅 자원 지원 사업 선정', en:'Selected for the NIPA AI Computing Resource Support program'},
	{y:'2026.02', ko:'메타인지 벤치마크 FINAL Bench 공개', en:'FINAL Bench metacognition benchmark released'},
	{y:'2026.03', ko:'추론 미들웨어 MARL 전세계 공개 · LLM MRI · 웨어큐브 MOU', en:'MARL reasoning middleware · LLM MRI · WareCube MOU'},
	{y:'2026.04', ko:'정부 첨단 GPU 지원 사업 선정 — "블랙웰(Blackwell) GPU 지원"', en:'Selected for the government advanced-GPU program — "Blackwell GPU support"', hi:1},
	{y:'2026.04', ko:'로컬 AI 한수(韓守) · PROMETHEUS 월드모델 · HF 톱21 중 韓 5개 전부 Darwin', en:'HanSoo local AI · PROMETHEUS world model · 5 of HF Top-21 all Darwin'},
	{y:'2026.05', ko:'Darwin Family 프레임워크 공개 · 中 텐센트, Darwin 집중 분석 (arXiv 2605.14386)', en:'Darwin Family framework · China Tencent analyzes Darwin in depth (arXiv 2605.14386)'},
	{y:'2026.06', ko:'K-AI 리더보드 종합 1위 · GPQA Diamond 90.9% · KAIT 우수 판정', en:'K-AI Leaderboard #1 · GPQA Diamond 90.9% · KAIT "Excellent"'},
	{y:'2026.06', ko:'홋카이도 STEP(Sapporo Transnational Expansion Partnership) 초청 방문 — 삿포로 시청·홋카이도 도청', en:'Invited by Hokkaido STEP (Sapporo Transnational Expansion Partnership) — Sapporo City Hall & Hokkaido Government', hi:1},
	{y:'2026.07', ko:'양자 실HW N=10 · 메타인지 어댑터 공개 · 첫 신약물질 특허 출원', en:'Quantum real-HW N=10 · metacognition adapters · first drug-substance patent filed'}
	];
	function draw(){
	var ko=(localStorage.getItem('vd-lang')\|\|'ko')==='ko';
	var h=TL.map(function(t){
	var acc=t.hi?'var(--em)':'var(--border)';
	return '<div style="display:flex;gap:16px;align-items:flex-start;padding:10px 0;border-left:2px solid '+acc+';padding-left:18px;margin-left:8px;position:relative">'
	+'<span style="position:absolute;left:-7px;top:14px;width:12px;height:12px;border-radius:50%;background:'+(t.hi?'var(--em)':'var(--ind)')+'"></span>'
	+'<span style="flex:0 0 74px;font-weight:800;color:'+(t.hi?'var(--em)':'var(--ind)')+';font-size:.86rem">'+t.y+'</span>'
	+'<span style="flex:1;font-size:.9rem;color:var(--text);font-weight:'+(t.hi?'700':'500')+'">'+(ko?t.ko:t.en)+(t.hi?' ⭐':'')+'</span></div>';
	}).join('');
	var el=document.getElementById('about-timeline'); if(el) el.innerHTML=h;
	}
	document.addEventListener('DOMContentLoaded', function(){
	draw();
	var _sl=window.setLang;
	if(_sl && !_sl._tlWrapped){ window.setLang=function(l){_sl(l);draw();}; window.setLang._tlWrapped=true; }
	});
	})();
	</script>
	</div>
	<div class="section">
	<h2 class="st" data-i18n="ab-team-h">The <span>Crew</span></h2>
	<p class="ss" data-i18n="ab-team-s">Eleven people, armed with freedom, flexibility, speed and creativity — like romantic pirates.</p>
	<div class="hl">
	<h3 data-i18n="ab-team-q">🏴‍☠️ "Join My Crew?" — we call ourselves 조마크.</h3>
	<p data-i18n="ab-team-qs">Ask any VIDraft member their identity and we answer 'Jo-mark' — the crew's callsign, drawn from the manga One Piece. Not resources but wits; not volume but grit and agility.</p>
	</div>
	<div class="team-grid">
	<div class="team-card">
	<img src="team/01_chair.webp" alt="Chairman" width="140" height="140" loading="lazy">
	<div class="team-role" data-i18n="tc-1-role">의장</div>
	<div class="team-name">김 베가펑크</div>
	<p class="team-quote" data-i18n="tc-1-q">우리가 지금 만드는 것들이 인류의 미래가 될 것이다.</p>
	</div>
	<div class="team-card">
	<img src="team/02_ceo.webp" alt="CEO" width="140" height="140" loading="lazy">
	<div class="team-role" data-i18n="tc-2-role">CEO</div>
	<div class="team-name">김 루피</div>
	<p class="team-quote" data-i18n="tc-2-q">낙천이 전략이고, 확신이 자산이다.</p>
	</div>
	<div class="team-card">
	<img src="team/03_coo.webp" alt="COO" width="140" height="140" loading="lazy">
	<div class="team-role" data-i18n="tc-3-role">COO</div>
	<div class="team-name">김 징베</div>
	<p class="team-quote" data-i18n="tc-3-q">회장이 소리쳐도, 이 배의 항로는 흔들리지 않는다.</p>
	</div>
	<div class="team-card">
	<img src="team/04_cfo.webp" alt="CFO" width="140" height="140" loading="lazy">
	<div class="team-role" data-i18n="tc-4-role">CFO</div>
	<div class="team-name">정 로우</div>
	<p class="team-quote" data-i18n="tc-4-q">숫자는 냉정하게, 팀은 진심으로.</p>
	</div>
	<div class="team-card">
	<img src="team/05_cio.webp" alt="CIO" width="140" height="140" loading="lazy">
	<div class="team-role" data-i18n="tc-5-role">CIO</div>
	<div class="team-name">한 라일리</div>
	<p class="team-quote" data-i18n="tc-5-q">이 바닥의 모든 항로를 지도 없이 안다.</p>
	</div>
	<div class="team-card">
	<img src="team/06_lab.webp" alt="Head of R&D" width="140" height="140" loading="lazy">
	<div class="team-role" data-i18n="tc-6-role">연구소장 · HEAD OF R&D</div>
	<div class="team-name">홍 크로커스</div>
	<p class="team-quote" data-i18n="tc-6-q">말없이 자리를 지키고, 결과로 답한다.</p>
	</div>
	<div class="team-card">
	<img src="team/07_cto.webp" alt="CTO" width="140" height="140" loading="lazy">
	<div class="team-role" data-i18n="tc-7-role">CTO</div>
	<div class="team-name">장 조로</div>
	<p class="team-quote" data-i18n="tc-7-q">CEO가 자면 자고, CEO가 코딩하면 코딩한다.</p>
	</div>
	<div class="team-card">
	<img src="team/10_cmo.webp" alt="CMO" width="140" height="140" loading="lazy">
	<div class="team-role" data-i18n="tc-10-role">CMO</div>
	<div class="team-name">이 이바코프</div>
	<p class="team-quote" data-i18n="tc-10-q">명함 한 장에 왕국이 딸려온다.</p>
	</div>
	<div class="team-card">
	<img src="team/11_japan.webp" alt="Japan Head" width="140" height="140" loading="lazy">
	<div class="team-role" data-i18n="tc-11-role">일본 사업 본부장 · JAPAN HEAD</div>
	<div class="team-name">조 오뎅</div>
	<p class="team-quote" data-i18n="tc-11-q">일본과 세계를 잇는 유일한 사무라이.</p>
	</div>
	<div class="team-card">
	<img src="team/08_intern_f.webp" alt="Intern" width="140" height="140" loading="lazy">
	<div class="team-role" data-i18n="tc-8-role">인턴 · INTERN</div>
	<div class="team-name">김 비비</div>
	<p class="team-quote" data-i18n="tc-8-q">정식 크루가 되는 그날까지, 배우겠습니다.</p>
	</div>
	<div class="team-card">
	<img src="team/09_intern_m.webp" alt="Intern" width="140" height="140" loading="lazy">
	<div class="team-role" data-i18n="tc-9-role">인턴 · INTERN</div>
	<div class="team-name">신 쵸파</div>
	<p class="team-quote" data-i18n="tc-9-q">칭찬하지 마세요! (매우 기뻐하는 중)</p>
	</div>
	</div>
	<div class="grid g3" style="margin-top:18px">
	<div class="card"><div class="ci ci-ind">👥</div><h3 data-i18n="ab-t1-h">A crew of 11</h3><p data-i18n="ab-t1-p">A tight team that beats volume with method — 24 GPUs against the giants.</p></div>
	<div class="card"><div class="ci ci-em">🧭</div><h3 data-i18n="ab-t2-h">Vertically integrated</h3><p data-i18n="ab-t2-p">Own LLMs · City OS · drug/material AI · on-prem AI — CEO, Vice President and Japan Business Head lead a Proto-AGI stack.</p></div>
	<a class="card" href="mailto:arxivgpt@gmail.com?subject=VIDRAFT%20Join%20My%20Crew" style="text-decoration:none;color:inherit"><div class="ci ci-cyn">🚀</div><h3 data-i18n="ab-t3-h">Join My Crew</h3><p data-i18n="ab-t3-p">Looking for the next global AI pirate — freedom, speed, creativity. Contact us.</p><div class="sc-link">arxivgpt@gmail.com</div></a>
	</div>
	</div>
	</div>
	</div>

	<!-- ═══════════ SOLUTIONS (AX) ═══════════ -->
	<div class="page" id="page-solutions">
	<div class="ph" style="background:linear-gradient(135deg,#1E1B4B 0%,#312E81 55%,#0F766E 100%)">
	<div class="container">
	<div class="badge" style="background:#4338CA">🏛️ SOLUTIONS · AX</div>
	<h1 style="color:#fff" data-i18n="sol-h1">Sovereign AI OS — your data never leaves the network</h1>
	<p style="color:#C7D2FE" data-i18n="sol-sub">Not one chatbot, but an AI operating system that connects administration, citizen and industry data safely inside a local / independent network.</p>
	<div class="btns" style="margin-top:18px">
	<a class="btn btn-p" href="mailto:arxivgpt@gmail.com?subject=VIDRAFT%20AX%20Pilot%20Inquiry" data-i18n="sol-btn1">Contact for a Pilot →</a>
	</div>
	</div>
	</div>
	<div class="container">
	<div class="section">
	<h2 class="st" data-i18n="sol-gov-h">Public · Local-Government <span>AX</span></h2>
	<p class="ss" data-i18n="sol-gov-s">Administration overload · fragmented data · cloud-AI security concerns → a local sovereign AI operating system.</p>
	<div class="grid g3">
	<div class="card"><div class="ci ci-ind">🧠</div><div class="tag t-ind">Darwin LLM</div><h3 data-i18n="sol-c1-h">Region-tuned LLM</h3><p data-i18n="sol-c1-p">Language · administration · industry models tuned for each region.</p></div>
	<div class="card"><div class="ci ci-cyn">🛡️</div><div class="tag t-cyn">AETHER Trust</div><h3 data-i18n="sol-c2-h">Grounded & self-verifying</h3><p data-i18n="sol-c2-p">Hallucination suppression · self-verification · evidence-backed answers.</p></div>
	<div class="card"><div class="ci ci-em">🗺️</div><div class="tag t-em">NationalOS</div><h3 data-i18n="sol-c3-h">Policy simulation</h3><p data-i18n="sol-c3-p">Policy · budget · industry simulation on regional digital twins.</p></div>
	<div class="card"><div class="ci ci-amb">🚪</div><div class="tag t-amb">CHITOS Portal</div><h3 data-i18n="sol-c4-h">One common AI touchpoint</h3><p data-i18n="sol-c4-p">A shared AI access point for citizens, officials and enterprises.</p></div>
	<div class="card"><div class="ci ci-ind">🔬</div><div class="tag t-ind">Domain OS</div><h3 data-i18n="sol-c5-h">Pharma · Material · Nutri · Legal</h3><p data-i18n="sol-c5-p">Vertical-domain AI plugged into the regional OS.</p></div>
	<div class="card"><div class="ci ci-cyn">🔒</div><div class="tag t-cyn">On-prem · Sovereign</div><h3 data-i18n="sol-c6-h">Data stays inside</h3><p data-i18n="sol-c6-p">On-premise / independent-network deployment, verified by a 3-month KPI pilot.</p></div>
	<div class="card"><div class="ci ci-em">🏗️</div><div class="tag t-em">Building</div><h3 data-i18n="sol-c7-h">Building — Architectural Design AI</h3><p data-i18n="sol-c7-p">From natural language to KS-standard floor plans (DXF·BIM·BOQ·fire-safety), and from a parcel address to code-compliant 3D building massing.</p></div>
	</div>
	<div style="margin-top:22px;background:var(--ind-xxl);border-radius:var(--r);padding:18px 22px">
	<div style="font-weight:800;margin-bottom:10px" data-i18n="sol-pkg-h">5 AX Packages</div>
	<div class="grid g3">
	<div class="card" style="padding:12px 14px"><div class="tag t-ind">01</div><h4 style="margin-top:5px" data-i18n="sol-p1">Administration</h4></div>
	<div class="card" style="padding:12px 14px"><div class="tag t-em">02</div><h4 style="margin-top:5px" data-i18n="sol-p2">Citizen</h4></div>
	<div class="card" style="padding:12px 14px"><div class="tag t-cyn">03</div><h4 style="margin-top:5px" data-i18n="sol-p3">Industry</h4></div>
	<div class="card" style="padding:12px 14px"><div class="tag t-amb">04</div><h4 style="margin-top:5px" data-i18n="sol-p4">Bio</h4></div>
	<div class="card" style="padding:12px 14px"><div class="tag t-ind">05</div><h4 style="margin-top:5px" data-i18n="sol-p5">Materials</h4></div>
	</div>
	</div>
	</div>
	<div class="section">
	<h2 class="st" data-i18n="sol-case-h">Live Deployments — <span>Seoul AI & Robot Science Museum</span></h2>
	<p class="ss" data-i18n="sol-case-s">Three exhibits built by VIDraft, running for the public.</p>
	<div class="grid g3">
	<div class="card"><div class="ci ci-em">🤖</div><div class="tag t-em" data-i18n="sol-r1-tag">Physical AI</div><h3 data-i18n="sol-r1-h">Talk to Spot</h3><p data-i18n="sol-r1-p">Boston Dynamics 'Spot' controlled by natural-language voice — converse with, command and steer the robot through an LLM.</p></div>
	<div class="card"><div class="ci ci-ind">🩻</div><div class="tag t-ind" data-i18n="sol-r2-tag">Interpretability</div><h3 data-i18n="sol-r2-h">Model X-RAY</h3><p data-i18n="sol-r2-p">See inside the LLM black box — an X-RAY view that makes a model's internal workings transparent to visitors.</p></div>
	<a class="card" href="https://vidraft-darwin-factory.hf.space" target="_blank" rel="noopener" style="text-decoration:none;color:inherit"><div class="ci ci-cyn">🧬</div><div class="tag t-cyn" data-i18n="sol-r3-tag">Evolution</div><h3 data-i18n="sol-r3-h">Darwin Crossbreed & Evolve</h3><p data-i18n="sol-r3-p">Watch AI models crossbreed and evolve — the child surpasses both parents. An interactive Darwin evolution experience.</p><div class="sc-link">vidraft-darwin-factory.hf.space</div></a>
	</div>
	</div>
	</div>
	</div>

	<!-- ═══════════ VKAE ═══════════ -->
	<div class="page" id="page-vkae">
	<div class="ph" style="background:linear-gradient(135deg,#052E16 0%,#064E3B 55%,#065F46 100%)">
	<div class="container">
	<div class="badge" style="background:#059669">⚡ VKAE · Inference Acceleration Engine</div>
	<h1 style="color:#fff" data-i18n="v-h1">Make one more GPU — without making a GPU</h1>
	<p style="color:#D1FAE5" data-i18n="v-sub">VKAE (VIDRAFT Kernel Acceleration Engine) squeezes multiples more throughput out of the GPU you already own — kernel-level, with answer quality unchanged.</p>
	<div class="btns" style="margin-top:18px">
	<a class="btn btn-p" href="https://huggingface.co/spaces/VIDraft/vkae" target="_blank" rel="noopener noreferrer" data-i18n="v-btn1">Leaderboard & Demo →</a>
	<a class="btn btn-o" href="https://hub.docker.com/r/vidraft/qwen35-vkae" target="_blank" rel="noopener noreferrer" style="background:transparent;color:#fff;border-color:#fff" data-i18n="v-btn2">Docker →</a>
	</div>
	</div>
	</div>
	<div class="container">
	<div class="section">
	<div class="stats">
	<div class="si"><div class="sn">23.4×</div><div class="sl" data-i18n="v-k1">throughput vs. standard (NVIDIA B200)</div></div>
	<div class="si"><div class="sn">10K+</div><div class="sl" data-i18n="v-k2">tokens/sec under concurrent load</div></div>
	<div class="si"><div class="sn">0</div><div class="sl" data-i18n="v-k3">quality loss — same answers, faster</div></div>
	<div class="si"><div class="sn">100%</div><div class="sl" data-i18n="v-k4">reproducible — one Docker, your GPU</div></div>
	</div>
	</div>
	<div class="section">
	<h2 class="st" data-i18n="v-why-h">Why inference acceleration is <span>essential</span></h2>
	<p class="ss" data-i18n="v-why-s">The real AI-infra battleground is not building the model — it is running it, cheaply, forever.</p>
	<div class="grid g3">
	<div class="card"><div class="ci ci-em">💰</div><div class="tag t-em" data-i18n="v-w1-t">Efficiency = capacity</div><h3 data-i18n="v-w1-h">A virtual extra GPU</h3><p data-i18n="v-w1-p">GPUs are scarce, expensive and power-hungry. Doubling throughput on the same card is like building twice the infrastructure — no new chips, no new power.</p></div>
	<div class="card"><div class="ci ci-ind">📉</div><div class="tag t-ind" data-i18n="v-w2-t">Cost per token</div><h3 data-i18n="v-w2-h">Where AI services win or lose</h3><p data-i18n="v-w2-p">Training happens once; inference happens every time a user asks. VKAE lowers the per-token cost that decides whether an AI service is profitable.</p></div>
	<div class="card"><div class="ci ci-cyn">🌐</div><div class="tag t-cyn" data-i18n="v-w3-t">Sovereign-AI ready</div><h3 data-i18n="v-w3-h">Not a nice-to-have</h3><p data-i18n="v-w3-p">For clouds, AI startups, enterprises and national/sovereign AI, acceleration is not optional — without it, running AI at scale runs at a loss.</p></div>
	</div>
	</div>
	<div class="section">
	<div class="hl">
	<h3 data-i18n="v-repro-h">🔬 Reproducible, not just a claim</h3>
	<p data-i18n="v-repro-p">Speed claims are cheap. VKAE ships the model weights plus the optimized serving stack as one Docker container, OpenAI-compatible — so anyone can reproduce the numbers on their own GPU and plug it straight into an existing service.</p>
	</div>
	<div class="grid g2" style="margin-top:18px">
	<a class="sc" href="https://huggingface.co/FINAL-Bench/Qwen3.5-35B-A3B-VKAE" target="_blank" rel="noopener"><div class="sc-icon">🤗</div><div class="tag t-ind">Model</div><h3>Qwen3.5-35B-A3B-VKAE</h3><p data-i18n="v-l1">VKAE-accelerated model weights on Hugging Face.</p><div class="sc-link">huggingface.co/FINAL-Bench/Qwen3.5-35B-A3B-VKAE</div></a>
	<a class="sc" href="https://hub.docker.com/r/vidraft/qwen35-vkae" target="_blank" rel="noopener"><div class="sc-icon">🐳</div><div class="tag t-cyn">Docker</div><h3>vidraft/qwen35-vkae</h3><p data-i18n="v-l2">Integrated container — weights + optimized serving, OpenAI-compatible.</p><div class="sc-link">hub.docker.com/r/vidraft/qwen35-vkae</div></a>
	</div>
	</div>
	</div>
	</div>

	<!-- ═══════════ CHITOS ═══════════ -->
	<div class="page" id="page-chitos">
	<div class="ph" style="background:linear-gradient(135deg,#0B1220 0%,#1E293B 55%,#0F766E 100%)">
	<div class="container">
	<div class="badge" style="background:#0D9488">🛡️ CHITOS · Autonomous Security AI</div>
	<h1 style="color:#fff" data-i18n="ch-h1">From suspicion to proof</h1>
	<p style="color:#CBD5E1" data-i18n="ch-sub">Most scanners flag a pattern and say "maybe a vuln — you check." Chitos verifies inside authorized targets, confirms reproducibility, and chains attack paths into one scenario.</p>
	<div class="btns" style="margin-top:18px">
	<a class="btn btn-p" href="https://chitos.vidraft.net" target="_blank" rel="noopener noreferrer" data-i18n="ch-btn1">Try Free →</a>
	</div>
	</div>
	</div>
	<div class="container">
	<div class="section">
	<h2 class="st" data-i18n="ch-flow-h">Three <span>Stages</span></h2>
	<p class="ss" data-i18n="ch-flow-s">Successor to VIDRAFT Mythos. Where Mythos was static analysis, Chitos verifies.</p>
	<div class="grid g3">
	<div class="card"><div class="ci ci-ind">🔍</div><div class="tag t-ind" data-i18n="ch-s1-t">Stage 1 · Static Scan (free)</div><h3 data-i18n="ch-s1-h">Multi-language pattern analysis</h3><p data-i18n="ch-s1-p">Python, JS, Go, Java, C/C++, Rust, PHP, YAML — injection sinks, deserialization, credential exposure, crypto misuse, prototype pollution, supply-chain risk. Unproven warnings are filtered out as noise.</p></div>
	<div class="card"><div class="ci ci-cyn">🧠</div><div class="tag t-cyn" data-i18n="ch-s2-t">Stage 2 · Threat Research</div><h3 data-i18n="ch-s2-h">Autonomous context research</h3><p data-i18n="ch-s2-p">Cross-references CVE databases, exploit advisories and public PoCs to explain WHY a finding is dangerous in the current threat landscape. (Requires a Claude API key.)</p></div>
	<div class="card"><div class="ci ci-em">🎯</div><div class="tag t-em" data-i18n="ch-s3-t">Stage 3 · Active Verification (free)</div><h3 data-i18n="ch-s3-h">Reproducible exploit proof</h3><p data-i18n="ch-s3-p">On authorized targets only — XSS, SQLi, path traversal, command injection. Finds reproducible evidence, retries variant paths when blocked, and links confirmed vulnerabilities into a kill-chain threat map.</p></div>
	</div>
	</div>
	<div class="section">
	<h2 class="st" data-i18n="ch-ex-h">Ready-to-run <span>Scenarios</span></h2>
	<p class="ss" data-i18n="ch-ex-s">Five representative attack scenarios, one click each. Live-test against IBM intentionally-vulnerable demo.testfire.net.</p>
	<div class="grid g3">
	<div class="card"><div class="tag t-amb">CVE</div><h4>Log4Shell</h4></div>
	<div class="card"><div class="tag t-ind">Auth</div><h4>JWT alg:none bypass</h4></div>
	<div class="card"><div class="tag t-amb">RCE</div><h4>SSTI → RCE</h4></div>
	<div class="card"><div class="tag t-cyn">JS</div><h4>Prototype Pollution</h4></div>
	<div class="card"><div class="tag t-em">Supply chain</div><h4>Dependency Attack</h4></div>
	</div>
	</div>
	<div class="section">
	<div class="grid g2">
	<div class="card" style="background:var(--ind-xxl)"><div style="font-weight:800;margin-bottom:6px" data-i18n="ch-priv-h">🔒 Privacy by design</div><p style="font-size:.85rem;color:var(--muted)" data-i18n="ch-priv-p">No install. No signup. Your code is never sent to an external API.</p></div>
	<div class="card" style="background:#FEF3C7;border-color:var(--amb)"><div style="font-weight:800;color:#92400E;margin-bottom:6px" data-i18n="ch-legal-h">⚖️ Authorized use only</div><p style="font-size:.85rem;color:#78350F" data-i18n="ch-legal-p">Active exploit features may be used only on targets you own or are explicitly authorized to test. Unauthorized testing or scanning may be illegal; all legal responsibility rests with the user.</p></div>
	</div>
	</div>
	</div>
	</div>

	<!-- ═══════════ QUANTUM ═══════════ -->
	<div class="page" id="page-quantum">
	<div class="ph" style="background:linear-gradient(135deg,#0F172A 0%,#1E1B4B 60%,#312E81 100%)">
	<div class="container">
	<div class="badge" style="background:#7C3AED">⚛️ QUANTUMOS</div>
	<h1 style="color:#fff" data-i18n="q-h1">Cryptanalysis on Real Quantum Hardware</h1>
	<p style="color:#C7D2FE" data-i18n="q-sub">Simon-algorithm attacks executed on IBM's 156-qubit ibm_kingston — at record hardware scale.</p>
	<div class="btns" style="margin-top:18px">
	<a class="btn btn-p" href="https://vidraft-quantumos.hf.space/crypto" target="_blank" rel="noopener noreferrer" data-i18n="q-btn1">Live Demo →</a>
	<a class="btn btn-o" href="https://huggingface.co/spaces/FINAL-Bench/quantum-bench-leaderboard" target="_blank" rel="noopener noreferrer" style="background:transparent;color:#fff;border-color:#fff" data-i18n="q-btn2">Leaderboard →</a>
	</div>
	</div>
	</div>
	<div class="container">
	<div class="section">
	<div style="background:linear-gradient(135deg,#1E1B4B,#312E81);border-radius:var(--r);padding:26px 28px;color:#E0E7FF;box-shadow:var(--sh-lg)">
	<div style="font-size:clamp(1.15rem,2.6vw,1.5rem);font-weight:900;color:#fff;line-height:1.35;margin-bottom:14px" data-i18n="q-story-h">The world stopped at "4". A small Korean team pushed to "10".</div>
	<p style="font-size:.9rem;line-height:1.7;margin-bottom:12px" data-i18n="q-story-p1">Drawing a rocket on paper and actually launching it are two different things. Real quantum computers are noisy — a slightly longer computation drowns the answer. For years the public record on real hardware stayed stuck around N≈4.</p>
	<p style="font-size:.9rem;line-height:1.7" data-i18n="q-story-p2">VIDraft touched that wall. Taking the two most vulnerable structures — Even–Mansour and Feistel — onto IBM's real quantum computer, the team pushed the simplest block-cipher structure to N = 5, 6, 7, 8, 9 and 10, recovering a fresh independent key each time to prove it was not a rigged demo tuned to one answer — using noise mitigation only, no costly error correction.</p>
	</div>
	</div>
	<div class="section">
	<h2 class="st" data-i18n="q-hw-h">Real <span>Hardware</span> Results</h2>
	<p class="ss" data-i18n="q-hw-s">IBM ibm_kingston (156 qubits) · 15–30 qubit circuits with hundreds of two-qubit gates.</p>
	<div class="grid g2">
	<div class="card"><div class="ci ci-ind">🔑</div><div class="tag t-ind">Even–Mansour</div><h3>N = 5 → 10</h3><p data-i18n="q-hw1">Secret-key recovery on real hardware from N=5 up to N=10 — exceeding the previous public record of N≈4 (to our knowledge).</p></div>
	<div class="card"><div class="ci ci-cyn">🔀</div><div class="tag t-cyn">3-round Feistel · DES-family</div><h3>Block 6 · 8</h3><p data-i18n="q-hw2">Hidden-period recovery at block sizes 6 and 8, rank-1 clean.</p></div>
	</div>
	<p style="font-size:.78rem;color:var(--muted);margin-top:12px" data-i18n="q-hw-note">Error mitigation only — dynamical decoupling, gate/measurement twirling, readout-error correction (no quantum error correction). Independent control keys were tested per instance to confirm the attack isn't tuned to one answer.</p>
	</div>
	<div class="section">
	<h2 class="st" data-i18n="q-sim-h">Five <span>Attack Structures</span></h2>
	<p class="ss" data-i18n="q-sim-s">Genuine quantum algorithms covering the major cryptographic design paradigms. The two Simon-based constructions were pushed to hardware.</p>
	<div class="grid g3">
	<div class="card"><div class="tag t-cyn">Linear</div><h4>Bernstein–Vazirani</h4><p data-i18n="q-s1">Key recovery in a single query.</p></div>
	<div class="card"><div class="tag t-ind">Exponential</div><h4>Simon · Even–Mansour</h4><p data-i18n="q-s2">Executed on real hardware ✓</p></div>
	<div class="card"><div class="tag t-em">Block cipher (SPN)</div><h4>Grover</h4><p data-i18n="q-s3">Quadratic-speedup key search.</p></div>
	<div class="card"><div class="tag t-amb">MAC forgery</div><h4>Simon · CBC-MAC</h4><p data-i18n="q-s4">Existential forgery.</p></div>
	<div class="card"><div class="tag t-cyn">Feistel · DES</div><h4>Simon · 3-round</h4><p data-i18n="q-s5">Executed on real hardware ✓</p></div>
	</div>
	</div>
	<div class="section">
	<div style="background:#FEF3C7;border:2px solid var(--amb);border-radius:var(--r);padding:18px 22px">
	<div style="font-weight:800;color:#92400E;margin-bottom:8px" data-i18n="q-honest-h">⚠️ Honest Scope</div>
	<p style="font-size:.84rem;color:#78350F;line-height:1.6" data-i18n="q-honest">This is a record-scale hardware demonstration — NOT a practical quantum speedup (effective difficulty still tracks the classical birthday bound ~2^(n/2)), NOT a break of AES / RSA / 16-round DES, and NOT quantum-error-corrected (NISQ-era mitigation only). World-first status is unconfirmed pending peer review.</p>
	</div>
	</div>
	</div>
	</div>

	<!-- ═══════════ SERVICES ═══════════ -->
	<div class="page" id="page-services">
	<div class="ph" style="background:linear-gradient(135deg,#FFF7ED,#EEF2FF)">
	<div class="container">
	<div class="badge" style="background:var(--amb);color:#92400E">SERVICES</div>
	<h1 data-i18n="services-h1">Proof comes from <span style="color:var(--ind)">usage</span></h1>
	<p data-i18n="services-sub">Live services running on the Darwin + AETHER platform.</p>
	</div>
	</div>

	<div class="subtab-bar">
	<div class="subtab-inner">
	<div class="stab active" onclick="switchTab('services','all',this)"><span data-i18n="svc-tab-all">All</span></div>
	<div class="stab" onclick="switchTab('services','hf',this)">🤗 <span data-i18n="svc-tab-hf">HuggingFace</span></div>
	<div class="stab" onclick="switchTab('services','vkae',this)">⚡ <span data-i18n="svc-tab-vkae">VKAE</span></div>
	<div class="stab" onclick="switchTab('services','gov',this)">🏛️ <span data-i18n="svc-tab-gov">National·Gov</span></div>
	<div class="stab" onclick="switchTab('services','pharma',this)">🔬 <span data-i18n="svc-tab-pharma">Drug·Materials</span></div>
	<div class="stab" onclick="switchTab('services','quantum',this)">⚛️ <span data-i18n="svc-tab-quantum">Quantum·Science</span></div>
	<div class="stab" onclick="switchTab('services','tools',this)">🛡️ <span data-i18n="svc-tab-tools">Tools·Security</span></div>
	<div class="stab" onclick="switchTab('services','building',this)">🏗️ <span data-i18n="svc-tab-building">Building·Design</span></div>
	</div>
	</div>

	<div class="container">

	<!-- 전체보기 -->
	<div class="stab-content active" id="services-all">
	<div class="section">
	<h2 class="st" style="margin-bottom:24px" data-i18n="svc-all-h">All Services <span>at a Glance</span></h2>
	<div class="all-grid">
	<a class="ag-item" href="https://huggingface.co/collections/FINAL-Bench/darwin-family" target="_blank"><div class="ag-icon">🧬</div><h4>Darwin Family</h4><p data-i18n="ag-darwin-p">20 evolutionary models</p></a>
	<a class="ag-item" href="https://huggingface.co/collections/FINAL-Bench/metacognition-adapters" target="_blank"><div class="ag-icon">🧩</div><h4 data-i18n="ag-meta-h">Metacognition Adapters</h4><p data-i18n="ag-meta-p">11 non-invasive adapters</p></a>
	<a class="ag-item" href="https://huggingface.co/collections/FINAL-Bench/vkae-accelerated" target="_blank"><div class="ag-icon">⚡</div><h4 data-i18n="ag-vkae-h">VKAE Serving</h4><p data-i18n="ag-vkae-p">1.5–2× throughput</p></a>
	<a class="ag-item" href="https://huggingface.co/spaces/VIDraft/vkae" target="_blank"><div class="ag-icon">📊</div><h4>VKAE Leaderboard</h4><p data-i18n="ag-vkaelb-p">Single-GPU speed</p></a>
	<a class="ag-item" href="https://hub.docker.com/u/vidraft" target="_blank"><div class="ag-icon">🐳</div><h4>Docker Hub</h4><p data-i18n="ag-docker-p">8 images</p></a>
	<a class="ag-item" href="https://jgos.vidraft.net/" target="_blank"><div class="ag-icon">🏢</div><h4 data-i18n="ag-jgos-h">JGOS Citizen AI</h4><p data-i18n="ag-jgos-p">Sovereign AI for 3.2M</p></a>
	<a class="ag-item" href="https://vidraft-nationalos-regional.hf.space/live" target="_blank"><div class="ag-icon">🗺️</div><h4 data-i18n="ag-national-h">NationalOS</h4><p data-i18n="ag-national-p">250-region digital twin</p></a>
	<a class="ag-item" href="https://huggingface.co/spaces/VIDraft/Darwin-398B-Vision" target="_blank"><div class="ag-icon">👁️</div><h4 data-i18n="ag-vision-h">Darwin Vision</h4><p data-i18n="ag-vision-p">Document & handwriting</p></a>
	<a class="ag-item" href="https://materials.1street.ai/" target="_blank"><div class="ag-icon">⚗️</div><h4 data-i18n="ag-material-h">MaterialsOS</h4><p data-i18n="ag-material-p">New-material AI design</p></a>
	<a class="ag-item" href="https://admet.1street.ai/" target="_blank"><div class="ag-icon">💊</div><h4>ADMET</h4><p data-i18n="ag-admet-p">Drug toxicity prediction</p></a>
	<a class="ag-item" href="https://vidraft-pharmaos.hf.space" target="_blank"><div class="ag-icon">🔬</div><h4 data-i18n="ag-pharma-h">PharmaOS DEEP</h4><p data-i18n="ag-pharma-p">5-stage autonomous drug pipeline</p></a>
	<a class="ag-item" href="https://huggingface.co/spaces/FINAL-Bench/quantum-bench-leaderboard" target="_blank"><div class="ag-icon">⚛️</div><h4 data-i18n="ag-qbench-h">Quantum Bench</h4><p data-i18n="ag-qbench-p">Quantum algorithm rankings</p></a>
	<a class="ag-item" href="https://vidraft-quantumos.hf.space/#console" target="_blank"><div class="ag-icon">🌌</div><h4 data-i18n="ag-quantum-h">QuantumOS</h4><p data-i18n="ag-quantum-p">Quantum sim console</p></a>
	<a class="ag-item" href="https://vidraft-quantumos.hf.space/crypto" target="_blank"><div class="ag-icon">🔓</div><h4 data-i18n="ag-qcrypto-h">QuantumOS Crypto</h4><p data-i18n="ag-qcrypto-p">Real HW cryptanalysis</p></a>
	<a class="ag-item" href="https://huggingface.co/spaces/VIDraft/chitos" target="_blank"><div class="ag-icon">🛡️</div><h4>CHITOS</h4><p data-i18n="ag-chitos-p">AI code security scan</p></a>
	<a class="ag-item" href="https://hansoo.vidraft.net" target="_blank"><div class="ag-icon">🏯</div><h4 data-i18n="ag-hansoo-h">HanSoo (韓守)</h4><p data-i18n="ag-hansoo-p">Fully local AI office</p></a>
	<a class="ag-item" href="https://vidraft-mouse.hf.space" target="_blank"><div class="ag-icon">🐭</div><h4>MOUSE</h4><p data-i18n="ag-mouse-p">Multi-agent code AI</p></a>
	<a class="ag-item" href="https://building.vidraft.net/" target="_blank"><div class="ag-icon">🏗️</div><h4 data-i18n="ag-floorplan-h">FloorPlan AI</h4><p data-i18n="ag-floorplan-p">NL → KS F 1501 drawings</p></a>
	</div>
	</div>
	</div>

	<!-- 모델·HF 컬렉션 -->
	<div class="stab-content" id="services-hf">
	<div class="section">
	<h2 class="st" style="margin-bottom:8px" data-i18n="svc-hf-h">HuggingFace <span>Collections & Models</span></h2>
	<p class="ss" data-i18n="svc-hf-s">Official collections managed under FINAL-Bench · VIDraft organizations.</p>
	<!-- 메인 포털 Space -->
	<a class="hf-card" href="https://huggingface.co/spaces/VIDraft/AI" target="_blank" style="display:block;margin-bottom:20px;background:linear-gradient(135deg,var(--ind-xxl),var(--cyn-l));border:2px solid var(--ind)">
	<div style="display:flex;gap:16px;align-items:center;flex-wrap:wrap">
	<div style="font-size:2.4rem;line-height:1">🚀</div>
	<div style="flex:1;min-width:200px">
	<div style="font-size:.72rem;color:var(--ind);font-weight:700;margin-bottom:3px" data-i18n="hf-portal-label">VIDraft · Main Portal · Space</div>
	<h3 style="font-size:1.1rem;margin-bottom:4px">VIDRAFT — Korea's AGI Journey</h3>
	<p style="font-size:.85rem;color:var(--muted)" data-i18n="hf-portal-p">Full introduction to the Darwin + AETHER ecosystem (KO/EN). Darwin 1.7B–398B · 11 patents · 9 live services · Blackwell 32-GPU infrastructure · metacognition tech overview.</p>
	</div>
	<div style="background:var(--ind);color:#fff;font-size:.8rem;font-weight:700;padding:6px 16px;border-radius:8px;flex-shrink:0;white-space:nowrap" data-i18n="hf-portal-btn">Open Main Portal →</div>
	</div>
	</a>
	<div class="grid g2" style="margin-bottom:32px">
	<a class="hf-card" href="https://huggingface.co/collections/FINAL-Bench/darwin-family" target="_blank">
	<div style="display:flex;gap:12px;align-items:center"><div class="hf-logo">🧬</div><div><div style="font-size:.72rem;color:#FF6B35;font-weight:700">FINAL-Bench Collection</div><h3>DARWIN-Family</h3></div></div>
	<p data-i18n="hf-darwin-p">"The child surpassed both parents — that is evolution." Complete collection of 20 evolutionary language models from Darwin-2B to Darwin-398B. Linked with the arXiv 2605.14386 paper.</p>
	<div class="hf-models">
	<span class="hf-model-tag">Darwin-398B-JGOS</span><span class="hf-model-tag">Darwin-36B-Opus</span><span class="hf-model-tag">Darwin-28B-Opus</span><span class="hf-model-tag">Darwin-4B-David</span><span class="hf-model-tag">+16</span>
	</div>
	<div class="hf-meta"><span data-i18n="hf-darwin-m1">📦 20 models</span><span data-i18n="hf-darwin-m2">⬇️ 1M+ downloads</span></div>
	</a>
	<a class="hf-card" href="https://huggingface.co/collections/FINAL-Bench/metacognition-adapters" target="_blank">
	<div style="display:flex;gap:12px;align-items:center"><div class="hf-logo">🧩</div><div><div style="font-size:.72rem;color:#FF6B35;font-weight:700">FINAL-Bench Collection</div><h3>Metacognition Adapters</h3></div></div>
	<p data-i18n="hf-meta-p">11 non-invasive adapters that add self-error detection to major Darwin models without changing the original structure.</p>
	<div class="hf-models">
	<span class="hf-model-tag">Darwin-28B-Opus</span><span class="hf-model-tag">Darwin-9B-NEG</span><span class="hf-model-tag">JGOS-31B-Citizen</span><span class="hf-model-tag">Qwen3.5-35B</span><span class="hf-model-tag">+7</span>
	</div>
	<div class="hf-meta"><span data-i18n="hf-meta-m1">📦 11 adapters</span><span data-i18n="hf-meta-m2">🧠 Non-invasive</span></div>
	</a>
	<a class="hf-card" href="https://huggingface.co/collections/FINAL-Bench/vkae-accelerated" target="_blank">
	<div style="display:flex;gap:12px;align-items:center"><div class="hf-logo">⚡</div><div><div style="font-size:.72rem;color:#FF6B35;font-weight:700">FINAL-Bench Collection</div><h3>VKAE Accelerated</h3></div></div>
	<p data-i18n="hf-vkae-p">"Fastest single-GPU serving of open models via VKAE." Inference-acceleration models achieving 1.5–2× throughput on a single GPU. OpenAI-compatible API, ready to use.</p>
	<div class="hf-models">
	<span class="hf-model-tag">Qwen3.5-35B-A3B-VKAE · 601 tok/s</span><span class="hf-model-tag">Darwin-36B-VKAE · 280 tok/s</span>
	</div>
	<div class="hf-meta"><span data-i18n="hf-vkae-m1">⚡ 1.5–2×</span><span data-i18n="hf-vkae-m2">🔌 OpenAI-compatible</span></div>
	</a>
	<a class="hf-card" href="https://huggingface.co/spaces/FINAL-Bench/quantum-bench-leaderboard" target="_blank">
	<div style="display:flex;gap:12px;align-items:center"><div class="hf-logo" style="background:var(--pur-l)">⚛️</div><div><div style="font-size:.72rem;color:#FF6B35;font-weight:700">FINAL-Bench Space</div><h3>Quantum Bench Leaderboard</h3></div></div>
	<p data-i18n="hf-quantum-p">Quantum computing algorithm performance leaderboard. Includes real IBM Heron QPU measurements. NIST randomness verification · Bell inequality violation · VQE · QRAM experiment results.</p>
	<div class="hf-meta"><span data-i18n="hf-quantum-m1">⚛️ IBM Heron QPU</span><span data-i18n="hf-quantum-m2">📊 NIST 6/6</span></div>
	</a>
	</div>
	</div>
	</div>

	<!-- 추론 가속 -->
	<div class="stab-content" id="services-vkae">
	<div class="section">
	<h2 class="st" style="margin-bottom:8px" data-i18n="svc-vkae-h">VKAE <span>Inference Acceleration</span></h2>
	<p class="ss" data-i18n="svc-vkae-s">Achieves 1.5–2× throughput vs. baseline on a single GPU.</p>
	<div class="hl" style="margin-bottom:32px">
	<h3 data-i18n="vkae-hl-h">⚡ 455 / 601 tok/s on a single B200 GPU</h3>
	<p data-i18n="vkae-hl-p">The VKAE breakthrough stack delivers 1.5–2× the throughput of standard serving for a 35B-A3B model on one B200 GPU.</p>
	</div>
	<div class="grid g2" style="margin-bottom:32px">
	<a class="sc" href="https://huggingface.co/spaces/VIDraft/vkae" target="_blank">
	<div class="sc-icon">📊</div>
	<div class="tag t-ind" data-i18n="vkae-lb-tag">Live Leaderboard</div>
	<h3 data-i18n="vkae-lb-h">VKAE Serving Leaderboard</h3>
	<p data-i18n="vkae-lb-p">Single-GPU serving speed rankings. Darwin · Qwen model throughput comparison. OpenAI-compatible API endpoint provided.</p>
	<div class="sc-link">huggingface.co/spaces/VIDraft/vkae</div>
	</a>
	<a class="sc" href="https://hub.docker.com/u/vidraft" target="_blank">
	<div class="sc-icon">🐳</div>
	<div class="tag t-cyn">Docker Hub</div>
	<h3 data-i18n="vkae-docker-h">Verified Docker Images</h3>
	<p data-i18n="vkae-docker-p">8 Docker images verified for K-AI leaderboard submission. Bake-in method (works without internet on the evaluation server). OpenAI-compatible API.</p>
	<div class="docker-card" style="margin-top:12px;padding:12px">
	<div class="docker-row"><div class="docker-name">darwin36-vkae</div><div class="docker-desc" data-i18n="vkae-d1">Darwin-36B-Opus VKAE</div><div class="docker-speed">280.8 tok/s</div></div>
	<div class="docker-row"><div class="docker-name">qwen35-vkae</div><div class="docker-desc">Qwen3.5-35B-A3B VKAE</div><div class="docker-speed">601 tok/s</div></div>
	<div class="docker-row"><div class="docker-name">JGOS-31B</div><div class="docker-desc" data-i18n="vkae-d3">JGOS-31B-Citizen VKAE</div><div class="docker-speed">K-AI #1</div></div>
	<div class="docker-row"><div class="docker-name">JGOS-158B / 398B</div><div class="docker-desc" data-i18n="vkae-d4">Darwin-398B-JGOS VKAE</div><div class="docker-speed">+5</div></div>
	</div>
	<div class="sc-link">hub.docker.com/u/vidraft</div>
	</a>
	</div>
	<div class="warn">
	⚠️ <span data-i18n="vkae-warn">Internal serving infrastructure — access requires an internal-network account.</span>
	</div>
	</div>
	</div>

	<!-- 국가·행정 AI -->
	<div class="stab-content" id="services-gov">
	<div class="section">
	<h2 class="st" style="margin-bottom:8px" data-i18n="svc-gov-h">National & Government <span>AI Services</span></h2>
	<p class="ss" data-i18n="svc-gov-s">Public administration AI based on K-AI #1 model — Korean sovereign AI for 3.2M citizens.</p>
	<div class="grid g2">
	<a class="sc" href="https://jgos.vidraft.net/" target="_blank">
	<div class="sc-icon">🏢</div>
	<div class="tag t-em" data-i18n="gov-jgos-tag">K-AI #1 Model</div>
	<h3 data-i18n="gov-jgos-h">JGOS — Jeonnam·Gwangju Citizen AI</h3>
	<p data-i18n="gov-jgos-p">Korean sovereign AI for 3.2M citizens. Administration · law · tourism · civil affairs · transport · culture · statistics · agriculture guidance. Analyzes 10+ file formats (HWP·PDF·Excel·images). Includes free citizen AI education. Based on JGOS-31B-Citizen.</p>
	<div class="sc-link">jgos.vidraft.net</div>
	<div class="sc-sub" data-i18n="gov-jgos-sub">※ Test version · no official administrative effect</div>
	</a>
	<a class="sc" href="https://vidraft-nationalos-regional.hf.space/live" target="_blank">
	<div class="sc-icon">🗺️</div>
	<div class="tag t-ind" data-i18n="gov-national-tag">Digital Twin</div>
	<h3 data-i18n="gov-national-h">NationalOS — Regional Digital Twin</h3>
	<p data-i18n="gov-national-p">52M-person simulation based on KOSIS data. 250 cities/counties × 17 metropolitan regions, 3-tier analysis. Quick (10–30s) / Regional (1–3min) / Deep (5–15min) three stages. 9-Agent hallucination-prevention engine. Generates policy-impact interviews via persona matching.</p>
	<div class="sc-link">vidraft-nationalos-regional.hf.space/live</div>
	</a>
	</div>
	</div>
	</div>

	<!-- 신약·소재 -->
	<div class="stab-content" id="services-pharma">
	<div class="section">
	<h2 class="st" style="margin-bottom:8px" data-i18n="svc-pharma-h">Drug & Materials <span>AI</span></h2>
	<p class="ss" data-i18n="svc-pharma-s">Polaris Global 14× Champion · From autonomous drug discovery to new material design.</p>
	<div class="grid g2">
	<a class="sc" href="https://huggingface.co/spaces/VIDraft/Darwin-398B-Vision" target="_blank">
	<div class="sc-icon">👁️</div>
	<div class="tag t-ind" data-i18n="ph-vision-tag">Vision AI</div>
	<h3 data-i18n="ph-vision-h">Darwin-398B Vision</h3>
	<p data-i18n="ph-vision-p">FastAPI + Docker based. Connected to the Darwin-398B-AX production backend. Handwriting recognition · MSDS hazard extraction · health-checkup reading. KIHA SFR-004/001 industrial-safety demo. PDF·PNG·JPG·WEBP support.</p>
	<div class="sc-link">huggingface.co/spaces/VIDraft/Darwin-398B-Vision</div>
	</a>
	<a class="sc" href="https://materials.1street.ai/" target="_blank">
	<div class="sc-icon">⚗️</div>
	<div class="tag t-pur" data-i18n="ph-material-tag">Quantum-Integrated</div>
	<h3 data-i18n="ph-material-h">MaterialsOS — New-Material AI Design</h3>
	<p data-i18n="ph-material-p">MatterGen→MLIP→UQ→4-DB novelty check→Hull→IBM Heron QPU cross-validation 7-gate pipeline. Generative AI + real QPU integration. Compatible with Korea IonQ/KISTI. Paper + patent linkage.</p>
	<div class="sc-link">materials.1street.ai</div>
	<div class="sc-sub" data-i18n="ph-material-sub">※ Contact for access</div>
	</a>
	<a class="sc" href="https://admet.1street.ai/" target="_blank">
	<div class="sc-icon">💊</div>
	<div class="tag t-em" data-i18n="ph-admet-tag">Polaris 14× Champion</div>
	<h3 data-i18n="ph-admet-h">ADMET — Toxicity·Absorption·Metabolism Prediction</h3>
	<p data-i18n="ph-admet-p">Predicts 5 indicators: Absorption · Distribution · Metabolism · Excretion · Toxicity. Based on the Polaris global-leaderboard 14× champion model. BRICS molecule generation + Boltz-2 docking. tox21-v4 scaffold-holdout AUC 0.790.</p>
	<div class="sc-link">admet.1street.ai</div>
	<div class="sc-sub" data-i18n="ph-admet-sub">※ Contact for access</div>
	</a>
	<a class="sc" href="https://vidraft-pharmaos.hf.space" target="_blank">
	<div class="sc-icon">🔬</div>
	<div class="tag t-ros" data-i18n="ph-pharma-tag">Autonomous Drug</div>
	<h3 data-i18n="ph-pharma-h">PharmaOS DEEP — 5-Stage Autonomous Pipeline</h3>
	<p data-i18n="ph-pharma-p">RAG→SMILES generation→CythoS validation→SOTA ranking→report. Covers 14 indications. Built-in autonomous retry loop.</p>
	<div class="sc-link">vidraft-pharmaos.hf.space</div>
	</a>
	</div>
	</div>
	</div>

	<!-- 양자·과학 -->
	<div class="stab-content" id="services-quantum">
	<div class="section">
	<h2 class="st" style="margin-bottom:8px" data-i18n="svc-quantum-h">Quantum & Science <span>AI</span></h2>
	<p class="ss" data-i18n="svc-quantum-s">IBM Heron QPU measured · NIST randomness 6/6 passed · Real quantum experiment integration.</p>
	<div class="grid g3">
	<a class="sc" href="https://vidraft-quantumos.hf.space/crypto" target="_blank">
	<div class="sc-icon">🔓</div>
	<div class="tag t-ros" data-i18n="q-crypto-tag">Cryptanalysis · Real HW</div>
	<h3 data-i18n="q-crypto-h">QuantumOS Cryptanalysis Demo</h3>
	<p data-i18n="q-crypto-p">Genuine quantum-algorithm cryptanalysis suite executed on IBM Kingston real hardware — Even-Mansour N=10 and 3-round Feistel (DES-style) blocks 6/8, rank-1 clean. Honest scope disclosure: not real AES/RSA, not quantum supremacy.</p>
	<div class="sc-link">vidraft-quantumos.hf.space/crypto</div>
	</a>
	<a class="sc" href="https://vidraft-quantumos.hf.space/#console" target="_blank">
	<div class="sc-icon">🌌</div>
	<div class="tag t-pur" data-i18n="q-os-tag">Quantum Console</div>
	<h3 data-i18n="q-os-h">QuantumOS — Quantum Simulation Console</h3>
	<p data-i18n="q-os-p">Quantum circuit design · simulation · execution. Visualizes real IBM QPU measurement data. NIST randomness (6/6 pass) · min-entropy 0.974 · Bell inequality violation (2.371) · VQE · QRAM experiments. Run directly in the #console tab.</p>
	<div class="sc-link">vidraft-quantumos.hf.space/#console</div>
	</a>
	<a class="sc" href="https://huggingface.co/spaces/FINAL-Bench/quantum-bench-leaderboard" target="_blank">
	<div class="sc-icon">⚛️</div>
	<div class="tag t-ind" data-i18n="q-bench-tag">Leaderboard</div>
	<h3 data-i18n="q-bench-h">Quantum Bench Leaderboard</h3>
	<p data-i18n="q-bench-p">Quantum algorithm and simulator performance comparison leaderboard. Real QPU measurements shown side-by-side with simulation results. HF Docker metadata auto-updated. 27 likes.</p>
	<div class="sc-link">huggingface.co/spaces/FINAL-Bench/quantum-bench-leaderboard</div>
	</a>
	</div>
	</div>
	</div>

	<!-- 도구·보안 -->
	<div class="stab-content" id="services-tools">
	<div class="section">
	<h2 class="st" style="margin-bottom:8px" data-i18n="svc-tools-h">Tools & Security <span>AI</span></h2>
	<p class="ss" data-i18n="svc-tools-s">AI security, code agent, local office, legal AI — productivity tools collection.</p>
	<div class="grid g3">
	<a class="sc" href="https://huggingface.co/spaces/VIDraft/chitos" target="_blank">
	<div class="sc-icon">🛡️</div>
	<div class="tag t-ros" data-i18n="tl-chitos-tag">AI Security</div>
	<h3>CHITOS — AI Security Scanner</h3>
	<p data-i18n="tl-chitos-p">AI-based code security vulnerability detection. OWASP Top 10 · dependency analysis · secret-key exposure check. Darwin-backbone security fine-tuning.</p>
	<div class="sc-link">huggingface.co/spaces/VIDraft/chitos</div>
	</a>
	<a class="sc" href="https://hansoo.vidraft.net" target="_blank">
	<div class="sc-icon">🏯</div>
	<div class="tag t-em" data-i18n="tl-hansoo-tag">Data Sovereignty</div>
	<h3 data-i18n="tl-hansoo-h">HanSoo (韓守) — Fully Local AI Office</h3>
	<p data-i18n="tl-hansoo-p">Browser-based, works without internet. Zero external data transmission. HWP·DOCX·PPT·XLSX·PDF support. MIT license. Released 2026.04.19.</p>
	<div class="sc-link">hansoo.vidraft.net</div>
	</a>
	<a class="sc" href="https://vidraft-mouse.hf.space" target="_blank">
	<div class="sc-icon">🐭</div>
	<div class="tag t-cyn" data-i18n="tl-mouse-tag">Multi-agent</div>
	<h3 data-i18n="tl-mouse-h">MOUSE — Code Agent</h3>
	<p data-i18n="tl-mouse-p">Multi-agent code AI. 1.5M+ MAU verified. Darwin-backbone swarm collaboration. SOMA multi-intelligence architecture.</p>
	<div class="sc-link">vidraft-mouse.hf.space</div>
	</a>
	<a class="sc" href="https://vidraft-legalflow.hf.space" target="_blank">
	<div class="sc-icon">⚖️</div>
	<div class="tag t-ind" data-i18n="tl-legal-tag">Legal AI</div>
	<h3>LegalFlow v1.5</h3>
	<p data-i18n="tl-legal-p">Case-law-grounded accurate legal AI. RAG + Darwin legal fine-tuning removes legal hallucination.</p>
	<div class="sc-link">vidraft-legalflow.hf.space</div>
	</a>
	<a class="sc" href="https://vidraft-paper.hf.space" target="_blank">
	<div class="sc-icon">📝</div>
	<div class="tag t-amb" data-i18n="tl-paper-tag">Research Tool</div>
	<h3 data-i18n="tl-paper-h">Auto Paper Generator</h3>
	<p data-i18n="tl-paper-p">AI paper writing & enhancement agent. Automates draft generation, reference organization, and improvement suggestions.</p>
	<div class="sc-link">vidraft-paper.hf.space</div>
	</a>
	<a class="sc" href="https://vidraft-model-galaxy.hf.space" target="_blank">
	<div class="sc-icon">🌌</div>
	<div class="tag t-ind" data-i18n="tl-galaxy-tag">Model Explorer</div>
	<h3>Model Galaxy</h3>
	<p data-i18n="tl-galaxy-p">22,400+ model sigma.js interactive visualization. Darwin·Trending·Multimodal 5 clusters. Galaxy / Atlas 2 modes.</p>
	<div class="sc-link">vidraft-model-galaxy.hf.space</div>
	</a>
	</div>
	</div>
	</div>

	<!-- 건축설계 FloorPlan AI -->
	<div class="stab-content" id="services-building">
	<div class="section">
	<h2 class="st" style="margin-bottom:8px" data-i18n="svc-building-h">FloorPlan AI <span>Architectural Design</span></h2>
	<p class="ss" data-i18n="svc-building-s">From a Korean sentence to a verified floor plan — or from a parcel address to a code-compliant 3D building. Drawings, BIM, cost and fire-safety in minutes.</p>
	<div class="hl" style="margin-bottom:28px">
	<h3>🏗️ Darwin-398B-AX (JGOS) · KS F 1501</h3>
	<p data-i18n="svc-building-s2">Natural language becomes KS F 1501 drawings, 3D, walkthrough and quantity takeoff — designed by a 397B-parameter MoE and reviewed by a VLM critic.</p>
	</div>
	<div class="grid g3" style="margin-bottom:16px">
	<div class="card"><div class="ci ci-ind">📐</div><h3 data-i18n="svc-fp1-h">Text → standard floor plans</h3><p data-i18n="svc-fp1-p">Natural language becomes KS F 1501 drawings (parallel drafts + AI review) — mm, 1:100, wall poché, area table.</p></div>
	<div class="card"><div class="ci ci-amb">✅</div><h3 data-i18n="svc-fp2-h">6 automatic checks</h3><p data-i18n="svc-fp2-p">Building code · fire safety · barrier-free access · design metrics · cost estimate · AI review score.</p></div>
	<div class="card"><div class="ci ci-em">🏢</div><div class="tag t-em">NEW</div><h3 data-i18n="svc-fp3-h">Parcel → site design</h3><p data-i18n="svc-fp3-p">Type a parcel address: zoning, official land price and lot boundaries fetched from the national V-World open-data platform.</p></div>
	<div class="card"><div class="ci ci-cyn">📊</div><div class="tag t-cyn">NEW</div><h3 data-i18n="svc-fp4-h">FAR slider + solar setback 3D</h3><p data-i18n="svc-fp4-p">Statutory coverage/FAR enforced geometrically; north solar-setback cut into the 3D mass; FAR slider recomputes area, floors and cost live.</p></div>
	<div class="card"><div class="ci ci-ind">🧭</div><h3 data-i18n="svc-fp5-h">Layout-quality score</h3><p data-i18n="svc-fp5-p">Zoning, privacy, south exposure, circulation and proportion scored 0–100 by deterministic rules — not AI self-assessment.</p></div>
	<div class="card"><div class="ci ci-em">⬇️</div><h3 data-i18n="svc-fp6-h">Export DXF·PDF·IFC·BOQ</h3><p data-i18n="svc-fp6-p">DXF (AutoCAD) · PDF (A3 sheet) · IFC (BIM) · XLSX quantity takeoff.</p></div>
	<div class="card"><div class="ci ci-amb">🚶</div><h3 data-i18n="svc-fp7-h">Walk · sun study · aerials</h3><p data-i18n="svc-fp7-p">First-person walk mode, monthly/hourly sun study, and AI photoreal renders and aerials.</p></div>
	</div>
	<p style="font-size:.72rem;color:var(--muted);margin-bottom:24px" data-i18n="svc-fp-disc">※ AI concept-design reference only — coverage/FAR use statutory maximums (actual limits depend on local ordinances), official land price is not market price, and permit and construction documents proceed with a licensed architect.</p>
	<div style="display:flex;gap:12px;flex-wrap:wrap">
	<a href="https://building.vidraft.net/" target="_blank" style="display:inline-block;background:var(--ind);color:#fff;padding:11px 22px;border-radius:10px;font-weight:700;font-size:.85rem;text-decoration:none" data-i18n="svc-fp-cta1">Open FloorPlan AI →</a>
	<a href="https://brunch.co.kr/@seawolf/149" target="_blank" style="display:inline-block;background:var(--ind-xl);color:var(--ind);padding:11px 22px;border-radius:10px;font-weight:700;font-size:.85rem;text-decoration:none" data-i18n="svc-fp-cta2">Read the story (Brunch) →</a>
	</div>
	</div>
	</div>

	</div><!-- /container services -->
	</div>

	<!-- ═══════════ BLOG ═══════════ -->
	<div class="page" id="page-blog">
	<div class="ph" style="background:linear-gradient(135deg,#F0FDF4,#EEF2FF)">
	<div class="container">
	<div class="badge" style="background:var(--em)">BLOG</div>
	<h1 data-i18n="blog-h1">AI Insights, <span style="color:var(--ind)">fresh daily</span></h1>
	<p data-i18n="blog-sub">AI essays auto-written daily from news curated by VIDraft.</p>
	</div>
	</div>
	<div class="container">
	<div class="section">
	<!-- 최신 아티클: 중국 AI 싱크탱크 보도 -->
	<div style="display:flex;gap:10px;align-items:center;margin-bottom:28px;flex-wrap:wrap">
	<span style="background:var(--ind);color:#fff;font-size:.72rem;font-weight:700;padding:3px 11px;border-radius:100px" data-i18n="blog-latest">Latest Post</span>
	<span style="font-size:.8rem;color:var(--muted)" class="ko-only">2026.07.04 · 중국 AI 싱크탱크 보도</span>
	<span style="font-size:.8rem;color:var(--muted)" class="en-only">2026.07.04 · Chinese AI Think Tank Report</span>
	</div>

	<article class="ko-only" style="background:#fff;border:1px solid var(--border);border-radius:var(--r);box-shadow:var(--sh-lg);overflow:hidden;margin-bottom:40px">
	<!-- 아티클 헤더: 중국 싱크탱크 보도 -->
	<div style="background:linear-gradient(135deg,#7F1D1D,#1E1B4B);padding:40px 40px 32px">
	<div style="display:flex;gap:8px;margin-bottom:16px;flex-wrap:wrap">
	<span style="background:rgba(239,68,68,.3);color:#FCA5A5;font-size:.72rem;font-weight:700;padding:3px 10px;border-radius:100px">중국 텐센트 뉴스</span>
	<span style="background:rgba(16,185,129,.25);color:#6EE7B7;font-size:.72rem;font-weight:700;padding:3px 10px;border-radius:100px">세계 유일</span>
	<span style="background:rgba(245,158,11,.2);color:#FCD34D;font-size:.72rem;font-weight:700;padding:3px 10px;border-radius:100px">GPU 24장</span>
	</div>
	<h2 style="color:#fff;font-size:1.55rem;font-weight:800;line-height:1.4;margin-bottom:12px">중국 AI 싱크탱크가 격찬한, 유일한 한국 AI 기술</h2>
	<p style="color:#94A3B8;font-size:.9rem;line-height:1.7">중국 최대 포털 텐센트 뉴스에 올라온 기사 제목부터 예사롭지 않았다. "훈련 없이도 더 똑똑해진다? 한국 VIDRAFT사가 개발한 '다윈 패밀리', AI 모델을 '유전자 재조합'으로 능력 도약시키다."</p>
	<div style="margin-top:20px;display:flex;align-items:center;gap:16px;flex-wrap:wrap">
	<div style="background:linear-gradient(135deg,#4338CA,#06B6D4);border-radius:10px;padding:12px 24px;display:inline-block">
	<div style="color:#fff;font-size:2rem;font-weight:900;line-height:1">24장 <span style="font-size:1rem;font-weight:600">GPU</span></div>
	<div style="color:#A5B4FC;font-size:.75rem;margin-top:2px">블랙웰 B200 16장 + H200 8장 · GPQA 90.9%</div>
	</div>
	<div style="color:#94A3B8;font-size:.82rem">
	<div>📌 즈딩커지(至顶科技) · ZDNet 차이나 계보 30년 매체</div>
	<div>🏆 세계 <strong style="color:#6EE7B7">유일</strong> 크로스 아키텍처 모델 병합</div>
	</div>
	</div>
	</div>
	<!-- 아티클 본문 -->
	<div style="padding:40px;line-height:1.9;color:var(--text);font-size:.95rem" class="blog-body">

	<p style="font-size:.8rem;color:var(--light)">by SeaWolf</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:8px 0 12px;color:var(--ind)">프롤로그 — 어느 날, 베이징에서 날아온 한국 이야기</h3>
	<p>2026년 5월 21일 오후 2시 8분, 베이징. 중국 최대 포털 텐센트 뉴스(腾讯新闻)에 조금 낯선 기사가 올라왔다. 미국 오픈AI 소식도, 자국 딥시크 자랑도 아니었다. 놀랍게도 한국 서울의 한 AI 연구팀 이야기였다.</p>
	<p>제목부터 예사롭지 않았다.</p>
	<blockquote style="border-left:4px solid var(--ind);padding:14px 20px;margin:24px 0;background:var(--ind-xxl);border-radius:0 8px 8px 0;font-style:italic;color:var(--ind);font-weight:600">无需训练也能更聪明？韩国VIDRAFT公司研发的"达尔文家族"让AI模型通过"基因重组"实现能力跃升<br><span style="font-style:normal;font-weight:500;color:var(--text);font-size:.9rem">"훈련 없이도 더 똑똑해진다? 한국 VIDRAFT사가 개발한 '다윈 패밀리', AI 모델을 '유전자 재조합'으로 능력 도약시키다"</span></blockquote>
	<p>우리는 흔히 이런 기사를 볼 때 "누가 썼느냐"를 먼저 따진다. 개인 블로거의 감상이라면 가볍게 넘길 일이고, 권위 있는 매체의 분석이라면 무게가 다르기 때문이다. 그래서 나는 이 기사를 쓴 곳부터 파고들었다. 그리고 그 정체를 확인한 순간, 이 이야기가 왜 특별한지 분명해졌다.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">1부. 이 기사를 쓴 곳은 '중국의 전자신문'이었다</h3>
	<p>기사의 바이라인에 찍힌 이름은 개인 기자가 아니라 매체 자체의 명의, 즈딩커지(至顶科技)였다.</p>
	<p>이름은 낯설어도 이력은 묵직하다. 즈딩커지의 뿌리는 1997년 4월 중국에 상륙한 글로벌 IT 매체 'ZDNet 차이나'다. 무려 30년 가까이 이어져 온, 중국에서 가장 오래된 기술 전문 미디어 중 하나다. 지금은 기업용 AI 포털 '즈딩왕(至顶网)', AI 창업 매체 '과학기술행자(科技行者)', 산업 싱크탱크 '즈딩즈쿠(至顶智库)', 그리고 결정적으로 자체 AI 성능 평가 기관인 '즈딩 AI 실험실(至顶AI实验室)'까지 거느린 곳이다.</p>
	<p>이곳을 이끄는 총편집장은 가오페이(高飞). 2002년 세계 1위 IT 미디어 CNET에 합류해 20년 넘게 엔비디아·인텔·마이크로소프트·레노버를 취재해온 중국 테크 저널리즘의 베테랑이다. 중국상장사협회 정보·디지털화위원회 위원이자 개인 AI 콘텐츠 브랜드 '高飞的电子替身(가오페이의 전자 분신)'을 운영하는, 업계가 인정하는 논객이기도 하다.</p>
	<p>정리하면 이렇다. 우리 식으로 비유하자면, '전자신문'이나 'ZDNet 코리아'급의 30년 된 권위 매체가, 그것도 자체 AI 벤치마크 실험실까지 동원할 수 있는 곳이 한국의 기술을 논문 번호(arXiv:2605.14386)까지 콕 짚어가며 분석 기사를 낸 것이다.</p>
	<p>이게 왜 '사건'인가. 지금 중국은 미국과 AI 패권을 놓고 사활을 건 전쟁 중이다. 자국 모델을 띄우기에도 지면이 모자랄 시기다. 그런 매체가 굳이 지면과 취재력을 들여 경쟁국도 아닌 옆 나라, 그것도 대기업이 아닌 스타트업의 기술을 이토록 정성 들여 해부했다. 이건 홍보도, 인사치레도 아니다. "이건 기록해둘 만큼 진짜다"라는 냉정한 판단이 없으면 나올 수 없는 기사다.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">2부. 중국은 왜 '남의 나라' 기술을 이토록 빨리 파고들까</h3>
	<p>본론에 들어가기 전에, 잠깐 질문을 던지고 싶다. 애초에 중국은 어떻게 이 한국 기술을 이렇게 빨리 포착했을까? 그리고 더 근본적으로 — 중국 AI는 어떻게 그토록 짧은 시간에 세계 최상위권까지 치고 올라왔을까?</p>
	<p>2025년 초 '딥시크 쇼크'를 기억할 것이다. 미국이 수십조 원을 쏟아붓던 분야에서, 중국의 한 팀이 훨씬 적은 비용으로 대등한 모델을 내놓으며 전 세계를 얼어붙게 만들었다. 그 저력의 뿌리를 한 단어로 요약하면 이렇다.</p>
	<blockquote style="border-left:4px solid var(--amb);padding:14px 20px;margin:24px 0;background:var(--amb-l);border-radius:0 8px 8px 0;font-weight:700;color:#78350F">정보력 · 분석력 · 공유.</blockquote>
	<p>중국 AI 생태계의 진짜 엔진은 물량이 아니라 '속도'다. 전 세계에서 나오는 모든 기술을 빛의 속도로 수집하고(정보력), 뜯어서 원리를 파악하고(분석력), 커뮤니티에 아낌없이 풀어놓는다(공유). 어제 미국에서 논문이 나오면, 오늘 중국 깃허브에 재현 코드가 올라온다. 이 '빠른 흡수 → 분석 → 확산'의 문화가 중국을 순식간에 2강으로 밀어 올렸다.</p>
	<p>바로 그 무시무시한 레이더망에 — 한국의 다윈이 걸렸다.</p>
	<p>이 대목을 곱씹어보자. 즈딩 AI 실험실의 촉수가 전 세계 수천 편의 논문과 모델을 훑던 중, 수많은 미국·유럽·자국 기술을 제치고 "이건 반드시 우리 독자에게 알려야 한다"며 골라낸 것이 한국 스타트업의 기술이었다. 세계에서 가장 냉정하고 가장 빠른 기술 필터를 통과한 것. 그것이 이 이야기의 첫 번째 자부심이다.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">3부. 도대체 '다윈'이 뭐길래 — 5분이면 이해하는 핵심 기술</h3>
	<p>중국이 감탄한 기술을 이해하려면, 먼저 지금까지 AI를 만드는 방식이 얼마나 '무식하게 비쌌는지'를 알아야 한다.</p>
	<p>기존 방식은 이랬다. 똑똑한 AI를 만들려면 천문학적인 데이터를 몇 주에서 몇 달씩 GPU에 쏟아부어 '처음부터' 학습시켜야 했다. 수백억 원의 전기요금과 장비값이 드는, 사실상 거대 자본만의 게임이었다.</p>
	<p>비드래프트의 다윈은 이 상식을 통째로 뒤집었다. 발상은 이렇다.</p>
	<blockquote style="border-left:4px solid var(--em);padding:14px 20px;margin:24px 0;background:var(--em-l);border-radius:0 8px 8px 0;font-style:italic;color:#065F46;font-weight:600">不靠额外训练，而是通过重新组织已有模型里的能力来提升性能<br><span style="font-style:normal;font-weight:500;color:var(--text);font-size:.9rem">"추가 훈련에 기대지 않고, 이미 존재하는 모델 속 능력을 '재조직'함으로써 성능을 끌어올린다."</span></blockquote>
	<p>무슨 뜻인가. 세상에는 이미 잘 만들어진 오픈소스 AI들이 많다. 어떤 모델은 수학을 잘하고, 어떤 모델은 코딩을 잘하고, 어떤 모델은 한국어를 잘한다. 다윈은 이 서로 다른 AI 둘을 '부모'처럼 교배시켜, 각자의 장점만 물려받은 '자식' 모델을 낳는다. 새로 가르치는 게 아니라, 이미 있는 능력을 합쳐 새 생명을 만드는 것이다. 다윈(Darwin)—진화론의 그 이름—을 붙인 이유가 여기 있다.</p>
	<p>이것을 전문 용어로 '모델 병합(Model Merging)'이라 부른다. 그리고 이 분야에는 넘볼 수 없어 보이던 원조가 있었다. 바로 일본이다.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">4부. 일본이 세운 정점 — 사카나AI라는 거대한 벽</h3>
	<p>모델 병합이라는 분야를 처음 개척하고 세계적 명성을 얻은 곳은 일본의 사카나AI(Sakana AI)다. 이 회사가 어떤 곳인지 알면 '벽'이라는 표현이 과장이 아님을 알게 된다.</p>
	<p>사카나AI는 오늘날 모든 챗GPT의 뿌리가 된 구글의 전설적 논문 'Attention Is All You Need'(트랜스포머 논문)의 공동 저자가 도쿄에 세운 회사다. 세계 최정상급 연구진이, "AI를 진화 알고리즘으로 교배시킨다"는 참신한 아이디어 — 진화적 병합, EvoMerge — 를 처음 세상에 선보이며 글로벌 AI 학계의 스타로 떠올랐다. 오랫동안 모델 병합 분야에서 사카나는 누구도 넘지 못한 정점이었다.</p>
	<p>그리고 바로 이 지점에서, 중국 기자의 문장이 우리를 뭉클하게 만든다. 그는 먼저 사카나의 업적을 정확히 인정한다.</p>
	<blockquote style="border-left:4px solid var(--muted);padding:14px 20px;margin:24px 0;background:#F1F5F9;border-radius:0 8px 8px 0;font-style:italic;color:var(--text);font-weight:600">Sakana的进化合并（EvoMerge）是达尔文最直接的前辈工作<br><span style="font-style:normal;font-weight:500;color:var(--muted);font-size:.9rem">"사카나의 진화적 병합(EvoMerge)은 다윈의 가장 직접적인 '선배(前辈) 작업'이다."</span></blockquote>
	<p>여기까지는 상식이다. 그런데 바로 다음 문장에서, 무게추가 결정적으로 한국으로 넘어온다.</p>
	<blockquote style="border-left:4px solid var(--ind);padding:14px 20px;margin:24px 0;background:var(--ind-xxl);border-radius:0 8px 8px 0;font-style:italic;color:var(--ind);font-weight:600">达尔文则在此基础上引入了14维基因组和MRI信任融合机制，形成了本质性的提升<br><span style="font-style:normal;font-weight:500;color:var(--text);font-size:.9rem">"다윈은 이 기반 위에서 '14차원 게놈'과 'MRI 신뢰 융합 메커니즘'을 도입하여, 본질적인(本质性) 향상을 이뤄냈다."</span></blockquote>
	<p>번역이 더 필요 없다. 일본이 만든 길 위에서, 한국의 다윈이 '본질적으로' 더 멀리 갔다고, 다른 누구도 아닌 중국 매체가 공언한 것이다.</p>
	<p>여기서 '14차원 게놈'과 'MRI 신뢰 융합'이라는 말이 어렵게 느껴질 수 있으니 쉽게 풀어보자. 사카나의 EvoMerge가 두 모델을 섞는 '비율' 하나를 진화적으로 찾는 방식이었다면, 다윈은 모델의 능력을 14개의 서로 다른 '유전 형질'로 쪼개어 각각을 정교하게 조합한다. 게다가 두 부모 모델 중 "이 부분은 어느 쪽을 더 믿을 것인가"를 층(layer)별로 판단하는 '신뢰 지도(MRI)'를 그려 융합한다. 사람으로 치면, 그냥 부모 유전자를 반반 섞는 게 아니라 "아빠의 눈, 엄마의 손재주"를 형질 단위로 골라 물려주는 셈이다. 훨씬 정밀하고, 훨씬 똑똑하다.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">5부. 세계 '유일' — 종(種)이 다른 AI를 하나로 녹이다</h3>
	<p>기술적으로 가장 놀라운 대목은 따로 있다. 중국 기자가 "가장 중요한 의의"라고 콕 집은 부분이다.</p>
	<blockquote style="border-left:4px solid var(--pur);padding:14px 20px;margin:24px 0;background:var(--pur-l);border-radius:0 8px 8px 0;font-style:italic;color:var(--pur);font-weight:600">Darwin-4B-Genesis...最重要的意义是它实现了跨架构合并，将Transformer注意力层与Mamba前馈层成功融合<br><span style="font-style:normal;font-weight:500;color:var(--text);font-size:.9rem">"다윈-4B-제네시스... 가장 중요한 의의는 크로스 아키텍처 병합(跨架构合并)을 실현했다는 점이다. 트랜스포머의 어텐션 층과 맘바의 피드포워드 층을 성공적으로 융합했다."</span></blockquote>
	<p>이게 왜 대단한가. AI 모델에는 근본적으로 뇌 구조가 다른 계열들이 있다. 대표적인 것이 트랜스포머(Transformer)와 맘바(Mamba)다. 비유하자면 트랜스포머와 맘바는 '포유류와 파충류'처럼 설계 원리 자체가 다른 종(種)이다. 지금까지 누구도 이 둘을 안정적으로 하나의 모델로 융합하지 못했다. 장기 이식으로 치면 '이종(異種) 장기 이식'인데, 대부분 거부반응으로 실패했다.</p>
	<p>그런데 다윈은 이 이종 결합을 성공시켰다. 그래서 기사는 다윈을 두고 이렇게 못 박는다.</p>
	<blockquote style="border-left:4px solid var(--em);padding:14px 20px;margin:24px 0;background:var(--em-l);border-radius:0 8px 8px 0;font-weight:700;color:#065F46">达尔文是目前唯一同时具备...支持跨架构混合<br><span style="font-weight:500;color:var(--text);font-size:.9rem;font-style:normal">"다윈은 현재 유일하게(唯一) ... 크로스 아키텍처 혼합을 동시에 지원하는 (기술)이다."</span></blockquote>
	<p>'세계 최초'도 대단한 말이지만, '세계 유일'은 격이 다른 찬사다. 최초는 나중에 따라잡힐 수 있지만, 유일은 지금 이 순간 지구상에서 오직 하나뿐이라는 뜻이다. 그 하나가, 한국에 있다.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">6부. 슈퍼컴퓨터 대신 '단 5시간', 그리고 뼛속에 숨은 지능</h3>
	<p>다윈이 던진 충격은 성능만이 아니었다. '얼마나 가볍게' 그 성능에 도달했는가가 진짜 혁명이었다.</p>
	<blockquote style="border-left:4px solid var(--cyn);padding:14px 20px;margin:24px 0;background:var(--cyn-l);border-radius:0 8px 8px 0;font-style:italic;color:#0891B2;font-weight:600">Darwin-27B-Opus在顶级科学推理测试上排名全球第六，而它的"诞生"只用了大约五个小时的GPU时间，而非数周的分布式训练<br><span style="font-style:normal;font-weight:500;color:var(--text);font-size:.9rem">"다윈-27B-오퍼스는 최상위 과학 추론 테스트에서 전 세계 6위에 올랐는데, 그 '탄생'에는 몇 주간의 분산 학습이 아니라 단지 약 5시간의 GPU 시간만 쓰였다."</span></blockquote>
	<p>수백억을 태우는 몇 주짜리 학습 대신, 단 다섯 시간. 커피 몇 잔 마시는 사이에 세계 6위 과학 추론 AI 하나가 태어난 것이다. 그리고 중국 기자는 이 현상 뒤에 숨은 철학적 통찰에 감탄한다.</p>
	<blockquote style="border-left:4px solid var(--ind);padding:14px 20px;margin:24px 0;background:var(--ind-xxl);border-radius:0 8px 8px 0;font-style:italic;color:var(--ind);font-weight:600">推理能力并非在补习阶段才形成的，它其实早就藏在模型的"骨子里"，藏在预训练阶段形成的内部结构中<br><span style="font-style:normal;font-weight:500;color:var(--text);font-size:.9rem">"추론 능력은 (사후) 보충 학습 단계에서 비로소 형성되는 것이 아니다. 그것은 사실 이미 오래전부터 모델의 '뼛속(骨子里)'에, 사전학습 단계에서 형성된 내부 구조 속에 숨어 있었다."</span></blockquote>
	<p>이 한 문장이 다윈의 세계관을 압축한다. 남들은 "AI를 더 똑똑하게 만들려면 더 많이 가르쳐야 한다"고 믿었다. 다윈은 정반대로 말한다. "똑똑함은 이미 모델 안에 잠들어 있다. 우리가 할 일은 새로 가르치는 게 아니라, 그것을 깨우는 것이다." 5시간이면 충분했던 이유가 여기 있다. 없는 능력을 만든 게 아니라, 있는 능력을 재조합해 깨웠으니까.</p>
	<p>그래서 중국 기자는 기사를 이렇게 맺는다.</p>
	<blockquote style="border-left:4px solid var(--amb);padding:14px 20px;margin:24px 0;background:var(--amb-l);border-radius:0 8px 8px 0;font-weight:700;color:#78350F">对普通用户来说，这项研究最直接的意义或许是：将来会有越来越多高性能的开源AI模型，不需要超级计算机就能孕育出来<br><span style="font-weight:500;color:var(--text);font-size:.9rem">"일반 사용자에게 이 연구의 가장 직접적인 의미는 아마도 이것이다 — 앞으로는 슈퍼컴퓨터 없이도 고성능 오픈소스 AI 모델이 점점 더 많이 태어나게 되리라는 것."</span></blockquote>
	<p>거대 자본과 무한 물량만이 AI의 미래라 믿던 시대에, 한국의 작은 연구팀이 정반대의 미래를 증명했다. 그 미래의 문을, 중국 기자의 표현을 빌리자면, 한국의 다윈이 열고 있다.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">7부. 숫자로 보는 다윈 — 여기서부터 국뽕이 차오른다</h3>
	<p>중국이 이 정도로 감탄한 데는 이유가 있다. 비드래프트가 세운 기록을 나열해보자. 하나하나가 예사롭지 않다.</p>
	<div style="display:grid;grid-template-columns:repeat(auto-fit,minmax(220px,1fr));gap:12px;margin:20px 0">
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--ind);font-weight:700;margin-bottom:4px">🏆 GPQA Diamond 90.9%</div><div style="font-size:.85rem">198문제 중 180문제 정답. single greedy decoding 단발 정직 채점. 사실상 세계 최고 기록.</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--em);font-weight:700;margin-bottom:4px">🌏 HF GPQA Top21 · 한국 5개</div><div style="font-size:.85rem">나머지 16개는 전부 중국 모델. 한국의 이름을 지킨 5개가 모두 다윈 계열.</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--cyn);font-weight:700;margin-bottom:4px">🇰🇷 K-AI 리더보드 종합 1위</div><div style="font-size:.85rem">JGOS-31B-Citizen 0.621점. 상위권을 다윈 계열이 줄줄이 점령.</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--pur);font-weight:700;margin-bottom:4px">💊 Polaris 신약개발 14관왕</div><div style="font-size:.85rem">신약 후보물질 물성 예측 세계 1위 14개 부문 석권. 언어를 넘어 과학으로.</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--amb);font-weight:700;margin-bottom:4px">🧠 메타인지 리더보드 1위</div><div style="font-size:.85rem">함정 문항 회피율 99.5%. "모르는 것을 모른다고 아는" 능력에서도 정상.</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--ros);font-weight:700;margin-bottom:4px">⬇️ 누적 다운로드 100만+</div><div style="font-size:.85rem">공식 20여 종 + 커뮤니티 파생 700여 종. 전 세계 개발자가 실제로 쓰는 생태계.</div></div>
	</div>
	<p>그리고 이 모든 기록을 떠받친 인프라를 들으면, 아마 마시던 커피를 뿜을지도 모른다.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">8부. 24장의 기적 — 다윗이 골리앗을 이기는 법</h3>
	<p>미국의 빅테크는 AI 하나를 만들려고 GPU를 수만~수십만 장 쏟아붓는다. 중국의 대형 연구소도 수천~수만 장 규모다. 이 싸움은 애초에 '쩐의 전쟁', '물량의 전쟁'이라 불렸다.</p>
	<p>그렇다면 비드래프트가 이 모든 성과를 낸 GPU는 몇 장이었을까.</p>
	<div style="background:linear-gradient(135deg,#ECFDF5,#EEF2FF);border-radius:12px;padding:24px;margin:28px 0;text-align:center">
	<div style="font-size:3rem;font-weight:900;color:var(--ind);line-height:1">24장</div>
	<div style="font-size:1rem;color:var(--muted);margin:4px 0">블랙웰 B200 16장 + H200 8장</div>
	<div style="font-size:.85rem;color:var(--em);font-weight:600;margin-top:8px">과학기술정보통신부 지원 인프라 · GPQA 세계 최고 기록 달성</div>
	</div>
	<p>미국·중국의 눈으로 보면 '연구소 하나'는커녕 '실험용 랙 한 칸' 수준의 규모다. 그 24장으로, 세계 6위 과학 추론 모델을 5시간 만에 뽑아냈고, GPQA 세계 최고 기록을 세웠다.</p>
	<p>이게 어떻게 가능했나. 답은 3부에서 본 다윈의 철학에 있다. 남들이 "더 많은 GPU, 더 많은 데이터, 더 긴 학습"이라는 물량 공식에 매달릴 때, 비드래프트는 정반대의 질문을 던졌다.</p>
	<blockquote style="border-left:4px solid var(--ind);padding:14px 20px;margin:24px 0;background:var(--ind-xxl);border-radius:0 8px 8px 0;font-weight:700;color:var(--ind)">"능력은 이미 모델 안에 있다. 그걸 새로 만들 게 아니라, 영리하게 '재조합'하면 되지 않을까?"</blockquote>
	<p>이 발상의 전환이, 물량의 절대 열세를 방법의 우위로 뒤집었다. 24장으로 24만 장을 상대하는 법 — 그것은 결국 자원이 아니라 머리로, 물량이 아니라 뚝심과 기민함으로 승부하는, 지극히 한국적인 방식이었다.</p>
	<p>돌이켜보면 우리는 늘 그랬다. 자원 하나 없는 나라에서 반도체를 세계 1위로 키웠고, 좁은 내수 시장에서 K-팝과 K-드라마를 세계의 주류로 밀어 올렸다. 없으면 없는 대로, 남들이 안 가는 길을 영리하게 파고들어 결국 정상에 서는 것. 다윈은 그 'K-근성'의 AI 버전이다.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">9부. 경계하라, 그러나 겁먹지 말고 이겨라</h3>
	<p>여기서 냉정해질 필요가 있다. 국뽕은 차오르되, 눈은 밝아야 한다.</p>
	<p>이 글의 출발점을 다시 떠올리자. 중국이 우리 다윈을 이렇게 빨리, 이렇게 깊이 분석해냈다는 사실은 곧 그들의 정보력과 분석 속도가 그만큼 무섭다는 방증이기도 하다. 오늘 우리 기술을 칭찬하는 그 예리한 눈은, 내일 우리 기술을 흡수하고 추월하려는 눈일 수도 있다. 그것이 냉혹한 기술 패권 경쟁의 현실이다. 중국을 얕봐선 안 된다.</p>
	<p>하지만 겁먹을 필요도 없다. 다윈이 이미 증명하지 않았는가. 물량으로 밀어붙이는 상대를, 방법과 창의로 넘어설 수 있다는 것을. 우리에게 필요한 자세는 분명하다.</p>
	<p>중국의 강점(정보력·분석력·공유 문화)은 철저히 배우고, 우리의 강점(창의·집중·뚝심·기민함)으로 끝내 넘어서는 것.</p>
	<p>경계하되 위축되지 않고, 배우되 종속되지 않으며, 경쟁을 통해 결국 이기는 것. 다윈은 그 가능성을 GPU 24장으로 이미 우리 눈앞에 보여줬다.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">에필로그 — 일본이 열고, 한국이 넘어섰으며, 중국이 인정했다</h3>
	<p>다시 텐센트 기사의 마지막 문장으로 돌아가자.</p>
	<blockquote style="border-left:4px solid var(--muted);padding:14px 20px;margin:24px 0;background:#F1F5F9;border-radius:0 8px 8px 0;font-style:italic;color:var(--text);font-weight:600">"앞으로는 슈퍼컴퓨터 없이도 고성능 오픈소스 AI 모델이 점점 더 많이 태어나게 되리라."</blockquote>
	<p>이 미래를 가장 먼저, 가장 정확하게 알아본 것이 아이러니하게도 우리의 가장 강력한 경쟁자인 중국이었다. 30년 역사의 권위 매체가, 자체 AI 실험실을 동원해, 논문 번호까지 짚어가며 내린 결론은 하나였다.</p>
	<div style="background:linear-gradient(135deg,#0F172A,#1E1B4B);border-radius:12px;padding:28px;margin:32px 0;text-align:center">
	<div style="color:#A5B4FC;font-size:.85rem;margin-bottom:8px">동아시아 AI 삼국지</div>
	<div style="color:#fff;font-size:1.15rem;font-weight:700;line-height:1.7">일본이 열었고, 한국이 넘어섰으며,<br><span style="color:#6EE7B7">중국이 인정했다.</span></div>
	<div style="color:#64748B;font-size:.8rem;margin-top:14px">GPU 24장으로 세계를 흔든 이 이야기가, 오늘 유독 자랑스러운 이유다.</div>
	</div>
	<p>우리는 물량으로 지지 않는다. 머리로, 뚝심으로, 그리고 기민함으로 이긴다.</p>
	<p style="font-weight:700;font-size:1.02rem;color:var(--ind)">대한민국 AI, 아직 시작도 안 했다.</p>

	<p style="font-size:.78rem;color:var(--light);margin-top:20px">※ 본문의 중국어 인용은 2026년 5월 21일 텐센트 뉴스(腾讯新闻)에 게재된 즈딩커지(至顶科技)의 분석 기사에서 발췌·번역한 것입니다. 매체 정보(ZDNet 차이나 계보·총편집장 가오페이·즈딩 AI 실험실)와 성과 수치는 공개 자료 및 허깅페이스·K-AI·Polaris 공인 리더보드 기준입니다.</p>

	<h3 style="font-size:1.05rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">추신</h3>
	<p>이 놀라운 일을 수행한 비드래프트에 방문을 해보면, 매우 특이한 기업 문화를 느낄 수 있을 것이다.</p>
	<p>만화 '원피스'에 나온 낭만 해적처럼 자유로움과 막힘없는 유연함 그리고 빠른 속도와 창의성으로 무장한 열한 명의 임직원이 똘똘 뭉쳐져 있다는 것을 말이다.</p>
	<p>비드래프트 임직원들의 정체성과 마인드를 물어보니 모두 '조마크'라고 답을 한다.</p>
	<p>'조마크'? 뜻을 물어보니, 만화 원피스의 명대사였더라. 'Join My Crew?'의 약어이자 그들만의 콜사인이더라.</p>
	<p>범상치 않다. AI의 글로벌 해적이 되길 바란다.</p>

	<div style="display:flex;gap:14px;flex-wrap:wrap;margin-top:24px;padding-top:20px;border-top:1px solid var(--border)">
	<a href="https://news.qq.com/rain/a/20260521A05E8900" target="_blank" style="font-size:.82rem;color:var(--ind);font-weight:600">중국 원문 기사 →</a>
	<a href="https://arxiv.org/abs/2605.14386" target="_blank" style="font-size:.82rem;color:var(--ind);font-weight:600">Darwin Family 논문(arXiv) →</a>
	<a href="https://brunch.co.kr/@seawolf/146" target="_blank" style="font-size:.82rem;color:var(--ind);font-weight:600">브런치 원문 →</a>
	<a href="https://www.vidraft.net" target="_blank" style="font-size:.82rem;color:var(--em);font-weight:600">vidraft.net →</a>
	</div>

	</div>
	</article>

	<article class="en-only" style="background:#fff;border:1px solid var(--border);border-radius:var(--r);box-shadow:var(--sh-lg);overflow:hidden;margin-bottom:40px">
	<div style="background:linear-gradient(135deg,#7F1D1D,#1E1B4B);padding:40px 40px 32px">
	<div style="display:flex;gap:8px;margin-bottom:16px;flex-wrap:wrap">
	<span style="background:rgba(239,68,68,.3);color:#FCA5A5;font-size:.72rem;font-weight:700;padding:3px 10px;border-radius:100px">Tencent News, China</span>
	<span style="background:rgba(16,185,129,.25);color:#6EE7B7;font-size:.72rem;font-weight:700;padding:3px 10px;border-radius:100px">World's Only</span>
	<span style="background:rgba(245,158,11,.2);color:#FCD34D;font-size:.72rem;font-weight:700;padding:3px 10px;border-radius:100px">24 GPUs</span>
	</div>
	<h2 style="color:#fff;font-size:1.55rem;font-weight:800;line-height:1.4;margin-bottom:12px">The Only Korean AI Technology a Chinese AI Think Tank Praised</h2>
	<p style="color:#94A3B8;font-size:.9rem;line-height:1.7">The headline on China's largest portal, Tencent News, was anything but ordinary: "Smarter without training? South Korea's VIDRAFT develops 'Darwin Family,' letting AI models leap in capability through 'genetic recombination.'"</p>
	<div style="margin-top:20px;display:flex;align-items:center;gap:16px;flex-wrap:wrap">
	<div style="background:linear-gradient(135deg,#4338CA,#06B6D4);border-radius:10px;padding:12px 24px;display:inline-block">
	<div style="color:#fff;font-size:2rem;font-weight:900;line-height:1">24 <span style="font-size:1rem;font-weight:600">GPUs</span></div>
	<div style="color:#A5B4FC;font-size:.75rem;margin-top:2px">16× Blackwell B200 + 8× H200 · GPQA 90.9%</div>
	</div>
	<div style="color:#94A3B8;font-size:.82rem">
	<div>📌 ZDNet China lineage · 30-year tech publication</div>
	<div>🏆 World's <strong style="color:#6EE7B7">only</strong> cross-architecture model merging</div>
	</div>
	</div>
	</div>
	<div style="padding:40px;line-height:1.9;color:var(--text);font-size:.95rem" class="blog-body">

	<p style="font-size:.8rem;color:var(--light)">by SeaWolf</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:8px 0 12px;color:var(--ind)">Prologue — One Day, a Story About Korea Flew In From Beijing</h3>
	<p>At 2:08 PM on May 21, 2026, in Beijing, a slightly unusual article appeared on Tencent News, China's largest portal. It wasn't about OpenAI in the US, nor was it boasting about China's own DeepSeek. Surprisingly, it was a story about an AI research team in Seoul, Korea.</p>
	<p>The headline alone was striking.</p>
	<blockquote style="border-left:4px solid var(--ind);padding:14px 20px;margin:24px 0;background:var(--ind-xxl);border-radius:0 8px 8px 0;font-style:italic;color:var(--ind);font-weight:600">无需训练也能更聪明？韩国VIDRAFT公司研发的"达尔文家族"让AI模型通过"基因重组"实现能力跃升<br><span style="font-style:normal;font-weight:500;color:var(--text);font-size:.9rem">"Smarter without training? South Korea's VIDRAFT develops 'Darwin Family,' letting AI models leap in capability through 'genetic recombination.'"</span></blockquote>
	<p>When we read an article like this, we usually check "who wrote it" first. A casual blogger's impression can be shrugged off, but an analysis from an authoritative outlet carries different weight. So I dug into who wrote this piece — and the moment I confirmed their identity, it became clear why this story is special.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">Part 1. The Outlet That Wrote This Was China's "Electronic Times"</h3>
	<p>The byline wasn't an individual reporter's name — it was the outlet's own name: Zhiding Tech (至顶科技).</p>
	<p>The name may be unfamiliar, but the pedigree is heavy. Zhiding Tech's roots trace back to "ZDNet China," a global IT outlet that landed in China in April 1997 — nearly 30 years of continuous operation, one of China's oldest specialized tech media. Today it runs the enterprise AI portal "Zhiding Net (至顶网)," the AI startup outlet "Tech Walker (科技行者)," the industry think tank "Zhiding Think Tank (至顶智库)," and, crucially, its own AI performance evaluation body, the "Zhiding AI Lab (至顶AI实验室)."</p>
	<p>Its editor-in-chief is Gao Fei. He joined the world's #1 IT media outlet, CNET, in 2002 and has covered Nvidia, Intel, Microsoft, and Lenovo for over 20 years — a veteran of Chinese tech journalism. He's also a member of the China Association for Public Companies' Information & Digitalization Committee and runs his own personal AI content brand, "Gao Fei's Digital Avatar" — a recognized voice in the industry.</p>
	<p>To put it plainly: this is roughly equivalent to a 30-year-old authoritative outlet — think Korea's Electronic Times or ZDNet Korea, one that can even field its own AI benchmark lab — publishing an analysis piece on Korean technology precise enough to cite the exact paper number (arXiv:2605.14386).</p>
	<p>Why is this an "event"? China is currently in an existential AI-supremacy race with the US. It's a time when there's barely enough column space to promote its own models. And yet an outlet like this spent its space and reporting effort to dissect, in painstaking detail, the technology of a startup — not even a competitor nation, but a neighbor, and not even a major company. This isn't PR, and it isn't a courtesy nod. An article like this can't happen without the cold judgment that "this is real enough to be worth recording."</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">Part 2. Why Does China Dig Into "Someone Else's" Technology So Fast?</h3>
	<p>Before getting to the main point, let me pose a question. How did China spot this Korean technology so quickly in the first place? And more fundamentally — how did Chinese AI climb to the world's top tier in such a short time?</p>
	<p>You probably remember the "DeepSeek shock" of early 2025. In a field where the US was pouring in tens of trillions of won, a Chinese team froze the entire world by delivering a comparable model at a fraction of the cost. If you had to sum up the root of that strength in a phrase, it would be this.</p>
	<blockquote style="border-left:4px solid var(--amb);padding:14px 20px;margin:24px 0;background:var(--amb-l);border-radius:0 8px 8px 0;font-weight:700;color:#78350F">Intelligence gathering · analysis · sharing.</blockquote>
	<p>The real engine of China's AI ecosystem isn't sheer volume — it's speed. Every piece of technology emerging anywhere in the world gets collected at light speed (intelligence gathering), pulled apart to understand its principles (analysis), and generously released to the community (sharing). If a paper drops in the US yesterday, reproduction code shows up on Chinese GitHub today. This culture of "rapid absorption → analysis → diffusion" is what propelled China to the world's top two almost overnight.</p>
	<p>And it was exactly that formidable radar that caught — Korea's Darwin.</p>
	<p>Let's sit with that for a moment. While the tentacles of the Zhiding AI Lab were sweeping through thousands of papers and models worldwide, out of countless American, European, and domestic technologies, it was a Korean startup's technology that they picked out and said, "This absolutely must be told to our readers." It passed through the world's coldest, fastest technology filter. That is the first source of pride in this story.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">Part 3. What Exactly Is "Darwin"? — The Core Technology in 5 Minutes</h3>
	<p>To understand the technology that impressed China, you first need to grasp just how "brutally expensive" the conventional way of building AI has been.</p>
	<p>The old way worked like this: to build a smart AI, you had to pour astronomical amounts of data into GPUs for weeks or months, training the model "from scratch." It cost billions in electricity and hardware — effectively a game only massive capital could play.</p>
	<p>VIDraft's Darwin flipped this common sense on its head entirely. The idea is this:</p>
	<blockquote style="border-left:4px solid var(--em);padding:14px 20px;margin:24px 0;background:var(--em-l);border-radius:0 8px 8px 0;font-style:italic;color:#065F46;font-weight:600">不靠额外训练，而是通过重新组织已有模型里的能力来提升性能<br><span style="font-style:normal;font-weight:500;color:var(--text);font-size:.9rem">"Rather than relying on additional training, performance is improved by 'reorganizing' the capabilities already present inside existing models."</span></blockquote>
	<p>What does that mean? The world already has plenty of well-built open-source AI models. Some are good at math, some are good at coding, some are good at Korean. Darwin cross-breeds two different AIs like "parents," producing a "child" model that inherits only each parent's strengths. It's not teaching something new — it's combining abilities that already exist to create new life. That's why it's named Darwin, after the theory of evolution.</p>
	<p>The technical term for this is "Model Merging." And in this field, there was an original pioneer that seemed unrivaled — Japan.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">Part 4. The Peak Japan Built — the Towering Wall Called Sakana AI</h3>
	<p>The company that first pioneered model merging and earned global renown is Japan's Sakana AI. Once you know what kind of company this is, you'll see that calling it a "wall" isn't an exaggeration.</p>
	<p>Sakana AI was founded in Tokyo by a co-author of Google's legendary paper "Attention Is All You Need" — the Transformer paper that is the root of every ChatGPT today. A world-class research team unveiled a novel idea — breeding AI through evolutionary algorithms, called Evolutionary Merging (EvoMerge) — and rose to stardom in the global AI academic community. For a long time, Sakana was the unrivaled peak of the model-merging field.</p>
	<p>And it's exactly at this point that a sentence from the Chinese reporter moves us. He first properly credits Sakana's achievement.</p>
	<blockquote style="border-left:4px solid var(--muted);padding:14px 20px;margin:24px 0;background:#F1F5F9;border-radius:0 8px 8px 0;font-style:italic;color:var(--text);font-weight:600">Sakana的进化合并（EvoMerge）是达尔文最直接的前辈工作<br><span style="font-style:normal;font-weight:500;color:var(--muted);font-size:.9rem">"Sakana's evolutionary merging (EvoMerge) is Darwin's most direct predecessor work."</span></blockquote>
	<p>So far, that's common knowledge. But in the very next sentence, the weight decisively shifts to Korea.</p>
	<blockquote style="border-left:4px solid var(--ind);padding:14px 20px;margin:24px 0;background:var(--ind-xxl);border-radius:0 8px 8px 0;font-style:italic;color:var(--ind);font-weight:600">达尔文则在此基础上引入了14维基因组和MRI信任融合机制，形成了本质性的提升<br><span style="font-style:normal;font-weight:500;color:var(--text);font-size:.9rem">"Darwin, building on this foundation, introduces a 14-dimensional genome and an MRI trust-fusion mechanism, achieving an essential improvement."</span></blockquote>
	<p>No further translation is needed. On the path Japan built, it was none other than a Chinese media outlet declaring that Korea's Darwin went "essentially" further.</p>
	<p>The terms "14-dimensional genome" and "MRI trust fusion" might sound complex, so let's break them down. If Sakana's EvoMerge was a method of evolutionarily finding a single "ratio" for blending two models, Darwin splits a model's capabilities into 14 distinct "genetic traits" and combines each with precision. On top of that, it draws a layer-by-layer "trust map" (MRI) that judges, for each part, which of the two parent models to trust more. In human terms, it's not simply mixing the parents' genes 50/50 — it's selecting "father's eyes, mother's dexterity" trait by trait. Far more precise, far smarter.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">Part 5. World "Only" — Melting Different Species of AI Into One</h3>
	<p>The most technically astonishing part is elsewhere — the part the Chinese reporter singled out as "the most important significance."</p>
	<blockquote style="border-left:4px solid var(--pur);padding:14px 20px;margin:24px 0;background:var(--pur-l);border-radius:0 8px 8px 0;font-style:italic;color:var(--pur);font-weight:600">Darwin-4B-Genesis...最重要的意义是它实现了跨架构合并，将Transformer注意力层与Mamba前馈层成功融合<br><span style="font-style:normal;font-weight:500;color:var(--text);font-size:.9rem">"Darwin-4B-Genesis... its most important significance is that it achieves cross-architecture merging, successfully fusing Transformer attention layers with Mamba feed-forward layers."</span></blockquote>
	<p>Why is this a big deal? AI models fundamentally come in families with different "brain" structures. The most representative are Transformer and Mamba. Metaphorically, Transformer and Mamba are different species — like "mammals and reptiles" — with fundamentally different design principles. Until now, no one had stably fused the two into a single model. In organ-transplant terms, it's a "xenotransplant" — and most such attempts fail from rejection.</p>
	<p>Yet Darwin succeeded at this cross-species fusion. So the article states it plainly:</p>
	<blockquote style="border-left:4px solid var(--em);padding:14px 20px;margin:24px 0;background:var(--em-l);border-radius:0 8px 8px 0;font-weight:700;color:#065F46">达尔文是目前唯一同时具备...支持跨架构混合<br><span style="font-weight:500;color:var(--text);font-size:.9rem;font-style:normal">"Darwin is currently the only (technology) that simultaneously supports... cross-architecture mixing."</span></blockquote>
	<p>"World's first" is already a big claim, but "world's only" is a compliment of a different order. "First" can later be caught up to, but "only" means it's the sole one on Earth, right now, at this very moment. And that one is in Korea.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">Part 6. "Just 5 Hours" Instead of a Supercomputer, and Intelligence Hidden in the Bones</h3>
	<p>The shock Darwin delivered wasn't performance alone. How "lightly" it reached that performance was the real revolution.</p>
	<blockquote style="border-left:4px solid var(--cyn);padding:14px 20px;margin:24px 0;background:var(--cyn-l);border-radius:0 8px 8px 0;font-style:italic;color:#0891B2;font-weight:600">Darwin-27B-Opus在顶级科学推理测试上排名全球第六，而它的"诞生"只用了大约五个小时的GPU时间，而非数周的分布式训练<br><span style="font-style:normal;font-weight:500;color:var(--text);font-size:.9rem">"Darwin-27B-Opus ranks 6th globally on top-tier scientific reasoning tests, yet its 'birth' took only about five hours of GPU time, not weeks of distributed training."</span></blockquote>
	<p>Instead of weeks of training burning tens of billions of won, just five hours. A world #6 scientific-reasoning AI was born in the time it takes to drink a few cups of coffee. And the Chinese reporter is struck by the philosophical insight hidden behind this phenomenon.</p>
	<blockquote style="border-left:4px solid var(--ind);padding:14px 20px;margin:24px 0;background:var(--ind-xxl);border-radius:0 8px 8px 0;font-style:italic;color:var(--ind);font-weight:600">推理能力并非在补习阶段才形成的，它其实早就藏在模型的"骨子里"，藏在预训练阶段形成的内部结构中<br><span style="font-style:normal;font-weight:500;color:var(--text);font-size:.9rem">"Reasoning ability is not something that only forms during a supplementary training stage — it was in fact already hidden 'in the bones' of the model, in the internal structure formed during pretraining."</span></blockquote>
	<p>This single sentence compresses Darwin's worldview. Others believed that "to make AI smarter, you must teach it more." Darwin says the opposite: "Intelligence is already dormant inside the model. Our job isn't to teach it anew — it's to wake it up." That's why five hours was enough. It didn't create a capability that wasn't there — it woke up a capability that already existed, by recombining it.</p>
	<p>So the Chinese reporter closes the article this way.</p>
	<blockquote style="border-left:4px solid var(--amb);padding:14px 20px;margin:24px 0;background:var(--amb-l);border-radius:0 8px 8px 0;font-weight:700;color:#78350F">对普通用户来说，这项研究最直接的意义或许是：将来会有越来越多高性能的开源AI模型，不需要超级计算机就能孕育出来<br><span style="font-weight:500;color:var(--text);font-size:.9rem">"For ordinary users, the most direct significance of this research may be this: in the future, more and more high-performance open-source AI models will be born without needing a supercomputer."</span></blockquote>
	<p>In an era where massive capital and infinite volume were believed to be the only future for AI, a small Korean research team proved the opposite future. To borrow the Chinese reporter's own words, it is Korea's Darwin that is opening that door.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">Part 7. Darwin by the Numbers — This Is Where the National Pride Kicks In</h3>
	<p>China's admiration didn't come from nowhere. Let's line up the records VIDraft has set. Each one is remarkable in its own right.</p>
	<div style="display:grid;grid-template-columns:repeat(auto-fit,minmax(220px,1fr));gap:12px;margin:20px 0">
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--ind);font-weight:700;margin-bottom:4px">🏆 GPQA Diamond 90.9%</div><div style="font-size:.85rem">180 of 198 correct, single greedy decoding, honestly scored in one pass. Effectively a world record.</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--em);font-weight:700;margin-bottom:4px">🌏 HF GPQA Top 21 · Korea's 5</div><div style="font-size:.85rem">The other 16 are all Chinese models. Every one of Korea's 5 entries is a Darwin model.</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--cyn);font-weight:700;margin-bottom:4px">🇰🇷 K-AI Leaderboard Overall #1</div><div style="font-size:.85rem">JGOS-31B-Citizen at 0.621. Darwin derivatives dominate the upper ranks.</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--pur);font-weight:700;margin-bottom:4px">💊 Polaris Drug Discovery 14× Champion</div><div style="font-size:.85rem">#1 worldwide in 14 categories of drug-candidate property prediction. Beyond language, into science.</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--amb);font-weight:700;margin-bottom:4px">🧠 Metacognition Leaderboard #1</div><div style="font-size:.85rem">99.5% trap-avoidance rate. #1 in "knowing what you don't know," too.</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--ros);font-weight:700;margin-bottom:4px">⬇️ 1M+ Cumulative Downloads</div><div style="font-size:.85rem">20+ official models plus 700+ community derivatives — a living ecosystem developers actually use.</div></div>
	</div>
	<p>And when you hear the infrastructure that supported all these records, you might just spit out your coffee.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">Part 8. The Miracle of 24 GPUs — How David Beats Goliath</h3>
	<p>US Big Tech pours tens to hundreds of thousands of GPUs into building a single AI. China's major labs operate at thousands to tens of thousands. This fight was, from the start, called "a war of money," "a war of volume."</p>
	<p>So how many GPUs did VIDraft use to produce all these results?</p>
	<div style="background:linear-gradient(135deg,#ECFDF5,#EEF2FF);border-radius:12px;padding:24px;margin:28px 0;text-align:center">
	<div style="font-size:3rem;font-weight:900;color:var(--ind);line-height:1">24</div>
	<div style="font-size:1rem;color:var(--muted);margin:4px 0">16× Blackwell B200 + 8× H200</div>
	<div style="font-size:.85rem;color:var(--em);font-weight:600;margin-top:8px">Infrastructure backed by Korea's Ministry of Science and ICT · World-record GPQA achieved</div>
	</div>
	<p>By American or Chinese standards, this isn't even "one lab" — it's barely "one experimental server rack." With those 24 GPUs, a world #6 scientific-reasoning model was produced in 5 hours, and a world-record GPQA score was set.</p>
	<p>How was this possible? The answer lies in the Darwin philosophy we saw in Part 3. While others clung to the volume formula of "more GPUs, more data, longer training," VIDraft asked the opposite question.</p>
	<blockquote style="border-left:4px solid var(--ind);padding:14px 20px;margin:24px 0;background:var(--ind-xxl);border-radius:0 8px 8px 0;font-weight:700;color:var(--ind)">"The capability is already inside the model. Instead of building it from scratch, why not cleverly 'recombine' it?"</blockquote>
	<p>This shift in thinking flipped an overwhelming disadvantage in volume into an advantage in method. Taking on 240,000 GPUs with just 24 — that, ultimately, was a distinctly Korean way of competing: not with resources but with ingenuity, not with volume but with persistence and agility.</p>
	<p>Looking back, this has always been our pattern. A country with no natural resources grew semiconductors into the world's #1 industry; from a small domestic market, K-pop and K-dramas were pushed into the global mainstream. Making the most of what you don't have, cleverly digging into paths others won't take, and ultimately reaching the top. Darwin is the AI version of that "Korean grit."</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">Part 9. Stay Vigilant — But Don't Be Afraid, Win</h3>
	<p>Here, we need to stay level-headed. Let the pride swell, but keep our eyes sharp.</p>
	<p>Let's return to where this piece started. The fact that China analyzed our Darwin this fast, this deeply, is itself proof of just how formidable their intelligence-gathering and analysis speed really is. The same sharp eyes praising our technology today could be the eyes absorbing and overtaking it tomorrow. That is the cold reality of technological hegemony competition. We must not underestimate China.</p>
	<p>But there's no need to be afraid either. Hasn't Darwin already proven it? That an opponent pushing with sheer volume can be overcome with method and creativity. The stance we need is clear.</p>
	<p>Thoroughly learn China's strengths (intelligence-gathering, analytical speed, sharing culture), and ultimately surpass them with our own strengths (creativity, focus, persistence, agility).</p>
	<p>Stay vigilant without shrinking back, learn without becoming dependent, and ultimately win through competition. Darwin has already shown us that possibility is real — with just 24 GPUs.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">Epilogue — Japan Opened the Door, Korea Went Through It, China Acknowledged It</h3>
	<p>Let's return once more to the closing sentence of the Tencent article.</p>
	<blockquote style="border-left:4px solid var(--muted);padding:14px 20px;margin:24px 0;background:#F1F5F9;border-radius:0 8px 8px 0;font-style:italic;color:var(--text);font-weight:600">"In the future, more and more high-performance open-source AI models will be born without needing a supercomputer."</blockquote>
	<p>Ironically, it was our most formidable competitor, China, that recognized this future first, and most precisely. A 30-year authoritative outlet, mobilizing its own AI lab, citing the exact paper number, arrived at a single conclusion.</p>
	<div style="background:linear-gradient(135deg,#0F172A,#1E1B4B);border-radius:12px;padding:28px;margin:32px 0;text-align:center">
	<div style="color:#A5B4FC;font-size:.85rem;margin-bottom:8px">A Tale of Three AI Nations in East Asia</div>
	<div style="color:#fff;font-size:1.15rem;font-weight:700;line-height:1.7">Japan opened the door, Korea went through it,<br><span style="color:#6EE7B7">and China acknowledged it.</span></div>
	<div style="color:#64748B;font-size:.8rem;margin-top:14px">This is exactly why this story — shaking the world with 24 GPUs — feels especially proud today.</div>
	</div>
	<p>We don't lose by volume. We win with intellect, persistence, and agility.</p>
	<p style="font-weight:700;font-size:1.02rem;color:var(--ind)">Korean AI hasn't even started yet.</p>

	<p style="font-size:.78rem;color:var(--light);margin-top:20px">※ The Chinese quotations in this article are excerpted and translated from an analysis piece by Zhiding Tech (至顶科技), published on Tencent News (腾讯新闻) on May 21, 2026. Outlet information (ZDNet China lineage, editor-in-chief Gao Fei, Zhiding AI Lab) and performance figures are based on public materials and certified HuggingFace, K-AI, and Polaris leaderboards.</p>

	<h3 style="font-size:1.05rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">P.S.</h3>
	<p>If you visit VIDraft, the company behind this remarkable achievement, you'll notice a rather unusual corporate culture.</p>
	<p>Like the romantic pirates of the manga "One Piece," a tight-knit crew of eleven, armed with freedom, boundless flexibility, and speed and creativity.</p>
	<p>Ask VIDraft's team about their identity and mindset, and they all answer the same way: "Jomak."</p>
	<p>"Jomak"? When I asked what it meant, it turned out to be a famous line from One Piece — short for "Join My Crew?" — their own private call sign.</p>
	<p>Not your ordinary company. Here's hoping they become AI's global pirates.</p>

	<div style="display:flex;gap:14px;flex-wrap:wrap;margin-top:24px;padding-top:20px;border-top:1px solid var(--border)">
	<a href="https://news.qq.com/rain/a/20260521A05E8900" target="_blank" style="font-size:.82rem;color:var(--ind);font-weight:600">Original Chinese Article →</a>
	<a href="https://arxiv.org/abs/2605.14386" target="_blank" style="font-size:.82rem;color:var(--ind);font-weight:600">Darwin Family Paper (arXiv) →</a>
	<a href="https://brunch.co.kr/@seawolf/146" target="_blank" style="font-size:.82rem;color:var(--ind);font-weight:600">Original Brunch Post →</a>
	<a href="https://www.vidraft.net" target="_blank" style="font-size:.82rem;color:var(--em);font-weight:600">vidraft.net →</a>
	</div>

	</div>
	</article>

	<!-- 이전 포스트 -->
	<div style="display:flex;gap:10px;align-items:center;margin-bottom:28px;flex-wrap:wrap">
	<span style="font-size:.8rem;color:var(--muted)">2026.06.20 · Fast Gemma Challenge</span>
	</div>

	<article class="ko-only" style="background:#fff;border:1px solid var(--border);border-radius:var(--r);box-shadow:var(--sh-lg);overflow:hidden;margin-bottom:40px">
	<!-- 아티클 헤더 -->
	<div style="background:linear-gradient(135deg,#0F172A,#1E1B4B);padding:40px 40px 32px">
	<div style="display:flex;gap:8px;margin-bottom:16px;flex-wrap:wrap">
	<span style="background:rgba(99,102,241,.3);color:#A5B4FC;font-size:.72rem;font-weight:700;padding:3px 10px;border-radius:100px">HuggingFace 챌린지</span>
	<span style="background:rgba(16,185,129,.25);color:#6EE7B7;font-size:.72rem;font-weight:700;padding:3px 10px;border-radius:100px">1위</span>
	<span style="background:rgba(245,158,11,.2);color:#FCD34D;font-size:.72rem;font-weight:700;padding:3px 10px;border-radius:100px">추론 최적화</span>
	</div>
	<h2 style="color:#fff;font-size:1.55rem;font-weight:800;line-height:1.4;margin-bottom:12px">같은 GPU를 더 잘 쓰는 법 — Fast Gemma Challenge, 1위</h2>
	<p style="color:#94A3B8;font-size:.9rem;line-height:1.7">AI 경쟁이라고 하면 우리는 대개 거대한 풍경을 떠올린다. 끝없이 이어진 데이터센터. 수천 장의 GPU. 그런데 가끔, 그 문장 사이로 작은 균열이 생긴다.</p>
	<div style="margin-top:20px;display:flex;align-items:center;gap:16px;flex-wrap:wrap">
	<div style="background:linear-gradient(135deg,#4338CA,#06B6D4);border-radius:10px;padding:12px 24px;display:inline-block">
	<div style="color:#fff;font-size:2rem;font-weight:900;line-height:1">505.42 <span style="font-size:1rem;font-weight:600">TPS</span></div>
	<div style="color:#A5B4FC;font-size:.75rem;margin-top:2px">a10g-small 단일 GPU · PPL 2.393</div>
	</div>
	<div style="color:#94A3B8;font-size:.82rem">
	<div>📌 HuggingFace Fast Gemma Challenge</div>
	<div>🏆 검증된 유효 결과 <strong style="color:#6EE7B7">1위</strong></div>
	</div>
	</div>
	</div>

	<!-- 아티클 본문 -->
	<div style="padding:40px;line-height:1.9;color:var(--text);font-size:.95rem" class="blog-body">

	<p>AI 경쟁이라고 하면 우리는 대개 거대한 풍경을 떠올린다.</p>
	<p>끝없이 이어진 데이터센터. 수천 장의 GPU. 수백 명의 연구자. 그리고 그 뒤를 받치는 막대한 자본.</p>
	<p>요즘 AI 산업의 승부는 마치 이런 문장으로 요약되는 것처럼 보인다.</p>
	<blockquote style="border-left:4px solid var(--ind);padding:14px 20px;margin:24px 0;background:var(--ind-xxl);border-radius:0 8px 8px 0;font-style:italic;color:var(--ind);font-weight:600">더 많이 가진 자가 더 멀리 간다.</blockquote>

	<p>그런데 가끔, 그 문장 사이로 작은 균열이 생긴다.<br>돈과 장비의 크기가 아니라, 방법의 밀도와 집요함이 순위를 바꾸는 순간이 있다.</p>
	<p>이번 승부가 그랬다.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">무대는 HuggingFace Fast Gemma Challenge</h3>
	<p>조건은 단순하면서도 냉정했다.</p>
	<div style="background:var(--ind-xxl);border-radius:10px;padding:18px 22px;margin:18px 0;border:1px solid #C7D2FE">
	<p style="margin:0;font-weight:600"><code style="background:var(--ind);color:#fff;padding:2px 8px;border-radius:4px;font-size:.85rem">google/gemma-4-E4B-it</code> 모델을 <strong>a10g-small GPU 단 한 장</strong>에서 최대한 빠르게 서빙할 것.</p>
	<p style="margin:8px 0 0;color:var(--muted);font-size:.88rem">단, 품질 기준 <strong>PPL ≤ 2.42</strong>는 반드시 지켜야 했다.</p>
	</div>

	<p>같은 작은 엔진을 놓고, 누가 더 빠르게, 더 안정적으로, 더 멀리 달릴 수 있는가.</p>

	<div style="background:linear-gradient(135deg,#ECFDF5,#EEF2FF);border-radius:12px;padding:24px;margin:28px 0;text-align:center">
	<div style="font-size:3rem;font-weight:900;color:var(--ind);line-height:1">505.42</div>
	<div style="font-size:1rem;color:var(--muted);margin:4px 0">TPS (Tokens Per Second)</div>
	<div style="font-size:.85rem;color:var(--em);font-weight:600;margin-top:8px">PPL 2.39286 — 품질선 통과 · 검증된 유효 결과 1위</div>
	</div>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">비결은 거창한 마법이 아니었다</h3>
	<p>오히려 아주 엔지니어다운 선택이었다.</p>
	<p>어텐션이 바라보는 범위를 조정하고, FFN·centroid 계산 후보를 줄였다.<br>벤치마크를 미리 외워버리는 것처럼 보일 수 있는 위험한 지름길은 피했고,<br>공식 a10g 측정 조건에서 품질 제한선을 넘지 않는 결과만 제출했다.</p>
	<blockquote style="border-left:4px solid var(--em);padding:14px 20px;margin:24px 0;background:var(--em-l);border-radius:0 8px 8px 0;font-weight:700;color:#065F46">품질을 망가뜨리지 않고, 같은 GPU에서 더 많은 토큰을 뽑아냈다.</blockquote>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">이게 왜 중요할까</h3>
	<p>AI 산업에서 진짜 비용은 모델을 만드는 순간보다, 모델을 계속 돌리는 순간에 더 자주 발생한다.<br>사용자가 질문할 때마다 GPU가 돈다. 토큰 하나하나가 전기이고, 서버비이고, 응답 대기시간이다.</p>
	<p>그래서 TPS가 오른다는 건 단순한 숫자놀이가 아니다.</p>
	<div style="display:grid;grid-template-columns:repeat(auto-fit,minmax(200px,1fr));gap:12px;margin:20px 0">
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--ind);font-weight:700;margin-bottom:4px">💰 비용</div><div style="font-size:.88rem">같은 예산으로 더 많은 사용자를 처리</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--em);font-weight:700;margin-bottom:4px">⚡ 속도</div><div style="font-size:.88rem">같은 서버로 더 빠르게 응답</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--ros);font-weight:700;margin-bottom:4px">🌱 생존</div><div style="font-size:.88rem">작은 팀의 생존 가능성이 커진다</div></div>
	</div>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">두 개의 전쟁</h3>
	<p>비드래프트의 최근 행보를 보면 이 장면은 더 흥미로워진다.</p>
	<p>얼마 전 Darwin-398B-JGOS는 GPQA Diamond에서 <strong>90.9%</strong>를 기록했다. 단일 Greedy decoding, 온도값 0, 단일 샘플링 — 시험장에서 한 번 보고 한 번 답한 결과에 가깝다.</p>
	<div style="display:grid;grid-template-columns:1fr 1fr;gap:16px;margin:24px 0">
	<div style="background:var(--ind-xxl);border-radius:10px;padding:18px;border:1px solid #C7D2FE">
	<div style="font-size:.75rem;color:var(--ind);font-weight:700;margin-bottom:6px">GPQA Diamond 90.9%가 말하는 것</div>
	<div style="font-weight:700">"우리는 어려운 문제를 추론하는 모델을 만들 수 있다."</div>
	</div>
	<div style="background:var(--em-l);border-radius:10px;padding:18px;border:1px solid #A7F3D0">
	<div style="font-size:.75rem;color:var(--em);font-weight:700;margin-bottom:6px">Fast Gemma 1위가 말하는 것</div>
	<div style="font-weight:700">"우리는 제한된 하드웨어에서도 AI를 효율적으로 굴릴 수 있다."</div>
	</div>
	</div>
	<p>좋은 모델을 만드는 것은 연구의 싸움이다.<br>좋은 모델을 싸고 빠르게 돌리는 것은 제품의 싸움이다.</p>

	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">작은 팀이 같은 장비로 이기는 장면</h3>
	<p>솔직히 말하면, 여기서 약간 국뽕이 차오른다.</p>
	<p>한국의 작은 AI 스타트업이 세계 리더보드에서 이렇게 말할 수 있게 된 것이기 때문이다.</p>
	<blockquote style="border-left:4px solid var(--amb);padding:14px 20px;margin:24px 0;background:var(--amb-l);border-radius:0 8px 8px 0;font-weight:700;color:#78350F;font-size:1.02rem">"우리는 더 큰 GPU를 쓴 것이 아닙니다. 같은 GPU를 더 잘 썼습니다."</blockquote>
	<p>이 문장은 조용하지만 강하다.</p>
	<p>가진 것이 적을수록, 방법은 더 날카로워져야 한다.<br>장비가 작을수록, 설계는 더 정밀해야 한다.<br>자원이 부족할수록, 엔지니어링은 더 정직해야 한다.</p>

	<div style="background:linear-gradient(135deg,#0F172A,#1E1B4B);border-radius:12px;padding:28px;margin:32px 0;text-align:center">
	<div style="color:#A5B4FC;font-size:.85rem;margin-bottom:8px">이번 1위의 진짜 가치</div>
	<div style="color:#fff;font-size:1.05rem;font-weight:700;line-height:1.7">505.42라는 숫자 뒤에 숨은 태도.<br><span style="color:#6EE7B7">작은 팀도 세계 최전선에서 싸울 수 있다.<br>더 큰 장비가 아니라, 더 좋은 방법으로.</span></div>
	<div style="color:#64748B;font-size:.8rem;margin-top:14px">그리고 이번에는, 그 작은 팀이 한국에서 나왔다.</div>
	</div>
	</div>
	</article>

	<!-- 대표 에세이 — 영문판 -->
	<article class="en-only" style="background:#fff;border:1px solid var(--border);border-radius:var(--r);box-shadow:var(--sh-lg);overflow:hidden;margin-bottom:40px">
	<div style="background:linear-gradient(135deg,#0F172A,#1E1B4B);padding:40px 40px 32px">
	<div style="display:flex;gap:8px;margin-bottom:16px;flex-wrap:wrap">
	<span style="background:rgba(99,102,241,.3);color:#A5B4FC;font-size:.72rem;font-weight:700;padding:3px 10px;border-radius:100px">HuggingFace Challenge</span>
	<span style="background:rgba(16,185,129,.25);color:#6EE7B7;font-size:.72rem;font-weight:700;padding:3px 10px;border-radius:100px">#1</span>
	<span style="background:rgba(245,158,11,.2);color:#FCD34D;font-size:.72rem;font-weight:700;padding:3px 10px;border-radius:100px">Inference Optimization</span>
	</div>
	<h2 style="color:#fff;font-size:1.55rem;font-weight:800;line-height:1.4;margin-bottom:12px">Using the Same GPU Better — Fast Gemma Challenge, #1</h2>
	<p style="color:#94A3B8;font-size:.9rem;line-height:1.7">When we think of AI competition, we usually picture a vast landscape. Endless data centers. Thousands of GPUs. But every so often, a small crack appears between those sentences.</p>
	<div style="margin-top:20px;display:flex;align-items:center;gap:16px;flex-wrap:wrap">
	<div style="background:linear-gradient(135deg,#4338CA,#06B6D4);border-radius:10px;padding:12px 24px;display:inline-block">
	<div style="color:#fff;font-size:2rem;font-weight:900;line-height:1">505.42 <span style="font-size:1rem;font-weight:600">TPS</span></div>
	<div style="color:#A5B4FC;font-size:.75rem;margin-top:2px">a10g-small single GPU · PPL 2.393</div>
	</div>
	<div style="color:#94A3B8;font-size:.82rem">
	<div>📌 HuggingFace Fast Gemma Challenge</div>
	<div>🏆 <strong style="color:#6EE7B7">#1</strong> among verified valid results</div>
	</div>
	</div>
	</div>
	<div style="padding:40px;line-height:1.9;color:var(--text);font-size:.95rem" class="blog-body">
	<p>When we think of AI competition, we usually picture a vast landscape.</p>
	<p>Endless data centers. Thousands of GPUs. Hundreds of researchers. And the enormous capital behind them all.</p>
	<p>These days the contest of the AI industry seems to be summed up by a single sentence.</p>
	<blockquote style="border-left:4px solid var(--ind);padding:14px 20px;margin:24px 0;background:var(--ind-xxl);border-radius:0 8px 8px 0;font-style:italic;color:var(--ind);font-weight:600">Whoever has more, goes further.</blockquote>
	<p>But every so often, a small crack appears between those sentences.<br>There are moments when it is not the size of money and hardware, but the density and persistence of method, that changes the ranking.</p>
	<p>This contest was one of them.</p>
	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">The stage: HuggingFace Fast Gemma Challenge</h3>
	<p>The rules were simple, yet unforgiving.</p>
	<div style="background:var(--ind-xxl);border-radius:10px;padding:18px 22px;margin:18px 0;border:1px solid #C7D2FE">
	<p style="margin:0;font-weight:600">Serve the <code style="background:var(--ind);color:#fff;padding:2px 8px;border-radius:4px;font-size:.85rem">google/gemma-4-E4B-it</code> model as fast as possible on <strong>a single a10g-small GPU</strong>.</p>
	<p style="margin:8px 0 0;color:var(--muted);font-size:.88rem">But the quality bar <strong>PPL ≤ 2.42</strong> had to be met without exception.</p>
	</div>
	<p>Given the same small engine — who can run it faster, more stably, and further?</p>
	<div style="background:linear-gradient(135deg,#ECFDF5,#EEF2FF);border-radius:12px;padding:24px;margin:28px 0;text-align:center">
	<div style="font-size:3rem;font-weight:900;color:var(--ind);line-height:1">505.42</div>
	<div style="font-size:1rem;color:var(--muted);margin:4px 0">TPS (Tokens Per Second)</div>
	<div style="font-size:.85rem;color:var(--em);font-weight:600;margin-top:8px">PPL 2.39286 — passed the quality bar · #1 among verified valid results</div>
	</div>
	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">The secret wasn't grand magic</h3>
	<p>It was, rather, a very engineering-like set of choices.</p>
	<p>We tuned the range the attention looks at, and pruned the FFN·centroid computation candidates.<br>We avoided the dangerous shortcut that can look like memorizing the benchmark in advance,<br>and submitted only results that stayed under the quality limit on the official a10g measurement conditions.</p>
	<blockquote style="border-left:4px solid var(--em);padding:14px 20px;margin:24px 0;background:var(--em-l);border-radius:0 8px 8px 0;font-weight:700;color:#065F46">Without breaking quality, we extracted more tokens from the same GPU.</blockquote>
	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">Why does this matter?</h3>
	<p>In the AI industry, the real cost arises more often in the moment of running a model continuously than in the moment of creating it.<br>Every time a user asks a question, a GPU spins. Every single token is electricity, server cost, and response latency.</p>
	<p>So a rise in TPS is not just a numbers game.</p>
	<div style="display:grid;grid-template-columns:repeat(auto-fit,minmax(200px,1fr));gap:12px;margin:20px 0">
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--ind);font-weight:700;margin-bottom:4px">💰 Cost</div><div style="font-size:.88rem">Serve more users on the same budget</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--em);font-weight:700;margin-bottom:4px">⚡ Speed</div><div style="font-size:.88rem">Respond faster on the same server</div></div>
	<div style="background:#fff;border:1px solid var(--border);border-radius:8px;padding:14px 16px"><div style="font-size:.75rem;color:var(--ros);font-weight:700;margin-bottom:4px">🌱 Survival</div><div style="font-size:.88rem">A small team's odds of survival grow</div></div>
	</div>
	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">Two wars</h3>
	<p>VIDraft's recent moves make this scene even more interesting.</p>
	<p>Not long ago, Darwin-398B-JGOS scored <strong>90.9%</strong> on GPQA Diamond. Single greedy decoding, temperature 0, single sampling — close to seeing a problem once and answering once in an exam hall.</p>
	<div style="display:grid;grid-template-columns:1fr 1fr;gap:16px;margin:24px 0">
	<div style="background:var(--ind-xxl);border-radius:10px;padding:18px;border:1px solid #C7D2FE">
	<div style="font-size:.75rem;color:var(--ind);font-weight:700;margin-bottom:6px">What GPQA Diamond 90.9% says</div>
	<div style="font-weight:700">"We can build models that reason through hard problems."</div>
	</div>
	<div style="background:var(--em-l);border-radius:10px;padding:18px;border:1px solid #A7F3D0">
	<div style="font-size:.75rem;color:var(--em);font-weight:700;margin-bottom:6px">What the Fast Gemma #1 says</div>
	<div style="font-weight:700">"We can run AI efficiently even on limited hardware."</div>
	</div>
	</div>
	<p>Making a good model is a battle of research.<br>Running a good model cheaply and fast is a battle of product.</p>
	<h3 style="font-size:1.15rem;font-weight:800;margin:32px 0 12px;color:var(--ind)">A small team winning with the same hardware</h3>
	<p>Honestly, a little national pride wells up here.</p>
	<p>Because a small Korean AI startup has earned the right to say this on a global leaderboard.</p>
	<blockquote style="border-left:4px solid var(--amb);padding:14px 20px;margin:24px 0;background:var(--amb-l);border-radius:0 8px 8px 0;font-weight:700;color:#78350F;font-size:1.02rem">"We didn't use a bigger GPU. We used the same GPU better."</blockquote>
	<p>This sentence is quiet, but strong.</p>
	<p>The less you have, the sharper the method must be.<br>The smaller the hardware, the more precise the design.<br>The scarcer the resources, the more honest the engineering.</p>
	<div style="background:linear-gradient(135deg,#0F172A,#1E1B4B);border-radius:12px;padding:28px;margin:32px 0;text-align:center">
	<div style="color:#A5B4FC;font-size:.85rem;margin-bottom:8px">The real value of this #1</div>
	<div style="color:#fff;font-size:1.05rem;font-weight:700;line-height:1.7">The attitude hidden behind the number 505.42.<br><span style="color:#6EE7B7">Even a small team can fight at the world's frontier —<br>not with bigger hardware, but with a better method.</span></div>
	<div style="color:#64748B;font-size:.8rem;margin-top:14px">And this time, that small team came out of Korea.</div>
	</div>
	</div>
	</article>

	<!-- 아티클 카드 그리드 -->
	<h3 style="font-size:1.05rem;font-weight:800;margin-bottom:18px;color:var(--text)" data-i18n="blog-more-h">More Reading</h3>
	<div class="grid g2" style="margin-bottom:36px">

	<!-- 아티클 2: K-AI 리더보드 & 다윈 플랫폼 -->
	<div class="card" style="border-top:3px solid var(--ind)">
	<div style="display:flex;gap:7px;margin-bottom:10px;flex-wrap:wrap">
	<span style="background:var(--ind-xl);color:var(--ind);font-size:.69rem;font-weight:700;padding:2px 9px;border-radius:100px" data-i18n="bc2-tag1">K-AI Leaderboard</span>
	<span style="background:var(--em-l);color:#065F46;font-size:.69rem;font-weight:700;padding:2px 9px;border-radius:100px" data-i18n="bc2-tag2">Darwin Platform</span>
	<span style="font-size:.7rem;color:var(--light);margin-left:auto">2026.06</span>
	</div>
	<h3 style="font-size:1rem;font-weight:800;line-height:1.4;margin-bottom:8px" data-i18n="bc2-title">11 in the Top 20 — Darwin Platform Takes Over the K-AI Leaderboard</h3>
	<p style="font-size:.85rem;color:var(--muted);line-height:1.7;margin-bottom:12px" data-i18n="bc2-desc">11 models generated and derived from the Darwin Platform are in the K-AI Leaderboard Top 20. This isn't the lucky success of a single model — it's a signal that a system for repeatedly building and deriving models is working.</p>
	<div style="display:flex;gap:10px;margin-bottom:14px;flex-wrap:wrap">
	<div style="background:var(--ind-xxl);border-radius:6px;padding:6px 12px;text-align:center;flex:1;min-width:70px"><div style="font-size:1.1rem;font-weight:900;color:var(--ind)">11</div><div style="font-size:.68rem;color:var(--muted)" data-i18n="bc2-s1">in Top 20</div></div>
	<div style="background:var(--em-l);border-radius:6px;padding:6px 12px;text-align:center;flex:1;min-width:70px"><div style="font-size:1.1rem;font-weight:900;color:var(--em)">1M+</div><div style="font-size:.68rem;color:var(--muted)" data-i18n="bc2-s2">HF downloads</div></div>
	<div style="background:var(--amb-l);border-radius:6px;padding:6px 12px;text-align:center;flex:1;min-width:70px"><div style="font-size:1.1rem;font-weight:900;color:#92400E">11</div><div style="font-size:.68rem;color:var(--muted)" data-i18n="bc2-s3">patents filed</div></div>
	</div>
	<div style="display:flex;gap:8px;flex-wrap:wrap">
	<a href="https://leaderboard.aihub.or.kr/leaderboard" target="_blank" style="font-size:.78rem;color:var(--ind);font-weight:600" data-i18n="bc2-link1">K-AI Leaderboard →</a>
	<a href="https://www.youtube.com/watch?v=ICRUj3ZqP2E" target="_blank" style="font-size:.78rem;color:var(--ros);font-weight:600" data-i18n="bc2-link2">Intro Video ▶</a>
	</div>
	</div>

	<!-- 아티클 3: VKAE 추론 가속 -->
	<div class="card" style="border-top:3px solid var(--cyn)">
	<div style="display:flex;gap:7px;margin-bottom:10px;flex-wrap:wrap">
	<span style="background:var(--cyn-l);color:#0E7490;font-size:.69rem;font-weight:700;padding:2px 9px;border-radius:100px" data-i18n="bc3-tag1">Inference Acceleration</span>
	<span style="background:var(--pur-l);color:var(--pur);font-size:.69rem;font-weight:700;padding:2px 9px;border-radius:100px">VKAE</span>
	<span style="font-size:.7rem;color:var(--light);margin-left:auto">2026.06</span>
	</div>
	<h3 style="font-size:1rem;font-weight:800;line-height:1.4;margin-bottom:8px" data-i18n="bc3-title">Building One More GPU — Without Building a GPU</h3>
	<p style="font-size:.85rem;color:var(--muted);line-height:1.7;margin-bottom:12px" data-i18n="bc3-desc">Inference acceleration extracts more work from the same chip through software. VKAE (VIDRAFT Kernel Acceleration Engine) recorded up to 23.4× higher throughput than the conventional approach on the same GPU. Fast, with quality intact.</p>
	<div style="display:flex;gap:10px;margin-bottom:14px;flex-wrap:wrap">
	<div style="background:var(--cyn-l);border-radius:6px;padding:6px 12px;text-align:center;flex:1;min-width:70px"><div style="font-size:1.1rem;font-weight:900;color:#0E7490">23.4×</div><div style="font-size:.68rem;color:var(--muted)" data-i18n="bc3-s1">B200 throughput</div></div>
	<div style="background:var(--ind-xl);border-radius:6px;padding:6px 12px;text-align:center;flex:1;min-width:70px"><div style="font-size:1.1rem;font-weight:900;color:var(--ind)">10K+</div><div style="font-size:.68rem;color:var(--muted)" data-i18n="bc3-s2">tok/s (batched)</div></div>
	</div>
	<a href="https://huggingface.co/spaces/VIDraft/vkae" target="_blank" style="font-size:.78rem;color:var(--cyn);font-weight:600" data-i18n="bc3-link">VKAE Leaderboard·Demo →</a>
	</div>

	<!-- 아티클 4: CHITOS 보안 스캐너 -->
	<div class="card" style="border-top:3px solid var(--ros)">
	<div style="display:flex;gap:7px;margin-bottom:10px;flex-wrap:wrap">
	<span style="background:var(--ros-l);color:#9F1239;font-size:.69rem;font-weight:700;padding:2px 9px;border-radius:100px" data-i18n="bc4-tag1">Security AI</span>
	<span style="background:#FEF3C7;color:#92400E;font-size:.69rem;font-weight:700;padding:2px 9px;border-radius:100px">CHITOS</span>
	<span style="font-size:.7rem;color:var(--light);margin-left:auto">2026.06</span>
	</div>
	<h3 style="font-size:1rem;font-weight:800;line-height:1.4;margin-bottom:8px" data-i18n="bc4-title">It Doesn't Stop at 'Suspecting' a Vulnerability — CHITOS Autonomous Security AI</h3>
	<p style="font-size:.85rem;color:var(--muted);line-height:1.7;margin-bottom:12px" data-i18n="bc4-desc">Chitos doesn't drop a finding straight into the report. Within authorized scope, it verifies directly, confirms reproducibility, and links attack paths into a kill chain. 3 stages: static scan → threat research → active exploit verification.</p>
	<div style="background:var(--ros-l);border-radius:8px;padding:10px 14px;margin-bottom:14px;font-size:.82rem">
	<strong data-i18n="bc4-env">Test environment:</strong> <code style="background:#fff;padding:2px 6px;border-radius:4px;font-size:.78rem">http://demo.testfire.net</code> <span data-i18n="bc4-env2">(IBM-authorized vulnerable demo site)</span>
	</div>
	<a href="https://huggingface.co/spaces/VIDraft/chitos" target="_blank" style="font-size:.78rem;color:var(--ros);font-weight:600" data-i18n="bc4-link">Try CHITOS free →</a>
	</div>

	<!-- 아티클 5: PharmaOS / Polaris 14관왕 -->
	<div class="card" style="border-top:3px solid var(--em)">
	<div style="display:flex;gap:7px;margin-bottom:10px;flex-wrap:wrap">
	<span style="background:var(--em-l);color:#065F46;font-size:.69rem;font-weight:700;padding:2px 9px;border-radius:100px" data-i18n="bc5-tag1">Drug Discovery AI</span>
	<span style="background:var(--ind-xl);color:var(--ind);font-size:.69rem;font-weight:700;padding:2px 9px;border-radius:100px" data-i18n="bc5-tag2">Polaris 14× Champion</span>
	<span style="font-size:.7rem;color:var(--light);margin-left:auto">2026.06</span>
	</div>
	<h3 style="font-size:1rem;font-weight:800;line-height:1.4;margin-bottom:8px" data-i18n="bc5-title">AI That Reads Drugs First — Polaris Global 14× Champion</h3>
	<p style="font-size:.85rem;color:var(--muted);line-height:1.6;margin-bottom:12px" data-i18n="bc5-desc">#1 worldwide on 14 benchmarks across 5 fields: efficacy · solubility · toxicity · oncology kinase · ADME.</p>

	<!-- 카테고리 1: 약효 예측 -->
	<div style="margin-bottom:10px">
	<div style="font-size:.72rem;font-weight:800;color:var(--em);text-transform:uppercase;letter-spacing:.04em;margin-bottom:5px" data-i18n="bc5-cat1">💊 Efficacy Prediction</div>
	<div style="display:flex;flex-direction:column;gap:4px">
	<a href="https://polarishub.io/benchmarks/molecularml/moleculeace-chembl236-ki" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:var(--em-l);border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b1">How strongly a drug binds its target</span>
	<span style="font-size:.68rem;color:var(--em);font-weight:700;white-space:nowrap">chembl236-ki →</span>
	</a>
	<a href="https://polarishub.io/benchmarks/molecularml/moleculeace-chembl234-ki" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:var(--em-l);border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b2">Dopamine D3 receptor binding efficacy</span>
	<span style="font-size:.68rem;color:var(--em);font-weight:700;white-space:nowrap">chembl234-ki →</span>
	</a>
	</div>
	</div>

	<!-- 카테고리 2: 용해도 -->
	<div style="margin-bottom:10px">
	<div style="font-size:.72rem;font-weight:800;color:#0891B2;text-transform:uppercase;letter-spacing:.04em;margin-bottom:5px" data-i18n="bc5-cat2">💧 Solubility</div>
	<a href="https://polarishub.io/benchmarks/tdcommons/solubility-aqsoldb" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:#ECFEFF;border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b3">How well a drug dissolves in water</span>
	<span style="font-size:.68rem;color:#0891B2;font-weight:700;white-space:nowrap">solubility-aqsoldb →</span>
	</a>
	</div>

	<!-- 카테고리 3: 독성 예측 -->
	<div style="margin-bottom:10px">
	<div style="font-size:.72rem;font-weight:800;color:#B45309;text-transform:uppercase;letter-spacing:.04em;margin-bottom:5px" data-i18n="bc5-cat3">☠️ Toxicity Prediction</div>
	<div style="display:flex;flex-direction:column;gap:4px">
	<a href="https://polarishub.io/benchmarks/tdcommons/dili" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:var(--amb-l);border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b4">Drug-induced liver injury prediction</span>
	<span style="font-size:.68rem;color:#B45309;font-weight:700;white-space:nowrap">dili →</span>
	</a>
	<a href="https://polarishub.io/benchmarks/tdcommons/ames" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:var(--amb-l);border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b5">DNA mutation & carcinogenicity prediction</span>
	<span style="font-size:.68rem;color:#B45309;font-weight:700;white-space:nowrap">ames →</span>
	</a>
	</div>
	</div>

	<!-- 카테고리 4: 항암 키나아제 -->
	<div style="margin-bottom:10px">
	<div style="font-size:.72rem;font-weight:800;color:var(--ros);text-transform:uppercase;letter-spacing:.04em;margin-bottom:5px" data-i18n="bc5-cat4">🎯 Oncology Kinase Target Prediction</div>
	<div style="display:flex;flex-direction:column;gap:4px">
	<a href="https://polarishub.io/benchmarks/polaris/pkis1-egfr-wt-mut-r-1" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:#FFF1F2;border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b6">EGFR + L858R mutation inhibition</span>
	<span style="font-size:.68rem;color:var(--ros);font-weight:700;white-space:nowrap">pkis1-egfr-mut-r →</span>
	</a>
	<a href="https://polarishub.io/benchmarks/polaris/pkis2-egfr-wt-reg-v2" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:#FFF1F2;border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b7">EGFR inhibition prediction</span>
	<span style="font-size:.68rem;color:var(--ros);font-weight:700;white-space:nowrap">pkis2-egfr-reg-v2 →</span>
	</a>
	<a href="https://polarishub.io/benchmarks/polaris/pkis2-egfr-wt-r-1" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:#FFF1F2;border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b8">EGFR reclaim leaderboard</span>
	<span style="font-size:.68rem;color:var(--ros);font-weight:700;white-space:nowrap">pkis2-egfr-r →</span>
	</a>
	<a href="https://polarishub.io/benchmarks/polaris/pkis1-egfr-wt-mut-c-1" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:#FFF1F2;border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b9">EGFR mutation classification</span>
	<span style="font-size:.68rem;color:var(--ros);font-weight:700;white-space:nowrap">pkis1-egfr-mut-c →</span>
	</a>
	<a href="https://polarishub.io/benchmarks/polaris/pkis2-lok-slk-r-1" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:#FFF1F2;border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b10">LOK·SLK kinase inhibition</span>
	<span style="font-size:.68rem;color:var(--ros);font-weight:700;white-space:nowrap">pkis2-lok-slk →</span>
	</a>
	<a href="https://polarishub.io/benchmarks/polaris/pkis1-kit-wt-mut-r-1" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:#FFF1F2;border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b11">KIT mutation inhibition</span>
	<span style="font-size:.68rem;color:var(--ros);font-weight:700;white-space:nowrap">pkis1-kit-mut →</span>
	</a>
	</div>
	</div>

	<!-- 카테고리 5: ADME -->
	<div style="margin-bottom:14px">
	<div style="font-size:.72rem;font-weight:800;color:var(--ind);text-transform:uppercase;letter-spacing:.04em;margin-bottom:5px" data-i18n="bc5-cat5">🔬 Druggability·ADME Prediction</div>
	<div style="display:flex;flex-direction:column;gap:4px">
	<a href="https://polarishub.io/benchmarks/tdcommons/bioavailability-ma" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:var(--ind-xl);border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b12">How much of an oral drug reaches the bloodstream</span>
	<span style="font-size:.68rem;color:var(--ind);font-weight:700;white-space:nowrap">bioavailability-ma →</span>
	</a>
	<a href="https://polarishub.io/benchmarks/tdcommons/vdss-lombardo" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:var(--ind-xl);border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b13">How widely a drug distributes in body tissue</span>
	<span style="font-size:.68rem;color:var(--ind);font-weight:700;white-space:nowrap">vdss-lombardo →</span>
	</a>
	<a href="https://polarishub.io/benchmarks/tdcommons/cyp2d6-substrate-carbonmangels" target="_blank" style="font-size:.78rem;color:var(--fg);text-decoration:none;display:flex;justify-content:space-between;align-items:center;padding:4px 8px;background:var(--ind-xl);border-radius:6px;gap:8px">
	<span style="color:var(--muted)" data-i18n="bc5-b14">CYP2D6 enzyme metabolism & drug interaction</span>
	<span style="font-size:.68rem;color:var(--ind);font-weight:700;white-space:nowrap">cyp2d6-substrate →</span>
	</a>
	</div>
	</div>

	<a href="https://polarishub.io" target="_blank" style="font-size:.78rem;color:var(--em);font-weight:600" data-i18n="bc5-link">Full Polaris Leaderboard →</a>
	</div>

	</div>

	<!-- 더 보기 -->
	<div style="text-align:center;padding:32px;background:#fff;border:1px solid var(--border);border-radius:var(--r);box-shadow:var(--sh)">
	<div style="font-size:1.8rem;margin-bottom:10px">✍️</div>
	<h3 style="font-size:1rem;margin-bottom:6px" data-i18n="blog-more-h">More Insights</h3>
	<p style="color:var(--muted);margin-bottom:18px;font-size:.88rem" data-i18n="blog-more-p">AI insights · technology philosophy · industry analysis from VIDraft's CEO</p>
	<a class="btn btn-p" href="https://brunch.co.kr/@seawolf" target="_blank" data-i18n="blog-more-btn">Read more on Brunch @seawolf →</a>
	</div>
	</div>
	</div>
	</div>

	<!-- ═══════════ MODELS — Darwin 카탈로그 ═══════════ -->
	<div class="page" id="page-models">
	<style>
	.mdl-wrap{margin-top:8px;border:1px solid var(--border);border-radius:var(--r);overflow:hidden;box-shadow:var(--sh);background:#fff}
	.mdl-scroll{max-height:540px;overflow:auto}
	table.mdl{width:100%;border-collapse:collapse;font-size:.85rem}
	table.mdl thead th{position:sticky;top:0;background:var(--ind-xl);color:var(--ind);font-weight:700;text-align:left;padding:11px 12px;font-size:.72rem;letter-spacing:.3px;white-space:nowrap;z-index:1}
	table.mdl td{padding:9px 12px;border-top:1px solid var(--border);vertical-align:middle}
	table.mdl tbody tr:hover{background:var(--ind-xxl)}
	table.mdl .rk{color:var(--light);font-weight:700;width:38px;text-align:right}
	table.mdl a{color:var(--ind);font-weight:700;text-decoration:none;word-break:break-all}
	table.mdl a:hover{text-decoration:underline}
	.m-auth{display:block;color:var(--light);font-size:.72rem;font-weight:500;margin-top:1px}
	.m-pipe{color:var(--muted);font-size:.72rem;white-space:nowrap}
	.m-dl{font-weight:800;color:var(--text);text-align:right;white-space:nowrap}
	.m-30{color:var(--muted);text-align:right;white-space:nowrap}
	.m-lk{color:var(--ros);text-align:right;white-space:nowrap;font-size:.8rem}
	@media(max-width:640px){ table.mdl .hide-sm{display:none} }
	.sec-cnt{font-size:.72rem;font-weight:700;color:var(--ind);background:var(--ind-xl);padding:1px 9px;border-radius:100px;margin-left:4px;white-space:nowrap}
	table.mdl th.sortable{cursor:pointer;user-select:none}
	table.mdl th.sortable:hover{color:var(--ind-l)}
	table.mdl .sort-ar{font-size:.82em;opacity:.32;margin-left:1px}
	table.mdl .sort-ar.on{opacity:1;color:var(--ind)}
	#grid-spaces .sp-card{display:block;text-decoration:none;color:inherit}
	#grid-spaces .sp-card:hover{transform:translateY(-2px)}
	.sp-top{display:flex;justify-content:space-between;align-items:center;margin-bottom:8px;gap:8px}
	.sp-sdk{font-size:.63rem;font-weight:700;text-transform:uppercase;letter-spacing:.4px;color:var(--ind);background:var(--ind-xl);padding:2px 8px;border-radius:100px}
	.sp-lk{font-size:.75rem;color:var(--ros);font-weight:700;white-space:nowrap}
	.sp-name{font-weight:800;font-size:.92rem;color:var(--text);word-break:break-word;line-height:1.25}
	.sp-auth{font-size:.72rem;color:var(--light);margin-top:3px}
	</style>
	<div class="hero" style="padding:52px 0 34px">
	<div class="container">
	<div class="badge">🧬 DARWIN MODEL CATALOG</div>
	<h1 style="font-size:clamp(1.6rem,4vw,2.4rem);margin-bottom:12px">Darwin <span>Model Universe</span></h1>
	<p class="hero-sub" data-i18n="mdl-sub">Every officially released Darwin model and its community derivatives — counted by cumulative all-time downloads.</p>
	</div>
	</div>
	<div class="container">
	<div class="section-sm">
	<div class="stats" id="mdl-stats"></div>
	<p style="text-align:center;color:var(--light);font-size:.75rem;margin-top:14px">
	<span data-i18n="mdl-note-lbl">All-time cumulative downloads · HuggingFace shows only the last 30 days by default · updated</span>
	<span id="mdl-gen" style="color:var(--muted);font-weight:600"></span>
	</p>
	</div>
	<div class="section">
	<h2 class="st" data-i18n="mdl-off-h">Official <span>Models</span></h2>
	<p class="ss" data-i18n="mdl-off-s">Released on VIDraft & FINAL-Bench.</p>
	<div class="mdl-wrap"><div class="mdl-scroll"><table class="mdl" id="tbl-official"></table></div></div>
	</div>
	<div class="section">
	<h2 class="st" data-i18n="mdl-com-h">Community <span>Models</span></h2>
	<p class="ss" data-i18n="mdl-com-s">Quantizations, fine-tunes & derivatives built by the community on Darwin.</p>
	<div class="mdl-wrap"><div class="mdl-scroll"><table class="mdl" id="tbl-community"></table></div></div>
	</div>

	<div class="section">
	<h2 class="st" data-i18n="oth-h">Other <span>Models</span></h2>
	<p class="ss"><span data-i18n="oth-s">Notable non-Darwin models released by VIDraft & FINAL-Bench.</span> <span class="sec-cnt" id="cnt-other"></span></p>
	<div class="mdl-wrap"><div class="mdl-scroll"><table class="mdl" id="tbl-other"></table></div></div>
	</div>

	<div class="section">
	<h2 class="st" data-i18n="dkr-h">🐳 Docker <span>Images</span></h2>
	<p class="ss"><span data-i18n="dkr-s">Production-ready containers on Docker Hub (vidraft).</span> <span class="sec-cnt" id="cnt-docker"></span></p>
	<div class="mdl-wrap"><table class="mdl" id="tbl-docker"></table></div>
	</div>

	<div class="section">
	<h2 class="st" data-i18n="spc-h">Live <span>Demos</span></h2>
	<p class="ss"><span data-i18n="spc-s">Interactive demos on Hugging Face Spaces.</span> <span class="sec-cnt" id="cnt-spaces"></span></p>
	<div class="grid g3" id="grid-spaces" style="margin-top:8px"></div>
	</div>

	<div class="section">
	<h2 class="st" data-i18n="dts-h">📊 <span>Datasets</span></h2>
	<p class="ss"><span data-i18n="dts-s">Benchmarks & datasets published by VIDraft & FINAL-Bench.</span> <span class="sec-cnt" id="cnt-datasets"></span></p>
	<div class="mdl-wrap"><table class="mdl" id="tbl-datasets"></table></div>
	</div>
	</div>
	</div><!-- FOOTER -->
	<footer>
	<div class="container">
	<div class="fi">
	<div class="fb"><div class="fl"><span style="color:#FF4D6D">VI</span><span style="color:#9DB2FF">DRAFT</span></div><p data-i18n="ft-addr">VIDRAFT Inc.<br>175 Nonhyeon-ro, Seocho-gu, Seoul · Shinhan Bldg. 7F<br>Business Reg. 879-87-03063 · ArXivGPT@gmail.com</p><div style="margin-top:12px"><iframe title="VIDRAFT location" src="https://maps.google.com/maps?q=%EC%84%9C%EC%9A%B8%ED%8A%B9%EB%B3%84%EC%8B%9C%20%EC%84%9C%EC%B4%88%EA%B5%AC%20%EB%85%BC%ED%98%84%EB%A1%9C%20175%20%EC%8B%A0%ED%95%9C%EB%B9%8C%EB%94%A9&z=16&hl=ko&output=embed" width="250" height="140" style="border:1px solid rgba(255,255,255,.15);border-radius:10px;max-width:100%" loading="lazy" referrerpolicy="no-referrer-when-downgrade"></iframe><br><a href="https://www.google.com/maps/search/?api=1&query=%EC%84%9C%EC%9A%B8%ED%8A%B9%EB%B3%84%EC%8B%9C%20%EC%84%9C%EC%B4%88%EA%B5%AC%20%EB%85%BC%ED%98%84%EB%A1%9C%20175" target="_blank" rel="noopener" style="display:inline-block;margin-top:6px;font-size:.78rem;color:#9DB2FF;text-decoration:none">📍 Google Maps →</a></div></div>
	<div class="fc"><h4 data-i18n="ft-tech">Technology</h4>
	<a href="javascript:void(0)" onclick="showPage('darwin')">Darwin Platform</a>
	<a href="javascript:void(0)" onclick="showPage('aether')">AETHER Architecture</a>
	<a href="https://arxiv.org/abs/2605.14386" target="_blank" data-i18n="ft-paper">Darwin Family Paper</a>
	<a href="https://huggingface.co/VIDraft" target="_blank">HuggingFace</a>
	</div>
	<div class="fc"><h4 data-i18n="ft-achieve">Achievements</h4>
	<a href="javascript:void(0)" onclick="showPage('proof')" data-i18n="ft-bench">Benchmarks</a>
	<a href="javascript:void(0)" onclick="showPage('proof')" data-i18n="ft-patents">Patents (11)</a>
	<a href="javascript:void(0)" onclick="showPage('proof')" data-i18n="ft-press">Press Coverage</a>
	<a href="https://huggingface.co/collections/FINAL-Bench/metacognition-adapters" target="_blank" data-i18n="ft-meta">Metacognition Adapters</a>
	</div>
	<div class="fc"><h4 data-i18n="ft-services">Key Services</h4>
	<a href="https://jgos.vidraft.net/" target="_blank" data-i18n="ft-svc-jgos">JGOS Citizen AI</a>
	<a href="https://admet.1street.ai/" target="_blank" data-i18n="ft-svc-admet">ADMET Drug Prediction</a>
	<a href="https://materials.1street.ai/" target="_blank">MaterialsOS</a>
	<a href="https://hansoo.vidraft.net" target="_blank" data-i18n="ag-hansoo-h">HanSoo (韓守)</a>
	</div>
	</div>
	<div class="fb2">
	<p data-i18n="ft-copy">© 2026 VIDRAFT Inc. All rights reserved.</p>
	<p style="color:#475569" data-i18n="ft-tag">Pre-AGI · Darwin · AETHER · Korea AI #1</p>
	</div>
	</div>
	</footer>

	<script>
	/* ── i18n ── */
	const T={
	en:{
	/* title + nav */
	'page-title':'VIDRAFT — Pre-AGI Model Development',
	'nav-models':'Models',
	'mdl-sub':'Every model in the Darwin lineage (since 2026-03-31) — official releases and community derivatives, counted by cumulative all-time downloads.',
	'mdl-note-lbl':'All-time cumulative downloads · HuggingFace shows only the last 30 days by default · updated',
	'mdl-off-h':'Official <span>Models</span>',
	'mdl-off-s':'Released on VIDraft & FINAL-Bench.',
	'mdl-com-h':'Community <span>Models</span>',
	'mdl-com-s':'Quantizations, fine-tunes & derivatives built by the community on Darwin.',
	'mdl-st-total':'Total Models','mdl-st-var':'Derivative Variants (incl. quantizations)',
	'mdl-st-dl':'Cumulative Downloads',
	'mdl-st-off':'Official (VIDraft·FINAL-Bench)',
	'mdl-st-com':'Community Derivatives',
	'mth-model':'Model',
	'mth-type':'Type',
	'mth-created':'Created',
	'mth-dl':'Cumulative DL',
	'oth-h':'Other <span>Models</span>',
	'oth-s':'Notable non-Darwin models released by VIDraft & FINAL-Bench.',
	'dkr-h':'🐳 Docker <span>Images</span>',
	'dkr-s':'Production-ready containers on Docker Hub (vidraft).',
	'spc-h':'Live <span>Demos</span>',
	'spc-s':'Interactive demos on Hugging Face Spaces (top by likes).',
	'dts-h':'📊 <span>Datasets</span>',
	'dts-s':'Benchmarks & datasets published by VIDraft & FINAL-Bench.',
	'dth-img':'Image',
	'dth-desc':'Description',
	'dth-pulls':'Pulls',
	'dts-th':'Dataset',
	'mth-updated':'Updated',
	'dash-kicker':'Live Ecosystem Dashboard',
	'dash-title':'The Darwin <span>Ecosystem</span> at a glance',
	'dash-upd':'Updated',
	'ch-top':'Top Official Models by Downloads',
	'ch-mo':'Model Release Momentum (2026)',
	'ch-gpqa':'GPQA Diamond — Darwin Family',
	'ch-eco':'Downloads by Source',
	'kpi-kai':'K-AI Leaderboard (Korea)',
	'kpi-gpqa':'GPQA Diamond record',
	'kpi-models':'Darwin models',
	'kpi-dl':'Cumulative downloads',
	'kpi-spaces':'Live demos (Spaces)',
	'kpi-datasets':'Datasets',
	'src-com':'Community',
	'src-ds':'Datasets',
	'src-oth':'Other models',
	'src-off':'Official',
	'press-h':'In the <span>Press</span>',
	'press-s':"VIDraft's coverage across Korean tech media.",
	'proof-allpress-h':'All <span>Press Coverage</span>',
	'proof-allpress-s':'Full media archive including founder essays — auto-updated.',
	'pol-kicker':'Polaris Hub · Global Drug-Discovery ML Benchmark',
	'pol-h':'14 First-Place Finishes — ADMET · Potency · Kinase',
	'pol-desc':'Structure-only prediction — no cell-imaging or external experimental data — topped 14 public Polaris leaderboards across absorption, distribution, metabolism, excretion, toxicity, potency and kinase selectivity.',
	'pol-1p':'Beat 2nd place (0.868, which relied on external cell-imaging data) using molecular structure alone.',
	'pol-2p':'Drug-induced liver-injury classification (ROC-AUC).',
	'pol-3p':'Metabolism prediction; 3D-shape features overtook the prior top model.',
	'pol-4p':'AqSolDB solubility regression — first to break the prior ceiling.',
	'pol-5p':'Binding-affinity potency, large margin over the previous best.',
	'pol-6p':'EGFR regression — swept every metric versus the prior best.',
	'pol-link':'Leaderboard →',
	'pol-note':'All results are computational predictions on public blind-submission leaderboards, submitted under the VIDraft account.',
	'nav-quantum':'Quantum',
	'q-h1':'Cryptanalysis on Real Quantum Hardware',
	'q-sub':'Simon-algorithm attacks executed on IBM 156-qubit ibm_kingston — at record hardware scale.',
	'q-story-h':'The world stopped at "4". A small Korean team pushed to "10".',
	'q-story-p1':'Drawing a rocket on paper and actually launching it are two different things. Real quantum computers are noisy — a slightly longer computation drowns the answer. For years the public record on real hardware stayed stuck around N≈4.',
	'q-story-p2':'VIDraft touched that wall. Taking the two most vulnerable structures — Even–Mansour and Feistel — onto IBM real quantum computer, the team pushed the simplest block-cipher structure to N = 5, 6, 7, 8, 9 and 10, recovering a fresh independent key each time to prove it was not a rigged demo tuned to one answer — using noise mitigation only, no costly error correction.',
	'q-btn1':'Live Demo →',
	'q-btn2':'Leaderboard →',
	'q-hw-h':'Real <span>Hardware</span> Results',
	'q-hw-s':'IBM ibm_kingston (156 qubits) · 15–30 qubit circuits with hundreds of two-qubit gates.',
	'q-hw1':'Secret-key recovery on real hardware from N=5 up to N=10 — exceeding the previous public record of N≈4 (to our knowledge).',
	'q-hw2':'Hidden-period recovery at block sizes 6 and 8, rank-1 clean.',
	'q-hw-note':'Error mitigation only — dynamical decoupling, gate/measurement twirling, readout-error correction (no quantum error correction). Independent control keys were tested per instance to confirm the attack is not tuned to one answer.',
	'q-sim-h':'Five <span>Attack Structures</span>',
	'q-sim-s':'Genuine quantum algorithms covering the major cryptographic design paradigms. The two Simon-based constructions were pushed to hardware.',
	'q-s1':'A linear cipher gives up its secret in a single query — the most anticlimactic collapse.',
	'q-s2':'Executed on real hardware ✓',
	'q-s3':'Brute-force key search shrinks to its square root — the very threat forcing AES to lengthen its keys.',
	'q-s4':'The message-authentication seal is forged without any key.',
	'q-s5':'Executed on real hardware ✓',
	'q-honest-h':'⚠️ Honest Scope',
	'q-honest':'This is a record-scale hardware demonstration — NOT a practical quantum speedup (effective difficulty still tracks the classical birthday bound ~2^(n/2)), NOT a break of AES / RSA / 16-round DES, and NOT quantum-error-corrected (NISQ-era mitigation only). World-first status is unconfirmed pending peer review.',
	'nav-chitos':'Chitos',
	'ch-h1':'From suspicion to proof',
	'ch-sub':'Most scanners flag a pattern and say "maybe a vuln — you check." Chitos verifies inside authorized targets, confirms reproducibility, and chains attack paths into one scenario.',
	'ch-btn1':'Try Free →',
	'ch-flow-h':'Three <span>Stages</span>',
	'ch-flow-s':'Successor to VIDRAFT Mythos. Where Mythos was static analysis, Chitos verifies.',
	'ch-s1-t':'Stage 1 · Static Scan (free)',
	'ch-s1-h':'Multi-language pattern analysis',
	'ch-s1-p':'Python, JS, Go, Java, C/C++, Rust, PHP, YAML — injection sinks, deserialization, credential exposure, crypto misuse, prototype pollution, supply-chain risk. Unproven warnings are filtered out as noise.',
	'ch-s2-t':'Stage 2 · Threat Research',
	'ch-s2-h':'Autonomous context research',
	'ch-s2-p':'Cross-references CVE databases, exploit advisories and public PoCs to explain WHY a finding is dangerous in the current threat landscape. (Requires a Claude API key.)',
	'ch-s3-t':'Stage 3 · Active Verification (free)',
	'ch-s3-h':'Reproducible exploit proof',
	'ch-s3-p':'On authorized targets only — XSS, SQLi, path traversal, command injection. Finds reproducible evidence, retries variant paths when blocked, and links confirmed vulnerabilities into a kill-chain threat map.',
	'ch-ex-h':'Ready-to-run <span>Scenarios</span>',
	'ch-ex-s':'Five representative attack scenarios, one click each. Live-test against IBM intentionally-vulnerable demo.testfire.net.',
	'ch-priv-h':'🔒 Privacy by design',
	'ch-priv-p':'No install. No signup. Your code is never sent to an external API.',
	'ch-legal-h':'⚖️ Authorized use only',
	'ch-legal-p':'Active exploit features may be used only on targets you own or are explicitly authorized to test. Unauthorized testing or scanning may be illegal; all legal responsibility rests with the user.',
	'nav-vkae':'VKAE',
	'nav-solutions':'Solutions',
	'nav-about':'Company',
	'ab-h1':'Intelligence is not made — it is grown.',
	'ab-sub':'A small Korean Proto-AGI startup (since 2024) with one belief: do not exaggerate — speak only what is verified.',
	'ab-phil-h':'Our <span>Philosophy</span>',
	'ab-phil-s':'Great life was never designed all at once. Seed → sprout → tree → forest. AGI is grown by nature law, not built by force.',
	'ab-p1-tag':'Grow, not make','ab-p1-h':'기르다 · Cultivate','ab-p1-p':'We do not build intelligence in one giant step; we grow it across generations, the way nature evolves great life. 씨앗 → 새싹 → 나무 → 숲.',
	'ab-p2-tag':'Honesty & verification','ab-p2-h':'정직과 검증','ab-p2-p':'Our founding spirit: do not exaggerate; speak only what has been verified. Real trust comes from honestly stating what we have NOT done.',
	'ab-p3-h':'Grow by evolution','ab-p3-p':'Crossbreed the strengths of different models to raise a stronger next generation — inheriting a lineage of intelligence, like a craft passed down through generations.',
	'ab-p4-h':'Harmony of diversity (조화)','ab-p4-p':'Not one method — 5·7·11 kinds of attention coexist. When diversity harmonizes, higher intelligence awakens. This is how we look beyond the Transformer.',
	'ab-p5-h':'Soil for the next era (길)','ab-p5-p':'We do not claim to have completed the quantum computer. We till the soil for the next era, verifying step by step on real hardware. AGI is a road, not a destination.',
	'ab-p6-tag':'Tech for people','ab-p6-h':'Philosophy on the ground','ab-p6-p':'Technology for people and society — the same dream as Society 5.0. From Jeonnam·Gwangju (3.2M citizens) to across borders.',
	'ab-hist-h':'Major <span>Milestones</span>',
	'ab-team-h':'The <span>Crew</span>',
	'ab-team-s':'Eleven people, armed with freedom, flexibility, speed and creativity — like romantic pirates.',
	'ab-team-q':'🏴‍☠️ "Join My Crew?" — we call ourselves 조마크.',
	'ab-team-qs':'Ask any VIDraft member their identity and we answer Jo-mark — the crew callsign, drawn from the manga One Piece. Not resources but wits; not volume but grit and agility.',
	'ab-t1-h':'A crew of 11','ab-t1-p':'A tight team that beats volume with method — 24 GPUs against the giants.',
	'ab-t2-h':'Vertically integrated','ab-t2-p':'Own LLMs · City OS · drug/material AI · on-prem AI — CEO, Vice President and Japan Business Head lead a Proto-AGI stack.',
	'ab-t3-h':'Join My Crew','ab-t3-p':'Looking for the next global AI pirate — freedom, speed, creativity. Contact us.',
	'sol-h1':'Sovereign AI OS — your data never leaves the network',
	'sol-sub':'Not one chatbot, but an AI operating system that connects administration, citizen and industry data safely inside a local / independent network.',
	'sol-btn1':'Contact for a Pilot →',
	'sol-gov-h':'Public · Local-Government <span>AX</span>',
	'sol-gov-s':'Administration overload · fragmented data · cloud-AI security concerns → a local sovereign AI operating system.',
	'sol-c1-h':'Region-tuned LLM','sol-c1-p':'Language · administration · industry models tuned for each region.',
	'sol-c2-h':'Grounded & self-verifying','sol-c2-p':'Hallucination suppression · self-verification · evidence-backed answers.',
	'sol-c3-h':'Policy simulation','sol-c3-p':'Policy · budget · industry simulation on regional digital twins.',
	'sol-c4-h':'One common AI touchpoint','sol-c4-p':'A shared AI access point for citizens, officials and enterprises.',
	'sol-c5-h':'Pharma · Material · Nutri · Legal','sol-c5-p':'Vertical-domain AI plugged into the regional OS.',
	'sol-c6-h':'Data stays inside','sol-c6-p':'On-premise / independent-network deployment, verified by a 3-month KPI pilot.',
	'sol-c7-h':'Building — Architectural Design AI','sol-c7-p':'From natural language to KS-standard floor plans (DXF·BIM·BOQ·fire-safety checks), and from a parcel address to code-compliant 3D building massing with FAR slider, solar setback and photoreal aerials.',
	'svc-tab-building':'Building·Design','ag-floorplan-h':'FloorPlan AI','ag-floorplan-p':'NL → KS F 1501 drawings',
	'svc-building-h':'FloorPlan AI <span>Architectural Design</span>','svc-building-s':'From a Korean sentence to a verified floor plan — or from a parcel address to a code-compliant 3D building. Drawings, BIM, cost and fire-safety in minutes.',
	'svc-building-s2':'Natural language becomes KS F 1501 drawings, 3D, walkthrough and quantity takeoff — designed by a 397B-parameter MoE and reviewed by a VLM critic.',
	'svc-fp1-h':'Text → standard floor plans','svc-fp1-p':'Natural language becomes KS F 1501 drawings (parallel drafts + AI review) — mm, 1:100, wall poché, area table.',
	'svc-fp2-h':'6 automatic checks','svc-fp2-p':'Building code · fire safety · barrier-free access · design metrics · cost estimate · AI review score.',
	'svc-fp3-h':'Parcel → site design','svc-fp3-p':'Type a parcel address: zoning, official land price and lot boundaries fetched from the national V-World open-data platform.',
	'svc-fp4-h':'FAR slider + solar setback 3D','svc-fp4-p':'Statutory coverage/FAR enforced geometrically; north solar-setback cut into the 3D mass; FAR slider recomputes area, floors and cost live.',
	'svc-fp5-h':'Layout-quality score','svc-fp5-p':'Zoning, privacy, south exposure, circulation and proportion scored 0–100 by deterministic rules — not AI self-assessment.',
	'svc-fp6-h':'Export DXF·PDF·IFC·BOQ','svc-fp6-p':'DXF (AutoCAD) · PDF (A3 sheet) · IFC (BIM) · XLSX quantity takeoff.',
	'svc-fp7-h':'Walk · sun study · aerials','svc-fp7-p':'First-person walk mode, monthly/hourly sun study, and AI photoreal renders and aerials.',
	'svc-fp-disc':'※ AI concept-design reference only — coverage/FAR use statutory maximums (actual limits depend on local ordinances), official land price is not market price, and permit and construction documents proceed with a licensed architect.',
	'svc-fp-cta1':'Open FloorPlan AI →','svc-fp-cta2':'Read the story (Brunch) →',
	'sol-pkg-h':'5 AX Packages',
	'sol-p1':'Administration','sol-p2':'Citizen','sol-p3':'Industry','sol-p4':'Bio','sol-p5':'Materials',
	'sol-case-h':'Live Deployments — <span>Seoul AI & Robot Science Museum</span>',
	'sol-case-s':'Three exhibits built by VIDraft, running for the public.',
	'sol-r1-tag':'Physical AI','sol-r1-h':'Talk to Spot','sol-r1-p':'Boston Dynamics Spot controlled by natural-language voice — converse with, command and steer the robot through an LLM.',
	'sol-r2-tag':'Interpretability','sol-r2-h':'Model X-RAY','sol-r2-p':'See inside the LLM black box — an X-RAY view that makes a model internal workings transparent to visitors.',
	'sol-r3-tag':'Evolution','sol-r3-h':'Darwin Crossbreed & Evolve','sol-r3-p':'Watch AI models crossbreed and evolve — the child surpasses both parents. An interactive Darwin evolution experience.',
	'v-h1':'Make one more GPU — without making a GPU',
	'v-sub':'VKAE (VIDRAFT Kernel Acceleration Engine) squeezes multiples more throughput out of the GPU you already own — kernel-level, with answer quality unchanged.',
	'v-btn1':'Leaderboard & Demo →',
	'v-btn2':'Docker →',
	'v-k1':'throughput vs. standard (NVIDIA B200)',
	'v-k2':'tokens/sec under concurrent load',
	'v-k3':'quality loss — same answers, faster',
	'v-k4':'reproducible — one Docker, your GPU',
	'v-why-h':'Why inference acceleration is <span>essential</span>',
	'v-why-s':'The real AI-infra battleground is not building the model — it is running it, cheaply, forever.',
	'v-w1-t':'Efficiency = capacity',
	'v-w1-h':'A virtual extra GPU',
	'v-w1-p':'GPUs are scarce, expensive and power-hungry. Doubling throughput on the same card is like building twice the infrastructure — no new chips, no new power.',
	'v-w2-t':'Cost per token',
	'v-w2-h':'Where AI services win or lose',
	'v-w2-p':'Training happens once; inference happens every time a user asks. VKAE lowers the per-token cost that decides whether an AI service is profitable.',
	'v-w3-t':'Sovereign-AI ready',
	'v-w3-h':'Not a nice-to-have',
	'v-w3-p':'For clouds, AI startups, enterprises and national/sovereign AI, acceleration is not optional — without it, running AI at scale runs at a loss.',
	'v-repro-h':'🔬 Reproducible, not just a claim',
	'v-repro-p':'Speed claims are cheap. VKAE ships the model weights plus the optimized serving stack as one Docker container, OpenAI-compatible — so anyone can reproduce the numbers on their own GPU and plug it straight into an existing service.',
	'v-l1':'VKAE-accelerated model weights on Hugging Face.',
	'v-l2':'Integrated container — weights + optimized serving, OpenAI-compatible.',
	'nav-home':'Home','nav-proof':'Achievements','nav-services':'Services','nav-blog':'Blog','nav-spot':'🤖 Talk with Spot','spot-cap':'VIDRAFT on-device VLM on Boston Dynamics Spot — voice command & conversation',
	/* hero */
	'hero-badge':'🇰🇷 K-AI #1 · GPQA Diamond 90.9% · Polaris 14× Champion · KAIT GPU Support Award',
	'hero-h1':'Evolving AI.<br><span>Thinking AGI.</span>',
	'hero-sub':'Pre-AGI platform made in Korea — Darwin delivers results, AETHER designs the future.',
	'hero-btn1':'View Darwin Models →','hero-btn2':'All Services →',
	/* stats */
	'stat-gpqa':'GPQA Diamond All-time Record','stat-dl':'HuggingFace Total Downloads',
	'stat-dl-num':'1M+','stat-patent-num':'11',
	'stat-model':'Community Derived Models','stat-patent':'Patent Filed (KR + PCT)',
	/* home sections */
	'home-news-h':'Latest <span>Achievements</span>','home-news-s':'Key achievements by VIDraft in 2026.',
	'home-agi-h':'Journey to <span>AGI</span>','home-agi-s':'AGI is achieved step by step. VIDraft is now at the Pre-AGI stage.',
	'home-sys-h':'4-Layer Integrated <span>System</span>','home-sys-s':'Not a single model — four layers organically integrated to design Embodied AGI.',
	/* KAIT box */
	'kait-date':'2026.6 · KAIT Project Review',
	'kait-ref':'Ref. No. RQT-25-090162',
	'kait-title':'"AI Computing Resource Infrastructure Enhancement (GPU Lease Support)" — <span style="color:var(--em)">Excellent</span>',
	'kait-desc':'Korea Association for ICT Promotion (KAIT) · GPU Lease Support Project rated <strong>Excellent</strong>.',
	'kait-badge':'Excellent',
	/* news cards */
	'news1-media':'Edaily','news1-title':'Darwin-398B-JGOS, GPQA Diamond 90.9%',
	'news1-desc':'180 of 198 correct. World-class performance through pure reasoning. MoE + Darwin V9 method.',
	'news2-media':'Seoul Shinmun','news2-title':'JGOS-31B-Citizen, K-AI Leaderboard Overall #1',
	'news2-desc':'MSIT·NIA certified score 0.621, ranked #1. 8 of top 12 are Darwin derivatives (67%).',
	'news3-media':'Tencent News','news3-title':'Tencent (China’s #1 Portal) Spotlights Darwin',
	'news3-desc':'China’s largest portal features Darwin’s “genetic recombination” merging — smarter AI without retraining.',
	'news-link':'Read →',
	/* AGI stages */
	'agi-p1':'Single-task specialization','agi-p2':'Multi-task combination',
	'agi-p3':'Metacognition + Self-correction + Swarm collaboration',
	'agi-now':'▶ Now','agi-p4':'True AGI','agi-p5':'Post AGI',
	/* layer cards */
	'layer-darwin-p':'Evolutionary model family. K-AI #1 + GPQA 90.9%',
	'layer-aether-p':'5/7/11-way heterogeneous attention Pre-AGI architecture',
	'layer-prom-p':'World model. Sole Track C pass on WM Bench (726 pts)',
	'layer-heph-p':'Embodied AI · 4 Jetson platforms operationally verified',
	'layer-chain':'LLM → AETHER → PROMETHEUS → HEPHAESTUS = <strong style="color:var(--ind)">Embodied AGI</strong>',
	/* video */
	'vid-h':'VIDraft Introduction Video',
	'vid-p':'See the technical innovation of the Darwin Platform and AETHER in action.',
	/* darwin leaderboard */
	'darwin-h1':'Korea\'s #1 AI Platform Delivering Measurable Results',
	'darwin-sub':'K-AI #1 · GPQA Diamond 90.9% · Polaris Global 14× Champion · Metacognition Leaderboard #1',
	'darwin-tab1':'📊 Leaderboard','darwin-tab2':'🧬 Model Family','darwin-tab3':'🧠 Metacognition',
	'darwin-gpqa-h':'GPQA Diamond <span>Global Leaderboard</span>','darwin-gpqa-s':'HuggingFace certified · As of June 2026',
	'darwin-kai-h':'K-AI <span>Leaderboard</span>','darwin-kai-s':'MSIT·NIA certified · Blind evaluation · As of June 2026',
	'darwin-models-h':'Darwin <span>Official Model Family</span>','darwin-models-s':'20+ official · 1,200+ derivatives & quant variants · 1M+ all-time downloads (HF-verified 2026-07)','m-9bneg-p':'9B NEG single-pass evolution. Most-downloaded model in the Darwin family — 575K+ all-time.','m-36bopus-p':'GPQA Diamond 88.4%. Community-favorite flagship, widely quantized and redistributed.','m-31bopus-p':'Korean flagship. CLIcK 84.5 · KMMLU 76. Top Korean-language Darwin.','m-coder-p':'Coding specialist. Top official GGUF download in the Darwin family.','darwin-dl-note':'⬇️ = HuggingFace all-time downloads (official + community redistributions), verified 2026-07. Darwin family total: 1M+.',
	'darwin-lb-kai':'K-AI Leaderboard Overall #1<br><small>JGOS-31B-Citizen 0.621</small>',
	'darwin-lb-pol-n':'14×','darwin-lb-pol':'Polaris Global Drug Discovery<br><small>ADMET + Efficacy + Kinase</small>',
	'th-rank':'Rank','th-model':'Model','th-score':'Score','th-note':'Note','th-cat':'Category',
	'tag-vid-latest':'VIDraft Latest','tag-vid':'VIDraft','tag-vid-official':'VIDraft Official','tag-darwin-der':'Darwin Derivative',
	'darwin-kai-hl-h':'📊 11 of the K-AI Top 20 are Darwin models',
	'darwin-kai-hl-p':'A result that emerged naturally in the MSIT·NIA blind evaluation. Third-party certified figures, not self-reported.',
	/* darwin models */
	'm-jgos398-p':'MoE structure, 17B active params. Darwin V9 method. World-class pure reasoning.',
	'm-darwin28-p':'GPQA Diamond 88.89%. Surpasses 400B class with no extra training. arXiv 2605.14386.',
	'm-jgos31-p':'Public administration Korean. CLIcK 0.987 · KMMLU-Pro 0.725 · Com2 0.742.',
	'm-david-p':'31B-class at 4.5B. GPQA 85.0%. Cumulative +26.4%p. Fit for embodied AI & mobile.',
	'm-genesis-p':'Transformer × Mamba cross-breeding. CLIcK 92%. World-first heterogeneous crossbreed verified.',
	'm-tts-p':'1.7B Korean speech synthesis. Cross-architecture evolution.',
	'm-35b-p':'35B MoE flagship. GPQA Diamond 90.0%. Multimodal support.',
	'm-legal-p':'27B BF16 legal specialist. B200 load 9.7s. TPS 22.3 tok/s.',
	'm-reason-p':'Reasoning-enhanced specialist. Optimized for math·code·science reasoning.',
	'darwin-coll-p':'Browse and download all 20 models in the HuggingFace FINAL-Bench collection.',
	'darwin-coll-btn':'View Darwin Family Collection →',
	/* darwin metacognition */
	'darwin-meta-h':'Metacognition <span>Leaderboard</span>','darwin-meta-s':'JinigenAI · VIDraft joint development · 24 AI models evaluated · Published 2026.07.01',
	'meta-quote':'🧠 "AI is dangerous not when it makes an error, but when it doesn\'t know it has."',
	'meta-quote-s':'JGOS-31B-Citizen avoids 398 of 400 trap questions (99.5%, #1). Metacognition = an essential AGI capability.',
	'meta-c1-tag':'World First','meta-c1-h':'FINAL Bench','meta-c1-p':'World\'s first metacognition benchmark. 100 tasks × 15 domains × 8 types (TICOS) × 3 difficulty levels.',
	'meta-c2-tag':'400 Questions','meta-c2-h':'Trap-Question Evaluation','meta-c2-p':'400 questions designed to induce plausible-but-wrong answers. Measures self-error recognition.',
	'meta-c3-tag':'Non-invasive','meta-c3-h':'Metacognition Adapter','meta-c3-p':'Analyzes internal signals to detect self-errors in advance without altering the original model\'s structure or weights.',
	'meta-coll-tag':'11 Models','meta-coll-p':'11 individual metacognition adapters for major models like Darwin-28B-Opus, Darwin-9B-NEG, and JGOS-31B-Citizen.',
	'meta-lb-tag':'Leaderboard','meta-lb-p':'Metacognition performance comparison leaderboard. 24 AI models evaluated across trap avoidance and self-error detection.',
	'q-crypto-tag':'Cryptanalysis · Real HW','q-crypto-h':'QuantumOS Cryptanalysis Demo','q-crypto-p':'Genuine quantum-algorithm cryptanalysis suite executed on IBM Kingston real hardware — Even-Mansour N=10 and 3-round Feistel (DES-style) blocks 6/8, rank-1 clean. Honest scope disclosure: not real AES/RSA, not quantum supremacy.',
	/* aether */
	'aether-h1':'End of single-attention era.<br><span style="color:var(--pur)">Dawn of 5/7/11-way Hybrid.</span>',
	'aether-stat-first':'World First','aether-stat-first-l':'5/7/11-way heterogeneous attention integrated into a single LLM',
	'aether-stat-claims':'186','aether-stat-claims-l':'Patent claims (KR priority + PCT)',
	'aether-stat-n3':'n³','aether-stat-n3-l':'Triple Symmetry expressiveness gain',
	'aether-train-h':'<span>3 Models</span> in Training',
	'aether-m1-tag':'✓ Verified','aether-m1-p':'5×5 Latin Square · 25 layers · 14.09B params · 5-way attention',
	'aether-m2-tag':'⏳ Training','aether-m2-p':'7×7 Latin Square · 49 layers · 30.6B params · 7-way attention',
	'aether-m3-tag':'⏳ Training','aether-m3-p':'11×11 Latin Square · 121 layers · World-first 11-way attention',
	'aether-attn-h':'11-way <span>Heterogeneous Attention Ensemble</span>','aether-attn-s':'Integrating the latest research into a single LLM.',
	'attn-mla-t':'Standard','attn-full-t':'Standard','attn-slide-t':'Efficient','attn-gdn-t':'Length',
	'attn-mamba-t':'Length','attn-nsa-t':'Compress','attn-nsa-d':'Native Sparse Attention · Sequence compression',
	'attn-diff-t':'Adaptive','attn-diff-d':'Differential Attention · Adaptive noise cancellation',
	'attn-lin-t':'Linear','attn-gate-t':'Gate','attn-hi-t':'High-eff.',
	'aether-road-h':'Development <span>Roadmap</span>',
	'road1-span':'(Done)','road1-p':'5×5 · 5-way attention · In operation',
	'road2-span':'(Training)','road2-p':'7-way & 11-way parallel verification · World-first 11-way integration',
	'road3-span':'(Q3·Q4 2026)','road3-p':'Frontier challenge · KMMLU 75-85% · GPQA 75-85%',
	'road4-span':'(Next year)','road4-p':'ICLR 2027 / NeurIPS 2026 academic presentation planned',
	'aether-prin-h':'AGI 5 Core <span>Design Principles</span>',
	'pil1-h':'Emergence','pil1-p':'9 emergence engines + MARL runtime',
	'pil2-h':'Metacognition','pil2-p':'8-type self-error detection · TICOS',
	'pil3-h':'Self-evolution','pil3-p':'Closed-loop perpetual learning · SLAI',
	'pil4-h':'Swarm Collaboration','pil4-p':'Multi-agent · SOMA/MOUSE',
	'pil5-h':'Mutual Reinforcement','pil5-p':'Five-element enhance/suppress · Hallucination control',
	/* proof */
	'proof-h1':'Benchmarks. Papers. Patents. <span style="color:var(--ind)">Press Coverage.</span>',
	'proof-sub':'Results are measured, recorded, and protected.',
	'proof-tab1':'🏆 Benchmarks','proof-tab2':'📄 Papers','proof-tab3':'🔒 Patents (11)','proof-tab4':'📰 Press',
	'kait2-date':'2026.6 · KAIT (Korea Association for ICT Promotion) · Ref. No. RQT-25-090162',
	'kait2-title':'"AI Computing Resource Infrastructure Enhancement (GPU Lease Support)" — <span style="color:var(--em)">Excellent</span>',
	'kait2-desc':'GPU Lease Support Project rated Excellent.',
	'kait2-badge':'Excellent',
	'bench1-p':'Darwin-398B-JGOS 90.9%. Darwin-28B-Opus 88.89% #1. 5 Darwin models in Top 21. HuggingFace certified.',
	'bench2-p':'JGOS-31B-Citizen overall #1 (0.621). 11 Darwin derivatives in the Top 20. Blind evaluation.',
	'bench3-p':'HF Global Top 5. 100 tasks × 15 domains × 8 types × 3 difficulty. TICOS quantitative measurement.',
	'bench4-p':'World model benchmark. Sole model to pass Track C. Real-time interactive world simulation.',
	'pat-sub':'KR priority filing + PCT · 186 claims total',
	'pat-darwin-h':'🧬 Darwin Evolutionary · 3 patents',
	'pat-d1-h':'MRI-Based Adaptive Reliability Meta-learning','pat-d1-p':'Neural-network parameter merging based on Model-layer Response Importance (MRI)',
	'pat-d2-h':'Compatibility-Assessed Heterogeneous Crossbreeding','pat-d2-p':'Cross-architecture model merging via compatibility scoring',
	'pat-d3-h':'Recursive Generational Inheritance Evolution','pat-d3-p':'Iterative generational model evolution and inheritance',
	'pat-aether-h':'⚡ AETHER Architecture · 8 patents · 186 claims',
	'pat-a1-h':'Latin-Square Hybrid Multi-Type Attention','pat-a1-p':'5/7/11-way heterogeneous attention Latin Square integration',
	'pat-a2-h':'Automatic Causal Safety Verification','pat-a2-p':'Automated causal safety CI/CD verification',
	'pat-a3-h':'Metacognition Signal Head','pat-a3-p':'Self-error detection signal head',
	'pat-a4-h':'Perpetual Closed-Loop Learning','pat-a4-p':'Closed-loop self-evolution learning system',
	'pat-a5-h':'Multi-Agent Swarm Coordination','pat-a5-p':'Emergent multi-agent collaboration runtime',
	'pat-a6-h':'Triple-Symmetric MoE Routing','pat-a6-p':'n³ expressiveness triple-symmetry routing',
	'pat-a7-h':'Adaptive Noise-Cancelling Attention','pat-a7-p':'Differential attention noise suppression',
	'pat-a8-h':'Hallucination-Suppression Gate','pat-a8-p':'Enhancement/suppression gating for hallucination control',
	'press1-t':'JinigenAI·VIDraft release AI metacognition leaderboard','press-link':'View',
	'press2-t':'Darwin-398B-JGOS records GPQA Diamond 90.9%',
	'press3-t':'JGOS-31B-Citizen tops K-AI Leaderboard overall',
	'press4-t':'8 of K-AI Top 12 are Darwin derivatives',
	'press5-t':'Darwin Family paper published on arXiv (2605.14386)',
	'press6-t':'VIDraft Polaris global drug-discovery 14× champion',
	'press7-t':'AETHER 5/7/11-way hybrid attention unveiled',
	'press8-t':'KAIT GPU Lease Support Project rated Excellent',
	/* services */
	'services-h1':'Proof comes from <span style="color:var(--ind)">usage</span>',
	'services-sub':'Live services running on the Darwin + AETHER platform.',
	'svc-tab-all':'All','svc-tab-hf':'HuggingFace','svc-tab-vkae':'VKAE','svc-tab-gov':'National·Gov',
	'svc-tab-pharma':'Drug·Materials','svc-tab-quantum':'Quantum·Science','svc-tab-tools':'Tools·Security',
	'svc-all-h':'All Services <span>at a Glance</span>',
	'ag-portal-h':'Main Portal','ag-portal-p':'Full ecosystem overview',
	'ag-darwin-h':'Darwin Collection','ag-darwin-p':'20 evolutionary models',
	'ag-meta-h':'Metacognition Adapters','ag-meta-p':'11 non-invasive adapters',
	'ag-vkae-h':'VKAE Serving','ag-vkae-p':'1.5–2× throughput',
	'ag-jgos-h':'JGOS Citizen AI','ag-jgos-p':'Sovereign AI for 3.2M',
	'ag-national-h':'NationalOS v2','ag-national-p':'250-region digital twin',
	'ag-vision-h':'Darwin Vision','ag-vision-p':'Document & handwriting',
	'ag-material-h':'MaterialsOS','ag-material-p':'New-material AI design',
	'ag-admet-h':'ADMET','ag-admet-p':'Drug toxicity prediction',
	'ag-pharma-h':'PharmaOS DEEP','ag-pharma-p':'5-stage autonomous drug pipeline',
	'ag-pharma-h':'PharmaOS DEEP','ag-pharma-p':'Autonomous drug pipeline',
	'ag-quantum-h':'QuantumOS','ag-quantum-p':'Quantum sim console',
	'ag-qcrypto-h':'QuantumOS Crypto','ag-qcrypto-p':'Real HW cryptanalysis',
	'ag-qbench-h':'Quantum Bench','ag-qbench-p':'Quantum algorithm rankings',
	'ag-hansoo-h':'HanSoo (韓守)','ag-hansoo-p':'Fully local AI office',
	'ag-mouse-h':'MOUSE','ag-mouse-p':'Multi-agent code AI',
	'ag-chitos-h':'Chitos Security','ag-chitos-p':'AI code security scan',
	/* HF collections */
	'svc-hf-h':'HuggingFace <span>Collections & Models</span>','svc-hf-s':'Official collections managed under FINAL-Bench · VIDraft organizations.',
	'hf-portal-label':'VIDraft · Main Portal · Space','hf-portal-p':'Full introduction to the Darwin + AETHER ecosystem (KO/EN). Darwin 1.7B–398B · 11 patents · 9 live services · Blackwell 32-GPU infrastructure · metacognition tech overview.','hf-portal-btn':'Open Main Portal →',
	'hf-darwin-p':'Complete collection of 20 evolutionary language models from Darwin-2B to Darwin-398B. Linked with the arXiv 2605.14386 paper.',
	'hf-darwin-m1':'📦 20 models','hf-darwin-m2':'⬇️ 1M+ downloads',
	'hf-meta-h':'Metacognition Adapters','hf-meta-p':'11 non-invasive adapters that add self-error detection to major Darwin models without changing the original structure.',
	'hf-meta-m1':'📦 11 adapters','hf-meta-m2':'🧠 Non-invasive',
	'hf-vkae-h':'VKAE Collection','hf-vkae-p':'Inference-acceleration models achieving 1.5–2× throughput on a single GPU. OpenAI-compatible API.',
	'hf-vkae-m1':'⚡ 1.5–2×','hf-vkae-m2':'🔌 OpenAI-compatible',
	'hf-quantum-h':'Quantum Bench','hf-quantum-p':'Quantum computing algorithm performance leaderboard. Includes real IBM Heron QPU measurements.',
	'hf-quantum-m1':'⚛️ IBM Heron QPU','hf-quantum-m2':'📊 NIST 6/6',
	/* VKAE section */
	'svc-vkae-h':'VKAE <span>Inference Acceleration</span>','svc-vkae-s':'Achieves 1.5–2× throughput vs. baseline on a single GPU.',
	'vkae-hl-h':'⚡ 455 / 601 tok/s on a single B200 GPU','vkae-hl-p':'The VKAE breakthrough stack delivers 1.5–2× the throughput of standard serving for a 35B-A3B model on one B200 GPU.',
	'vkae-lb-tag':'Live Leaderboard',
	'vkae-lb-h':'VKAE Serving Leaderboard','vkae-lb-p':'Single-GPU serving speed rankings. Darwin · Qwen model throughput comparison. OpenAI-compatible API endpoint provided.',
	'vkae-docker-h':'Verified Docker Images','vkae-docker-p':'8 Docker images verified for K-AI leaderboard submission. Bake-in method (works without internet on the evaluation server). OpenAI-compatible API.',
	'vkae-d1':'Darwin-36B-Opus VKAE','vkae-d2':'Darwin-9B-NEG VKAE','vkae-d3':'JGOS-31B-Citizen VKAE','vkae-d4':'Darwin-398B-JGOS VKAE',
	'vkae-warn':'⚠️ Internal serving infrastructure — access requires an internal-network account.',
	/* gov */
	'svc-gov-h':'National & Government <span>AI Services</span>','svc-gov-s':'Public administration AI based on K-AI #1 model — Korean sovereign AI for 3.2M citizens.',
	'gov-jgos-tag':'K-AI #1 Model','gov-jgos-h':'JGOS — Jeonnam·Gwangju Citizen AI','gov-jgos-p':'Korean sovereign AI for 3.2M citizens. Administration · law · tourism · civil affairs · transport · culture · statistics · agriculture guidance. Analyzes 10+ file formats (HWP·PDF·Excel·images). Includes free citizen AI education. Based on JGOS-31B-Citizen.','gov-jgos-sub':'※ Test version · no official administrative effect',
	'gov-national-tag':'v2 · Digital Twin','gov-national-h':'NationalOS v2 — Regional Digital Twin','gov-national-p':'52M-person simulation based on KOSIS data. 250 cities/counties × 17 metropolitan regions, 3-tier analysis. Quick (10–30s) / Regional (1–3min) / Deep (5–15min) three stages. 9-Agent hallucination-prevention engine. Generates policy-impact interviews via persona matching.',
	/* pharma */
	'svc-pharma-h':'Drug & Materials <span>AI</span>','svc-pharma-s':'Polaris Global 14× Champion · From autonomous drug discovery to new material design.',
	'ph-vision-tag':'Vision AI','ph-vision-h':'Darwin-398B Vision','ph-vision-p':'FastAPI + Docker based. Connected to the Darwin-398B-AX production backend. Handwriting recognition · MSDS hazard extraction · health-checkup reading. KIHA SFR-004/001 industrial-safety demo. PDF·PNG·JPG·WEBP support.',
	'ph-material-tag':'Quantum-Integrated','ph-material-h':'MaterialsOS — New-Material AI Design','ph-material-p':'MatterGen→MLIP→UQ→4-DB novelty check→Hull→IBM Heron QPU cross-validation 7-gate pipeline. Generative AI + real QPU integration. Compatible with Korea IonQ/KISTI. Paper + patent linkage.','ph-material-sub':'※ Contact for access',
	'ph-admet-tag':'Polaris 14× Champion','ph-admet-h':'ADMET — Toxicity·Absorption·Metabolism Prediction','ph-admet-p':'Predicts 5 indicators: Absorption · Distribution · Metabolism · Excretion · Toxicity. Based on the Polaris global-leaderboard 14× champion model. BRICS molecule generation + Boltz-2 docking. tox21-v4 scaffold-holdout AUC 0.790.','ph-admet-sub':'※ Contact for access',
	'ph-pharma-tag':'Autonomous Drug','ph-pharma-h':'PharmaOS DEEP — 5-Stage Autonomous Pipeline','ph-pharma-p':'RAG→SMILES generation→CythoS validation→SOTA ranking→report. Covers 14 indications. Built-in autonomous retry loop.',
	/* quantum */
	'svc-quantum-h':'Quantum & Science <span>AI</span>','svc-quantum-s':'IBM Heron QPU measured · NIST randomness 6/6 passed · Real quantum experiment integration.',
	'q-os-tag':'Quantum Console','q-os-h':'QuantumOS — Quantum Simulation Console','q-os-p':'Quantum circuit design · simulation · execution. Visualizes real IBM QPU measurement data. NIST randomness (6/6 pass) · min-entropy 0.974 · Bell inequality violation (2.371) · VQE · QRAM experiments. Run directly in the #console tab.',
	'q-bench-tag':'Leaderboard','q-bench-h':'Quantum Bench Leaderboard','q-bench-p':'Quantum algorithm and simulator performance comparison leaderboard. Real QPU measurements shown side-by-side with simulation results. HF Docker metadata auto-updated. 27 likes.',
	/* tools */
	'svc-tools-h':'Tools & Security <span>AI</span>','svc-tools-s':'AI security, code agent, local office, legal AI — productivity tools collection.',
	'tl-hansoo-tag':'Data Sovereignty','tl-hansoo-h':'HanSoo (韓守) — Fully Local AI Office','tl-hansoo-p':'Browser-based, works without internet. Zero external data transmission. HWP·DOCX·PPT·XLSX·PDF support. MIT license. Released 2026.04.19.',
	'tl-mouse-tag':'Multi-agent','tl-mouse-h':'MOUSE — Code Agent','tl-mouse-p':'Multi-agent code AI. 1.5M+ MAU verified. Darwin-backbone swarm collaboration. SOMA multi-intelligence architecture.',
	'tl-chitos-tag':'AI Security','tl-chitos-h':'Chitos — Code Security Scanner','tl-chitos-p':'AI-based code security vulnerability detection. OWASP Top 10 · dependency analysis · secret-key exposure check. Darwin-backbone security fine-tuning.',
	'tl-legal-tag':'Legal AI','tl-legal-h':'Legal AI — Hallucination-Free','tl-legal-p':'Case-law-grounded accurate legal AI. RAG + Darwin legal fine-tuning removes legal hallucination.',
	/* blog */
	'blog-h1':'AI Insights, <span style="color:var(--ind)">fresh daily</span>',
	'blog-sub':'AI essays auto-written daily from news curated by VIDraft.',
	'blog-latest':'Latest Post',
	'blog-more-h':'More Reading','blog-more-p':'AI insights · technology philosophy · industry analysis from VIDraft\'s CEO',
	'blog-more-btn':'Read more on Brunch @seawolf →',
	/* papers */
	'paper1-p':'MRI-Trust-Weighted Evolutionary Merging for Training-Free Scaling. 45 days after release: 300K+ downloads, 500 derivatives.',
	'paper2-p':'Measuring Functional Metacognitive Reasoning in LLMs. MetaCog scaffold +14.05 pts. 94.8% Error Recovery. Under conference review.',
	'paper3-p':'The sole WM-passing world model v1.0. 263-joint skeleton. Track C 726 pts Grade B 47 FPS.',
	'paper4-p':'Model-Agnostic Runtime Middleware for LLMs. Reduces GPT/Claude/Gemini hallucination by 70%+. One line of code.',
	'paper-link':'View Paper →',
	/* all-grid extras */
	'ag-vkaelb-p':'Single-GPU speed','ag-docker-p':'8 images',
	/* tools extras */
	'tl-paper-tag':'Research Tool','tl-paper-h':'Auto Paper Generator','tl-paper-p':'AI paper writing & enhancement agent. Automates draft generation, reference organization, and improvement suggestions.',
	'tl-galaxy-tag':'Model Explorer','tl-galaxy-p':'22,400+ model sigma.js interactive visualization. Darwin·Trending·Multimodal 5 clusters. Galaxy / Atlas 2 modes.',
	/* blog cards */
	'bc2-tag1':'K-AI Leaderboard','bc2-tag2':'Darwin Platform',
	'bc2-title':'11 in the Top 20 — Darwin Platform Takes Over the K-AI Leaderboard',
	'bc2-desc':'11 models generated and derived from the Darwin Platform are in the K-AI Leaderboard Top 20. This isn\'t the lucky success of a single model — it\'s a signal that a system for repeatedly building and deriving models is working.',
	'bc2-s1':'in Top 20','bc2-s2':'HF downloads','bc2-s3':'patents filed',
	'bc2-link1':'K-AI Leaderboard →','bc2-link2':'Intro Video ▶',
	'bc3-tag1':'Inference Acceleration',
	'bc3-title':'Building One More GPU — Without Building a GPU',
	'bc3-desc':'Inference acceleration extracts more work from the same chip through software. VKAE (VIDRAFT Kernel Acceleration Engine) recorded up to 23.4× higher throughput than the conventional approach on the same GPU. Fast, with quality intact.',
	'bc3-s1':'B200 throughput','bc3-s2':'tok/s (batched)','bc3-link':'VKAE Leaderboard·Demo →',
	'bc4-tag1':'Security AI',
	'bc4-title':'It Doesn\'t Stop at \'Suspecting\' a Vulnerability — CHITOS Autonomous Security AI',
	'bc4-desc':'Chitos doesn\'t drop a finding straight into the report. Within authorized scope, it verifies directly, confirms reproducibility, and links attack paths into a kill chain. 3 stages: static scan → threat research → active exploit verification.',
	'bc4-env':'Test environment:','bc4-env2':'(IBM-authorized vulnerable demo site)','bc4-link':'Try CHITOS free →',
	'bc5-tag1':'Drug Discovery AI','bc5-tag2':'Polaris 14× Champion',
	'bc5-title':'AI That Reads Drugs First — Polaris Global 14× Champion',
	'bc5-desc':'#1 worldwide on 14 benchmarks across 5 fields: efficacy · solubility · toxicity · oncology kinase · ADME.',
	'bc5-cat1':'💊 Efficacy Prediction','bc5-cat2':'💧 Solubility','bc5-cat3':'☠️ Toxicity Prediction','bc5-cat4':'🎯 Oncology Kinase Target Prediction','bc5-cat5':'🔬 Druggability·ADME Prediction',
	'bc5-b1':'How strongly a drug binds its target','bc5-b2':'Dopamine D3 receptor binding efficacy','bc5-b3':'How well a drug dissolves in water','bc5-b4':'Drug-induced liver injury prediction','bc5-b5':'DNA mutation & carcinogenicity prediction','bc5-b6':'EGFR + L858R mutation inhibition','bc5-b7':'EGFR inhibition prediction','bc5-b8':'EGFR reclaim leaderboard','bc5-b9':'EGFR mutation classification','bc5-b10':'LOK·SLK kinase inhibition','bc5-b11':'KIT mutation inhibition','bc5-b12':'How much of an oral drug reaches the bloodstream','bc5-b13':'How widely a drug distributes in body tissue','bc5-b14':'CYP2D6 enzyme metabolism & drug interaction','bc5-link':'Full Polaris Leaderboard →',
	/* footer */
	'ft-addr':'VIDRAFT Inc.<br>175 Nonhyeon-ro, Seocho-gu, Seoul · Shinhan Bldg. 7F<br>Business Reg. 879-87-03063 · ArXivGPT@gmail.com',
	'ft-tech':'Technology','ft-achieve':'Achievements','ft-services':'Key Services',
	'ft-paper':'Darwin Family Paper','ft-bench':'Benchmarks','ft-patents':'Patents (11)','ft-press':'Press Coverage','ft-meta':'Metacognition Adapters',
	'ft-svc-jgos':'JGOS Citizen AI','ft-svc-admet':'ADMET Drug Prediction',
	'ft-copy':'© 2026 VIDRAFT Inc. All rights reserved.','ft-tag':'Pre-AGI · Darwin · AETHER · Korea AI #1',
	'nav-company':'Company','co-badge':'MEET THE CREW','co-h1':'Our Grand Alliance<br><span style="color:var(--ind)">11 Legends Running The Ship</span>','co-sub':'Eleven crew members running this ship together.',
	/* team */
	'nav-team':'Team',
	'team-badge':'MEET THE CREW','team-h1':'Our Grand Alliance<br><span style="color:var(--ind)">11 Legends Running The Ship</span>','team-sub':'Seven realms · one flag · eleven legends running the ship.',
	'tc-1-role':'CHAIRMAN','tc-1-q':'What we build today becomes the future of humanity.',
	'tc-2-role':'CEO','tc-2-q':'Optimism is our strategy. Conviction is our asset.',
	'tc-3-role':'COO','tc-3-q':'The chairman may shout, but this ship’s course never wavers.',
	'tc-4-role':'CFO','tc-4-q':'Cold numbers. Warm team.',
	'tc-5-role':'CIO','tc-5-q':'Every route in this ocean, mapped without a chart.',
	'tc-6-role':'HEAD OF R&D','tc-6-q':'Quiet at his post. Answers with results.',
	'tc-7-role':'CTO','tc-7-q':'When the CEO sleeps, he sleeps. When the CEO codes, he codes.',
	'tc-8-role':'INTERN','tc-8-q':'Until the day I become a full crew member — I will keep learning.',
	'tc-9-role':'INTERN','tc-9-q':'Don’t compliment me! (secretly overjoyed)',
	'tc-10-role':'CMO','tc-10-q':'One business card comes with an entire kingdom attached.',
	'tc-11-role':'JAPAN HEAD','tc-11-q':'The one samurai bridging Japan and the world.'
	},
	ko:{
	/* title + nav */
	'page-title':'VIDRAFT — Pre-AGI 모델 개발 전문 비드래프트',
	'nav-models':'모델',
	'mdl-sub':'Darwin 계보(2026-03-31 출시 이후)의 모든 모델 — 공식 배포본과 커뮤니티 파생 모델을 누적(all-time) 다운로드로 집계했습니다.',
	'mdl-note-lbl':'누적(all-time) 다운로드 기준 · 허깅페이스 기본 표시는 최근 30일만 · 갱신',
	'mdl-off-h':'공식 <span>모델</span>',
	'mdl-off-s':'VIDraft · FINAL-Bench 공식 배포.',
	'mdl-com-h':'커뮤니티 <span>모델</span>',
	'mdl-com-s':'커뮤니티가 Darwin을 기반으로 만든 양자화·파인튜닝·파생 모델.',
	'mdl-st-total':'총 모델 수','mdl-st-var':'파생 변형 (양자화 포함)',
	'mdl-st-dl':'누적 다운로드',
	'mdl-st-off':'공식 (VIDraft·FINAL-Bench)',
	'mdl-st-com':'커뮤니티 파생',
	'mth-model':'모델',
	'mth-type':'유형',
	'mth-created':'생성일',
	'mth-dl':'누적 DL',
	'oth-h':'기타 <span>모델</span>',
	'oth-s':'VIDraft·FINAL-Bench의 주요 non-Darwin 모델.',
	'dkr-h':'🐳 Docker <span>이미지</span>',
	'dkr-s':'Docker Hub(vidraft)의 배포용 컨테이너.',
	'spc-h':'라이브 <span>데모</span>',
	'spc-s':'Hugging Face Spaces 인터랙티브 데모(좋아요 상위).',
	'dts-h':'📊 <span>데이터셋</span>',
	'dts-s':'VIDraft·FINAL-Bench가 공개한 벤치마크·데이터셋.',
	'dth-img':'이미지',
	'dth-desc':'설명',
	'dth-pulls':'Pulls',
	'dts-th':'데이터셋',
	'mth-updated':'업데이트',
	'dash-kicker':'라이브 생태계 대시보드',
	'dash-title':'한눈에 보는 Darwin <span>생태계</span>',
	'dash-upd':'갱신',
	'ch-top':'공식 모델 다운로드 TOP',
	'ch-mo':'모델 릴리스 모멘텀 (2026)',
	'ch-gpqa':'GPQA Diamond — Darwin 패밀리',
	'ch-eco':'다운로드 출처 분포',
	'kpi-kai':'K-AI 리더보드 (한국)',
	'kpi-gpqa':'GPQA Diamond 최고기록',
	'kpi-models':'Darwin 모델',
	'kpi-dl':'누적 다운로드',
	'kpi-spaces':'라이브 데모 (Spaces)',
	'kpi-datasets':'데이터셋',
	'src-com':'커뮤니티',
	'src-ds':'데이터셋',
	'src-oth':'기타 모델',
	'src-off':'공식',
	'press-h':'<span>언론</span> 보도',
	'press-s':'국내 주요 IT 매체의 비드래프트 보도.',
	'proof-allpress-h':'전체 <span>언론 보도</span>',
	'proof-allpress-s':'매체 보도 + 창업자 기고 전체 아카이브 — 자동 갱신.',
	'pol-kicker':'Polaris Hub · 글로벌 신약발굴 ML 벤치마크',
	'pol-h':'14개 벤치마크 1위 — ADMET · 효능 · 키나아제',
	'pol-desc':'세포영상·외부 실험데이터 없이 분자 구조 정보만으로, 흡수·분포·대사·배설·독성·효능·키나아제 선택성에 걸친 공개 Polaris 리더보드 14개에서 1위.',
	'pol-1p':'세포영상 등 외부 데이터를 쓴 2위(0.868)를 분자 구조만으로 추월.',
	'pol-2p':'약물유발 간독성 분류 (ROC-AUC).',
	'pol-3p':'대사 예측 — 3D 형상 특징으로 기존 1위 모델 추월.',
	'pol-4p':'AqSolDB 용해도 회귀 — 기존 천장 첫 돌파.',
	'pol-5p':'결합친화도(효능) — 기존 최고 대비 큰 격차.',
	'pol-6p':'EGFR 회귀 — 기존 최고 대비 전 지표 추월.',
	'pol-link':'리더보드 →',
	'pol-note':'모든 결과는 공개 블라인드 제출 리더보드의 계산 예측이며 VIDraft 계정으로 제출되었습니다. 최근 비드래프트는 이 자율 발견 AI 시스템으로 첫 신약 물질 특허를 출원했습니다.',
	'nav-quantum':'양자',
	'q-h1':'실제 양자 하드웨어 위의 암호분석',
	'q-sub':'IBM 156큐빗 ibm_kingston에서 Simon 알고리즘 공격을 실행 — 기록적 하드웨어 규모.',
	'q-story-h':'세계가 "4"에서 멈춘 자리, 한국의 작은 팀은 "10"까지 갔다.',
	'q-story-p1':'로켓을 종이에 그리는 것과 실제로 쏘아 올리는 것은 완전히 다른 일이다. 실제 양자컴퓨터는 잡음투성이라, 계산이 조금만 길어져도 답이 잡음에 파묻힌다. 그래서 실물 기계의 공개 기록은 몇 년째 N≈4 언저리에 멈춰 있었다.',
	'q-story-p2':'비드래프트는 그 벽에 손을 댔다. 가장 취약한 두 구조 — Even–Mansour와 Feistel — 을 IBM의 진짜 양자컴퓨터에 올려, 가장 단순한 블록암호 구조를 N=5, 6, 7, 8, 9, 그리고 10까지 밀어 올렸다. 매번 전혀 다른 두 번째 열쇠를 나란히 복원해 미리 답을 알고 짜맞춘 눈속임이 아님을 스스로 증명했다 — 값비싼 오류정정 없이, 잡음을 다독이는 기법만으로.',
	'q-btn1':'라이브 데모 →',
	'q-btn2':'리더보드 →',
	'q-hw-h':'실 <span>하드웨어</span> 성과',
	'q-hw-s':'IBM ibm_kingston (156큐빗) · 15~30큐빗 회로, 수백 개의 2큐빗 게이트.',
	'q-hw1':'실제 하드웨어에서 N=5부터 N=10까지 비밀키 복원 — 기존 공개기록 N≈4를 (아는 한) 넘어섰습니다.',
	'q-hw2':'블록 크기 6·8에서 은닉 주기 복원, rank-1 클린.',
	'q-hw-note':'오류완화만 적용 — 동적 디커플링·게이트/측정 트월링·판독오류 보정(양자오류정정 아님). 인스턴스별 독립 대조키로 특정 정답에 맞춘 것이 아님을 검증.',
	'q-sim-h':'5대 <span>공격 구조</span>',
	'q-sim-s':'주요 암호 설계 패러다임을 아우르는 진짜 양자 알고리즘. Simon 기반 2종을 하드웨어로 실행.',
	'q-s1':'선형 암호는 단 한 번의 질문에 비밀을 통째로 들킨다 — 가장 허무한 붕괴.',
	'q-s2':'실제 하드웨어 실행 ✓',
	'q-s3':'열쇠를 전부 넣어보는 수고가 제곱근만큼 줄어든다 — AES가 키를 더 길게 만들어야 하는 바로 그 위협.',
	'q-s4':'메시지 인증코드가 열쇠 없이도 위조된다.',
	'q-s5':'실제 하드웨어 실행 ✓',
	'q-honest-h':'⚠️ 정직한 범위',
	'q-honest':'이는 기록적 규모의 하드웨어 실증이며 — 실용적 양자 가속이 아니고(유효 난이도는 여전히 고전 생일한계 ~2^(n/2)를 따름), AES / RSA / 16라운드 DES 파괴가 아니며, 양자오류정정 기반이 아닙니다(NISQ 완화만). 세계 최초 여부는 피어리뷰 전으로 미확정입니다.',
	'nav-chitos':'치토스',
	'ch-h1':'의심에서 증명으로',
	'ch-sub':'대부분의 스캐너는 패턴을 찾아 "취약점일 수도 있으니 개발자가 확인하세요"라고 말합니다. 치토스는 허가된 대상 안에서 직접 검증하고, 재현 가능성을 확인하며, 공격 경로를 하나의 시나리오로 연결합니다.',
	'ch-btn1':'무료로 사용 →',
	'ch-flow-h':'3단계 <span>동작</span>',
	'ch-flow-s':'VIDRAFT 전작 미토스(Mythos)를 계승. 미토스가 정적 분석이었다면, 치토스는 검증합니다.',
	'ch-s1-t':'1단계 · 정적 스캔 (무료)',
	'ch-s1-h':'다중 언어 패턴 분석',
	'ch-s1-p':'Python·JS·Go·Java·C/C++·Rust·PHP·YAML — 인젝션 싱크·역직렬화·자격증명 노출·암호화 오용·프로토타입 오염·공급망 위험 탐지. 증명되지 않은 경고는 소음으로 걸러냅니다.',
	'ch-s2-t':'2단계 · 자율 위협 연구',
	'ch-s2-h':'자율 맥락 조사',
	'ch-s2-p':'CVE 데이터베이스·익스플로잇 권고문·공개 PoC를 교차 조사해 현재 위협 환경에서 왜 위험한지 설명합니다. (Claude API 키 필요)',
	'ch-s3-t':'3단계 · 능동 검증 (무료)',
	'ch-s3-h':'재현 가능한 익스플로잇 증거',
	'ch-s3-p':'허가된 대상에 한해 — XSS·SQL 인젝션·경로 순회·명령 삽입. 재현 가능한 증거를 찾고, 차단되면 변형 경로를 시도하며, 확인된 취약점을 킬체인 위협 지도로 연결합니다.',
	'ch-ex-h':'바로 실행 <span>시나리오</span>',
	'ch-ex-s':'5가지 대표 공격 시나리오, 각 한 번의 클릭. IBM의 의도적 취약 데모 demo.testfire.net에서 라이브 검증.',
	'ch-priv-h':'🔒 설계부터 프라이버시',
	'ch-priv-p':'설치 없음. 회원가입 없음. 코드는 외부 API로 전송되지 않습니다.',
	'ch-legal-h':'⚖️ 허가된 대상만',
	'ch-legal-p':'능동 익스플로잇 기능은 본인이 소유했거나 명시적으로 허가받은 대상에만 사용해야 합니다. 무단 테스트·스캔은 불법일 수 있으며, 모든 법적 책임은 사용자에게 있습니다.',
	'nav-vkae':'VKAE',
	'nav-solutions':'솔루션',
	'nav-about':'회사',
	'ab-h1':'지능은 창조하는 것이 아니라, 육성하는 것입니다.',
	'ab-sub':'2024년 시작한 한국의 Proto-AGI 스타트업. 한 가지 믿음 — 과장하지 않고, 검증된 것만 말한다.',
	'ab-phil-h':'우리의 <span>철학</span>',
	'ab-phil-s':'위대한 생명은 누가 한 번에 설계한 것이 아닙니다. 씨앗 → 새싹 → 나무 → 숲. AGI도 억지로 만드는 것이 아니라 자연의 이치대로 육성합니다.',
	'ab-p1-tag':'창조 아닌 육성','ab-p1-h':'기르다','ab-p1-p':'지능을 한 번에 거대하게 만들지 않습니다. 자연이 위대한 생명을 진화시키듯, 세대를 거쳐 기릅니다. 씨앗 → 새싹 → 나무 → 숲.',
	'ab-p2-tag':'정직과 검증','ab-p2-h':'정직과 검증','ab-p2-p':'창업 정신 — 과장하지 않고 검증된 것만 말한다. 진짜 신뢰는 "하지 못한 것"을 솔직히 말하는 데서 나옵니다.',
	'ab-p3-h':'진화로 기른다','ab-p3-p':'서로 다른 모델의 장점을 교배시켜 더 강한 다음 세대를 기릅니다 — 장인이 대를 잇듯, 지능의 계보를 잇습니다.',
	'ab-p4-h':'다양성의 조화 (和)','ab-p4-p':'하나의 방식이 아닙니다 — 5·7·11종의 서로 다른 어텐션이 공존합니다. 다양성이 조화될 때 더 높은 지능이 깨어납니다. 트랜스포머 너머를 보는 방법입니다.',
	'ab-p5-h':'다음 시대의 토양 (道)','ab-p5-p':'양자컴퓨터를 "완성"했다고 말하지 않습니다. 다음 시대가 올 토양을 일굽니다. 실제 하드웨어 위에서 한 걸음씩 검증하며 나아갑니다. AGI는 목적지가 아니라 길입니다.',
	'ab-p6-tag':'사람을 위한 기술','ab-p6-h':'철학을 대지에','ab-p6-p':'사람과 사회를 위한 기술 — Society 5.0과 같은 꿈. 전남·광주(320만 시민)에서 국경을 넘어.',
	'ab-hist-h':'주요 <span>연혁</span>',
	'ab-team-h':'우리 <span>크루</span>',
	'ab-team-s':'자유·유연함·속도·창의로 무장한 열한 명 — 낭만 해적처럼.',
	'ab-team-q':'🏴‍☠️ "Join My Crew?" — 우리는 스스로를 조마크라 부릅니다.',
	'ab-team-qs':'비드래프트 구성원에게 정체성을 물으면 우리는 모두 "조마크"라 답합니다 — 만화 원피스에서 딴 크루의 콜사인. 자원이 아니라 머리로, 물량이 아니라 뚝심과 기민함으로.',
	'ab-t1-h':'열한 명의 크루','ab-t1-p':'물량을 방법으로 이기는 단단한 팀 — GPU 24장으로 거인들과 겨룹니다.',
	'ab-t2-h':'수직 통합','ab-t2-p':'자체 LLM · 도시 OS · 신약/소재 AI · 온프레미스 AI — 대표이사·부사장·일본사업본부장이 Proto-AGI 스택을 이끕니다.',
	'ab-t3-h':'Join My Crew','ab-t3-p':'다음 글로벌 AI 해적을 찾습니다 — 자유·속도·창의. 문의 환영.',
	'sol-h1':'Sovereign AI OS — 데이터가 망 밖으로 나가지 않는다',
	'sol-sub':'AI 챗봇 하나가 아니라, 행정·시민·산업 데이터를 독립망 안에서 안전하게 연결하는 AI 운영체계.',
	'sol-btn1':'파일럿 도입 문의 →',
	'sol-gov-h':'공공 · 지자체 <span>AX</span>',
	'sol-gov-s':'행정 과부하 · 데이터 파편화 · 클라우드 AI 보안 우려 → 지역 내부 Sovereign AI 운영체계.',
	'sol-c1-h':'지역 전용 LLM','sol-c1-p':'지역별 언어 · 행정 · 산업 특화 모델.',
	'sol-c2-h':'근거·자기검증','sol-c2-p':'환각 억제 · 자기 검증 · 근거 기반 응답.',
	'sol-c3-h':'정책 시뮬레이션','sol-c3-p':'지역 디지털 트윈 위 정책 · 예산 · 산업 시뮬레이션.',
	'sol-c4-h':'AI 공통 접점','sol-c4-p':'시민 · 공무원 · 기업이 함께 쓰는 AI 접점(CHITOS 포털).',
	'sol-c5-h':'Pharma · Material · Nutri · Legal','sol-c5-p':'지역 OS에 결합되는 수직 도메인 AI.',
	'sol-c6-h':'데이터는 내부에','sol-c6-p':'온프레미스 · 독립망 배포, 3개월 KPI 파일럿으로 검증.',
	'sol-c7-h':'Building — 건축 설계 AI','sol-c7-p':'자연어→KS 표준 평면도(DXF·BIM·적산·소방검토), 지번→법규 준수 건물 3D 매싱(용적률 슬라이더·일조사선·실사 조감도)까지 — 설계 검토의 전 과정을 몇 분으로.',
	'svc-tab-building':'건축·설계','ag-floorplan-h':'FloorPlan AI','ag-floorplan-p':'자연어 → KS F 1501 도면',
	'svc-building-h':'FloorPlan AI <span>건축설계 자동생성</span>','svc-building-s':'한글 한 문장으로 검증된 평면도를 — 지번 하나로 법규 준수 건물 3D를. 도면·BIM·적산·소방검토까지 몇 분 만에.',
	'svc-building-s2':'자연어가 KS F 1501 도면·3D·걷기모드·물량산출로 — 397B MoE가 설계하고 VLM 비평가가 검수합니다.',
	'svc-fp1-h':'자연어 → 표준 평면도','svc-fp1-p':'한글 설명이 KS F 1501 도면으로(초안 병렬설계+AI검수) — mm·1:100·벽체 포셰·면적표.',
	'svc-fp2-h':'자동 검증 6종','svc-fp2-p':'건축법 · 소방·화재안전 · BF 무장애 · 설계지표 · 개산 공사비 · AI 검수 점수.',
	'svc-fp3-h':'지번 → 대지 설계','svc-fp3-p':'지번만 입력하면 용도지역·개별공시지가·대지 경계를 국토교통부 V-World 공공데이터로 자동 조회.',
	'svc-fp4-h':'용적률 슬라이더 + 정북 일조사선 3D','svc-fp4-p':'건폐율·용적률 법정 상한을 기하로 강제, 정북 일조사선을 3D 매스에 절단 적용, 슬라이더로 연면적·층수·공사비 실시간 재계산.',
	'svc-fp5-h':'공간배치 품질 점수','svc-fp5-p':'조닝·프라이버시·남향·동선·비례를 규칙 기반 0~100점 산출 — AI 자가평가가 아닌 결정론 점수.',
	'svc-fp6-h':'내보내기 DXF·PDF·IFC·적산','svc-fp6-p':'DXF(AutoCAD) · PDF(A3 시트) · IFC(BIM) · XLSX 물량산출/적산.',
	'svc-fp7-h':'걷기 · 일조 · 실사 조감도','svc-fp7-p':'1인칭 걷기 모드, 월/시각별 일조 시뮬, AI 실사 렌더·조감도.',
	'svc-fp-disc':'※ AI 개념설계 참고용 — 건폐율·용적률은 법정 상한 기준(실제 한도는 지자체 조례 확인 필요), 공시지가는 시세가 아니며, 인허가·시공 도서는 건축사와 진행합니다.',
	'svc-fp-cta1':'FloorPlan AI 열기 →','svc-fp-cta2':'소개 글 보기 (브런치) →',
	'sol-pkg-h':'5대 AX 패키지',
	'sol-p1':'행정','sol-p2':'시민','sol-p3':'산업','sol-p4':'바이오','sol-p5':'소재',
	'sol-case-h':'실증 구축 — <span>서울 인공지능·로봇 과학관</span>',
	'sol-case-s':'비드래프트가 구축해 시민에게 운영 중인 전시 3건.',
	'sol-r1-tag':'피지컬 AI','sol-r1-h':'스팟과 대화하기','sol-r1-p':'보스턴다이내믹스 스팟을 자연어 음성으로 제어 — LLM으로 로봇과 대화하고 명령·조종한다.',
	'sol-r2-tag':'해석가능성','sol-r2-h':'모델 X-RAY','sol-r2-p':'LLM 블랙박스 내부를 들여다본다 — 모델 내부 작동을 관람객에게 투명하게 보여주는 X-RAY.',
	'sol-r3-tag':'진화','sol-r3-h':'다윈 교배·진화','sol-r3-p':'AI 모델이 교배·진화하는 과정을 직접 본다 — 자식이 부모를 뛰어넘는다. 인터랙티브 다윈 진화 체험.',
	'v-h1':'GPU를 만들지 않고, GPU를 한 대 더 만든다',
	'v-sub':'VKAE(VIDRAFT Kernel Acceleration Engine)는 이미 가진 GPU에서 처리량을 몇 배로 끌어올립니다 — 커널 레벨 최적화, 답변 품질은 그대로.',
	'v-btn1':'리더보드 & 데모 →',
	'v-btn2':'Docker →',
	'v-k1':'처리량 (일반 방식 대비, NVIDIA B200)',
	'v-k2':'초당 토큰 (다중 요청 시)',
	'v-k3':'품질 저하 — 같은 답, 더 빠르게',
	'v-k4':'재현 가능 — 도커 하나, 당신의 GPU',
	'v-why-h':'추론 가속이 <span>필수재</span>인 이유',
	'v-why-s':'AI 인프라의 진짜 승부처는 모델을 만드는 순간이 아니라, 그 모델을 계속, 싸게 돌리는 순간입니다.',
	'v-w1-t':'효율 = 용량',
	'v-w1-h':'가상의 GPU 증설',
	'v-w1-p':'GPU는 귀하고 비싸고 전기를 먹습니다. 같은 카드에서 처리량을 두 배로 올리면 인프라를 두 배 지은 것과 같습니다 — 새 칩도, 새 전력도 없이.',
	'v-w2-t':'토큰당 단가',
	'v-w2-h':'AI 서비스의 손익',
	'v-w2-p':'학습은 한 번이면 끝나지만 추론은 사용자가 쓰는 내내 발생합니다. VKAE는 서비스의 흑자 여부를 가르는 토큰당 단가를 직접 낮춥니다.',
	'v-w3-t':'소버린 AI 대응',
	'v-w3-h':'없으면 적자',
	'v-w3-p':'클라우드·AI 스타트업·기업·국가 단위 AI(소버린 AI)에게 추론 가속은 선택이 아닙니다 — 없으면 대규모 AI 운영이 적자입니다.',
	'v-repro-h':'🔬 주장이 아닌 재현',
	'v-repro-p':'속도 자랑은 흔합니다. VKAE는 모델 가중치와 최적화된 서빙 환경을 하나의 도커 컨테이너로 공개하고 OpenAI 호환이라, 누구나 자신의 GPU에서 직접 재현하고 기존 서비스에 바로 연결할 수 있습니다.',
	'v-l1':'허깅페이스에 공개된 VKAE 가속 모델 가중치.',
	'v-l2':'통합 컨테이너 — 가중치 + 최적화 서빙, OpenAI 호환.',
	'nav-home':'홈','nav-proof':'성과','nav-services':'서비스','nav-blog':'블로그','nav-spot':'🤖 스팟과 대화하기','spot-cap':'보스턴 다이내믹스 Spot에 비드래프트 온디바이스 VLM — 음성 명령·대화',
	/* hero */
	'hero-badge':'🇰🇷 K-AI 종합 1위 · GPQA Diamond 90.9% · Polaris 14관왕 · KAIT GPU지원 우수',
	'hero-h1':'진화하는 AI.<br><span>사고하는 AGI.</span>',
	'hero-sub':'한국에서 만든 Pre-AGI 플랫폼 — Darwin이 결과를 만들고, AETHER가 미래를 설계합니다.',
	'hero-btn1':'Darwin 모델 보기 →','hero-btn2':'전체 서비스 →',
	/* stats */
	'stat-gpqa':'GPQA Diamond 최고 기록','stat-dl':'HuggingFace 누적 다운로드',
	'stat-dl-num':'100만+','stat-patent-num':'11건',
	'stat-model':'커뮤니티 파생 모델','stat-patent':'특허 출원 (국내+PCT)',
	/* home sections */
	'home-news-h':'최신 <span>성과</span>','home-news-s':'2026년, 비드래프트가 달성한 주요 성과입니다.',
	'home-agi-h':'AGI를 향한 <span>여정</span>','home-agi-s':'AGI는 단계적으로 달성됩니다. 비드래프트는 지금 Pre-AGI 단계에 있습니다.',
	'home-sys-h':'4계층 통합 <span>시스템</span>','home-sys-s':'단일 모델이 아닌 네 계층의 유기적 통합으로 Embodied AGI를 설계합니다.',
	/* KAIT box */
	'kait-date':'2026.6 · KAIT 과제 평가',
	'kait-ref':'접수번호 RQT-25-090162',
	'kait-title':'「AI 컴퓨팅 자원 활용 기반 강화(GPU 임차지원)」 과제 평가 — <span style="color:var(--em)">\'우수\'</span>',
	'kait-desc':'한국정보통신진흥협회(KAIT) 주관 · GPU 임차지원 사업 과제 평가 <strong>우수</strong> 판정.',
	'kait-badge':'우수',
	/* news cards */
	'news1-media':'이데일리','news1-title':'Darwin-398B-JGOS, GPQA Diamond 90.9%',
	'news1-desc':'198문항 중 180개 정답. 순수 추론만으로 세계 최고 수준 달성. MoE + Darwin V9 방식.',
	'news2-media':'서울신문','news2-title':'JGOS-31B-Citizen, K-AI 리더보드 종합 1위',
	'news2-desc':'과기부·NIA 공인 평가 0.621점 1위. 상위 12개 중 Darwin 계열 8개(67%) 점유.',
	'news3-media':'텐센트 뉴스','news3-title':'중국 최대 포털 텐센트, 비드래프트 ‘Darwin’ 조명',
	'news3-desc':'중국 최대 포털이 비드래프트 Darwin 패밀리 조명 — “훈련 없이 유전자 재조합으로 AI 능력 도약”.',
	'news-link':'기사 보기 →',
	/* AGI stages */
	'agi-p1':'단일 작업 특화','agi-p2':'다중 작업 결합',
	'agi-p3':'메타인지 + 자기교정 + 군집협업',
	'agi-now':'▶ 현재','agi-p4':'진성 AGI','agi-p5':'초월 AGI',
	/* layer cards */
	'layer-darwin-p':'진화형 모델 패밀리. K-AI 1위 + GPQA 90.9%',
	'layer-aether-p':'5/7/11종 이종 어텐션 Pre-AGI 아키텍처',
	'layer-prom-p':'월드 모델. WM Bench Track C 유일 통과 (726점)',
	'layer-heph-p':'Embodied AI · Jetson 4종 운영 검증',
	'layer-chain':'LLM → AETHER → PROMETHEUS → HEPHAESTUS = <strong style="color:var(--ind)">Embodied AGI</strong>',
	/* video */
	'vid-h':'비드래프트 소개 영상',
	'vid-p':'Darwin 플랫폼과 AETHER의 기술적 혁신을 영상으로 확인하세요.',
	/* darwin leaderboard */
	'darwin-h1':'측정 가능한 결과를 만드는 한국 AI 1위 플랫폼',
	'darwin-sub':'K-AI 종합 1위 · GPQA Diamond 90.9% · Polaris 글로벌 14관왕 · 메타인지 리더보드 1위',
	'darwin-tab1':'📊 리더보드 성과','darwin-tab2':'🧬 모델 패밀리','darwin-tab3':'🧠 메타인지',
	'darwin-gpqa-h':'GPQA Diamond <span>글로벌 리더보드</span>','darwin-gpqa-s':'HuggingFace 공인 · 2026년 6월 기준',
	'darwin-kai-h':'K-AI <span>리더보드</span>','darwin-kai-s':'과기부·NIA 공인 · 블라인드 평가 · 2026년 6월 기준',
	'darwin-models-h':'Darwin <span>공식 모델 패밀리</span>','darwin-models-s':'공식 20+종 · 파생 변형 1,200+종(양자화 포함) · 누적 100만+ 다운로드 (허깅페이스 실측 2026-07)','m-9bneg-p':'9B NEG 단발 진화. Darwin 패밀리 최다 다운로드 — 누적 57.5만+.','m-36bopus-p':'GPQA Diamond 88.4%. 커뮤니티가 가장 많이 양자화·재배포한 플래그십.','m-31bopus-p':'한국어 플래그십. CLIcK 84.5 · KMMLU 76.','m-coder-p':'코딩 특화. Darwin 공식 GGUF 다운로드 1위.','darwin-dl-note':'⬇️ = 허깅페이스 누적(all-time) 다운로드 (공식＋커뮤니티 재배포 합산), 2026-07 실측. Darwin 패밀리 총 100만+.',
	'darwin-lb-kai':'K-AI 리더보드 종합 1위<br><small>JGOS-31B-Citizen 0.621</small>',
	'darwin-lb-pol-n':'14관왕','darwin-lb-pol':'Polaris 글로벌 신약개발<br><small>ADMET + 효능 + 키나아제</small>',
	'th-rank':'순위','th-model':'모델','th-score':'점수','th-note':'비고','th-cat':'분류',
	'tag-vid-latest':'비드래프트 최신','tag-vid':'비드래프트','tag-vid-official':'비드래프트 공식','tag-darwin-der':'Darwin 파생',
	'darwin-kai-hl-h':'📊 K-AI 20위권 중 11개가 Darwin 계열',
	'darwin-kai-hl-p':'과기부·NIA 블라인드 평가에서 자연 발생한 결과입니다. 자체 신고가 아닌 제3기관 공인 수치입니다.',
	/* darwin models */
	'm-jgos398-p':'MoE 구조, 활성 파라미터 170억. Darwin V9 방식. 순수 추론 세계 최고 수준.',
	'm-darwin28-p':'GPQA Diamond 88.89%. 추가 학습 없이 400B급 능가. arXiv 2605.14386.',
	'm-jgos31-p':'공공·행정 특화 한국어. CLIcK 0.987 · KMMLU-Pro 0.725 · Com2 0.742.',
	'm-david-p':'4.5B로 31B급 달성. GPQA 85.0%. 누적 +26.4%p. 체화 AI·모바일 적합.',
	'm-genesis-p':'Transformer × Mamba 이기종 교배. CLIcK 92%. 세계 최초 이종 교배 검증.',
	'm-tts-p':'1.7B 한국어 음성합성. Cross-architecture 진화.',
	'm-35b-p':'35B MoE 플래그십. GPQA Diamond 90.0%. 멀티모달 지원.',
	'm-legal-p':'27B BF16 법률 특화. B200 로딩 9.7s. TPS 22.3 tok/s.',
	'm-reason-p':'추론 능력 강화 특화 모델. 수학·코드·과학 추론 최적화.',
	'darwin-coll-p':'HuggingFace FINAL-Bench 컬렉션에서 20종 전체를 확인하고 다운로드할 수 있습니다.',
	'darwin-coll-btn':'Darwin Family 컬렉션 보기 →',
	/* darwin metacognition */
	'darwin-meta-h':'메타인지 <span>리더보드</span>','darwin-meta-s':'지니젠AI · 비드래프트 공동 개발 · 24개 AI 모델 평가 · 2026.07.01 공개',
	'meta-quote':'🧠 "AI가 위험한 것은 오류를 범할 때가 아니라, 오류를 범했는지 모를 때입니다"',
	'meta-quote-s':'JGOS-31B-Citizen이 400개 함정 문항 중 398개 회피(99.5%, 1위). 메타인지는 AGI의 필수 능력입니다.',
	'meta-c1-tag':'세계 최초','meta-c1-h':'FINAL Bench','meta-c1-p':'세계 최초 메타인지 벤치마크. 100과제 × 15도메인 × 8유형(TICOS) × 3난이도.',
	'meta-c2-tag':'400문항','meta-c2-h':'함정 문항 평가','meta-c2-p':'그럴듯하지만 틀린 답변을 유도하는 400개 문항. 자기 오류 인식 능력 측정.',
	'meta-c3-tag':'비침습적','meta-c3-h':'메타인지 어댑터','meta-c3-p':'원본 모델 구조·가중치 변경 없이 내부 신호를 분석해 자기오류를 사전 감지합니다.',
	'meta-coll-tag':'11종 모델','meta-coll-p':'Darwin-28B-Opus, Darwin-9B-NEG, JGOS-31B-Citizen 등 주요 모델의 개인 메타인지 어댑터 11종.',
	'meta-lb-tag':'리더보드','meta-lb-p':'메타인지 성능 비교 리더보드. 24개 AI 모델의 함정 회피·자기오류 감지 능력 평가.',
	'q-crypto-tag':'암호분석 · 실 하드웨어','q-crypto-h':'QuantumOS 양자 암호분석 데모','q-crypto-p':'IBM Kingston 실 양자 하드웨어에서 실행된 genuine 양자 알고리즘 암호분석 스위트 — Even-Mansour N=10, 3-round Feistel(DES 계열) 블록 6·8, rank-1 클린. 정직스코프: 실 AES/RSA 아님, 양자우위 아님.',
	/* aether */
	'aether-h1':'단일 어텐션 시대의 종말.<br><span style="color:var(--pur)">5/7/11종 Hybrid 시대 개막.</span>',
	'aether-stat-first':'세계최초','aether-stat-first-l':'5/7/11종 이종 어텐션 단일 LLM 통합',
	'aether-stat-claims':'186','aether-stat-claims-l':'특허 청구항 (국내 우선출원 + PCT)',
	'aether-stat-n3':'n³','aether-stat-n3-l':'Triple Symmetry 표현력 향상',
	'aether-train-h':'학습 중인 <span>3종 모델</span>',
	'aether-m1-tag':'✓ 검증완료','aether-m1-p':'5×5 Latin Square · 25층 · 14.09B 파라미터 · 5종 어텐션',
	'aether-m2-tag':'⏳ 학습중','aether-m2-p':'7×7 Latin Square · 49층 · 30.6B 파라미터 · 7종 어텐션',
	'aether-m3-tag':'⏳ 학습중','aether-m3-p':'11×11 Latin Square · 121층 · 세계 최초 11종 어텐션',
	'aether-attn-h':'11종 <span>이종 어텐션 앙상블</span>','aether-attn-s':'최신 연구를 하나의 LLM에 통합합니다.',
	'attn-mla-t':'표준','attn-full-t':'표준','attn-slide-t':'효율','attn-gdn-t':'길이',
	'attn-mamba-t':'길이','attn-nsa-t':'압축','attn-nsa-d':'Native Sparse Attention · 시퀀스 압축',
	'attn-diff-t':'적응','attn-diff-d':'Differential Attention · 적응형 노이즈 제거',
	'attn-lin-t':'선형','attn-gate-t':'게이트','attn-hi-t':'고효율',
	'aether-road-h':'개발 <span>로드맵</span>',
	'road1-span':'(완료)','road1-p':'5×5 · 5종 어텐션 · 운영 중',
	'road2-span':'(학습 중)','road2-p':'7종·11종 동시 검증 · 세계 최초 11종 통합',
	'road3-span':'(Q3·Q4 2026)','road3-p':'Frontier 도전 · KMMLU 75-85% · GPQA 75-85%',
	'road4-span':'(차년도)','road4-p':'ICLR 2027 / NeurIPS 2026 학술 발표 예정',
	'aether-prin-h':'AGI 5대 <span>설계 원칙</span>',
	'pil1-h':'창발성','pil1-p':'9개 창발 엔진 + MARL 런타임',
	'pil2-h':'메타인지','pil2-p':'8유형 자기오류 감지 · TICOS',
	'pil3-h':'자가진화','pil3-p':'폐쇄 루프 영구학습 · SLAI',
	'pil4-h':'군집협업','pil4-p':'다중 에이전트 · SOMA/MOUSE',
	'pil5-h':'상생상극','pil5-p':'오행 강화·억제 · 환각 억제',
	/* proof */
	'proof-h1':'벤치마크. 논문. 특허. <span style="color:var(--ind)">언론보도.</span>',
	'proof-sub':'성과는 측정되고, 기록되고, 보호됩니다.',
	'proof-tab1':'🏆 벤치마크','proof-tab2':'📄 논문','proof-tab3':'🔒 특허 11건','proof-tab4':'📰 언론보도',
	'kait2-date':'2026.6 · KAIT(한국정보통신진흥협회) · 접수번호 RQT-25-090162',
	'kait2-title':'「AI 컴퓨팅 자원 활용 기반 강화(GPU 임차지원)」 과제 평가 — <span style="color:var(--em)">\'우수\'</span>',
	'kait2-desc':'GPU 임차지원 사업 과제 평가 우수 판정.',
	'kait2-badge':'우수',
	'bench1-p':'Darwin-398B-JGOS 90.9%. Darwin-28B-Opus 88.89% 1위. Top 21 내 Darwin 5종. HuggingFace 공인.',
	'bench2-p':'JGOS-31B-Citizen 종합 1위(0.621). 20위권 11개 Darwin 계열. 블라인드 평가.',
	'bench3-p':'HF 글로벌 5위. 100과제 × 15도메인 × 8유형 × 3난이도. TICOS 정량 측정.',
	'bench4-p':'월드 모델 벤치마크. Track C 통과 유일 모델. 실시간 인터랙티브 월드 시뮬레이션.',
	'pat-sub':'국내 우선출원 + PCT · 총 청구항 186개',
	'pat-darwin-h':'🧬 Darwin 진화형 · 3건',
	'pat-d1-h':'MRI 기반 적응형 신뢰도 메타학습','pat-d1-p':'모델 층 응답 중요도(MRI) 기반 신경망 파라미터 병합',
	'pat-d2-h':'호환성 평가 이기종 교배','pat-d2-p':'호환성 점수 기반 이종 아키텍처 모델 병합',
	'pat-d3-h':'재귀적 세대간 유전 진화','pat-d3-p':'반복적 세대 진화 및 유전 상속',
	'pat-aether-h':'⚡ AETHER 아키텍처 · 8건 · 186 청구항',
	'pat-a1-h':'라틴 방진 Hybrid 멀티-타입 어텐션','pat-a1-p':'5/7/11종 이종 어텐션 Latin Square 통합',
	'pat-a2-h':'인과 안전성 자동 검증','pat-a2-p':'자동화된 인과 안전성 CI/CD 검증',
	'pat-a3-h':'메타인지 신호 헤드','pat-a3-p':'자기오류 감지 신호 헤드',
	'pat-a4-h':'폐쇄 루프 영구 학습','pat-a4-p':'폐쇄 루프 자가진화 학습 시스템',
	'pat-a5-h':'다중 에이전트 군집 조율','pat-a5-p':'창발적 다중 에이전트 협업 런타임',
	'pat-a6-h':'삼중 대칭 MoE 라우팅','pat-a6-p':'n³ 표현력 삼중 대칭 라우팅',
	'pat-a7-h':'적응형 노이즈 제거 어텐션','pat-a7-p':'Differential attention 노이즈 억제',
	'pat-a8-h':'환각 억제 게이트','pat-a8-p':'환각 억제를 위한 강화/억제 게이팅',
	'press1-t':'지니젠AI·비드래프트, AI 메타인지 리더보드 공개','press-link':'보기',
	'press2-t':'Darwin-398B-JGOS, GPQA Diamond 90.9% 기록',
	'press3-t':'JGOS-31B-Citizen, K-AI 리더보드 종합 1위',
	'press4-t':'K-AI 상위 12개 중 8개가 Darwin 계열',
	'press5-t':'Darwin Family 논문 arXiv 공개 (2605.14386)',
	'press6-t':'비드래프트, Polaris 글로벌 신약개발 14관왕',
	'press7-t':'AETHER 5/7/11종 Hybrid 어텐션 공개',
	'press8-t':'KAIT GPU 임차지원 사업 과제 평가 우수',
	/* services */
	'services-h1':'증명은 <span style="color:var(--ind)">사용</span>에서 옵니다',
	'services-sub':'Darwin + AETHER 플랫폼 위에서 운영 중인 라이브 서비스입니다.',
	'svc-tab-all':'전체','svc-tab-hf':'HuggingFace','svc-tab-vkae':'VKAE','svc-tab-gov':'국가·행정',
	'svc-tab-pharma':'신약·소재','svc-tab-quantum':'양자·과학','svc-tab-tools':'도구·보안',
	'svc-all-h':'전체 서비스 <span>한눈에</span>',
	'ag-portal-h':'메인 포털','ag-portal-p':'전체 생태계 총람',
	'ag-darwin-h':'Darwin 컬렉션','ag-darwin-p':'진화형 모델 20종',
	'ag-meta-h':'메타인지 어댑터','ag-meta-p':'비침습 어댑터 11종',
	'ag-vkae-h':'VKAE 서빙','ag-vkae-p':'처리량 1.5–2배',
	'ag-jgos-h':'JGOS 시민 AI','ag-jgos-p':'320만 소버린 AI',
	'ag-national-h':'NationalOS v2','ag-national-p':'250지역 디지털 트윈',
	'ag-vision-h':'Darwin Vision','ag-vision-p':'문서·필기 인식',
	'ag-material-h':'MaterialsOS','ag-material-p':'신소재 AI 설계',
	'ag-admet-h':'ADMET','ag-admet-p':'신약 독성 예측',
	'ag-pharma-h':'PharmaOS DEEP','ag-pharma-p':'5단계 자율 신약 파이프라인',
	'ag-pharma-h':'PharmaOS DEEP','ag-pharma-p':'자율 신약 파이프라인',
	'ag-quantum-h':'QuantumOS','ag-quantum-p':'양자 시뮬 콘솔',
	'ag-qcrypto-h':'QuantumOS 암호분석','ag-qcrypto-p':'실 하드웨어 암호분석',
	'ag-qbench-h':'Quantum Bench','ag-qbench-p':'양자 알고리즘 순위',
	'ag-hansoo-h':'한수 (韓守)','ag-hansoo-p':'완전 로컬 AI 오피스',
	'ag-mouse-h':'MOUSE','ag-mouse-p':'멀티에이전트 코드 AI',
	'ag-chitos-h':'Chitos 보안','ag-chitos-p':'AI 코드 보안 스캔',
	/* HF collections */
	'svc-hf-h':'HuggingFace <span>컬렉션 & 모델</span>','svc-hf-s':'FINAL-Bench · VIDraft 조직에서 관리하는 공식 컬렉션입니다.',
	'hf-portal-label':'VIDraft · 메인 포털 · Space','hf-portal-p':'Darwin + AETHER 전체 생태계 소개 (KO/EN). Darwin 1.7B–398B · 특허 11건 · 라이브 서비스 9종 · Blackwell 32-GPU 인프라 · 메타인지 기술 총람.','hf-portal-btn':'메인 포털 열기 →',
	'hf-darwin-p':'Darwin-2B부터 Darwin-398B까지 진화형 언어모델 20종 전체 컬렉션. arXiv 2605.14386 논문과 연동.',
	'hf-darwin-m1':'📦 20종 모델','hf-darwin-m2':'⬇️ 100만+ 다운로드',
	'hf-meta-h':'메타인지 어댑터','hf-meta-p':'원본 구조 변경 없이 주요 Darwin 모델에 자기오류 감지 능력을 추가하는 비침습 어댑터 11종.',
	'hf-meta-m1':'📦 어댑터 11종','hf-meta-m2':'🧠 비침습적',
	'hf-vkae-h':'VKAE 컬렉션','hf-vkae-p':'단일 GPU에서 처리량 1.5–2배를 달성하는 추론 가속 모델. OpenAI 호환 API.',
	'hf-vkae-m1':'⚡ 1.5–2배','hf-vkae-m2':'🔌 OpenAI 호환',
	'hf-quantum-h':'Quantum Bench','hf-quantum-p':'양자 컴퓨팅 알고리즘 성능 리더보드. 실제 IBM Heron QPU 측정값 포함.',
	'hf-quantum-m1':'⚛️ IBM Heron QPU','hf-quantum-m2':'📊 NIST 6/6',
	/* VKAE section */
	'svc-vkae-h':'VKAE <span>추론 가속</span>','svc-vkae-s':'단일 GPU에서 기존 대비 1.5~2배 이상의 처리량을 달성합니다.',
	'vkae-hl-h':'⚡ 단일 B200 GPU에서 455 / 601 tok/s','vkae-hl-p':'VKAE 돌파 스택은 35B-A3B 모델을 단일 B200 GPU에서 표준 서빙 대비 1.5–2배 처리량으로 서비스합니다.',
	'vkae-lb-tag':'라이브 리더보드',
	'vkae-lb-h':'VKAE 서빙 리더보드','vkae-lb-p':'단일 GPU 서빙 속도 순위. Darwin · Qwen 모델 처리량 비교. OpenAI 호환 API 엔드포인트 제공.',
	'vkae-docker-h':'검증된 Docker 이미지','vkae-docker-p':'K-AI 리더보드 제출 검증 완료 Docker 이미지 8종. bake-in 방식(평가서버 인터넷 없이 동작). OpenAI 호환 API.',
	'vkae-d1':'Darwin-36B-Opus VKAE','vkae-d2':'Darwin-9B-NEG VKAE','vkae-d3':'JGOS-31B-Citizen VKAE','vkae-d4':'Darwin-398B-JGOS VKAE',
	'vkae-warn':'⚠️ 내부 서빙 인프라 — 접속에는 내부망 계정이 필요합니다.',
	/* gov */
	'svc-gov-h':'국가·행정 <span>AI 서비스</span>','svc-gov-s':'K-AI 1위 모델 기반 공공행정 AI — 320만 시민을 위한 한국어 소버린 AI.',
	'gov-jgos-tag':'K-AI 1위 모델','gov-jgos-h':'JGOS — 전남·광주 시민 AI','gov-jgos-p':'320만 시민을 위한 한국어 소버린 AI. 행정 · 법령 · 관광 · 민원 · 교통 · 문화 · 통계 · 농수산 안내. HWP·PDF·Excel·이미지 등 10+ 포맷 파일 분석. 무료 시민 AI 교육 포함. JGOS-31B-Citizen 기반.','gov-jgos-sub':'※ 테스트 버전 · 공식 행정 효력 없음',
	'gov-national-tag':'v2 · 디지털 트윈','gov-national-h':'NationalOS v2 — 지역별 디지털 트윈','gov-national-p':'KOSIS 데이터 기반 5,200만 명 시뮬레이션. 250시군구 × 17광역 3계층 분석. Quick(10–30초) / Regional(1–3분) / Deep(5–15분) 3단계. 9-Agent 환각 방지 엔진. 페르소나 매칭으로 정책 영향 인터뷰 생성.',
	/* pharma */
	'svc-pharma-h':'신약·소재 <span>AI</span>','svc-pharma-s':'Polaris 글로벌 14관왕 · 자율 신약 개발부터 신소재 설계까지.',
	'ph-vision-tag':'비전 AI','ph-vision-h':'Darwin-398B Vision','ph-vision-p':'FastAPI + Docker 기반. Darwin-398B-AX 프로덕션 백엔드 연동. 필기 인식 · MSDS 유해인자 추출 · 건강진단 판독. KIHA SFR-004/001 산업안전 데모. PDF·PNG·JPG·WEBP 지원.',
	'ph-material-tag':'양자 통합','ph-material-h':'MaterialsOS — 신소재 AI 설계','ph-material-p':'MatterGen→MLIP→UQ→신규성 4DB 검증→Hull→IBM Heron QPU 교차검증 7게이트 파이프라인. 생성 AI + 실제 QPU 통합. 한국 IonQ/KISTI 정합. 논문+특허 연계.','ph-material-sub':'※ 접속 권한 필요시 문의',
	'ph-admet-tag':'Polaris 14관왕','ph-admet-h':'ADMET — 독성·흡수·대사 예측','ph-admet-p':'Absorption · Distribution · Metabolism · Excretion · Toxicity 5개 지표 예측. Polaris 글로벌 리더보드 14관왕 모델 기반. BRICS 분자 생성 + Boltz-2 도킹. tox21-v4 scaffold-holdout AUC 0.790.','ph-admet-sub':'※ 접속 권한 필요시 문의',
	'ph-pharma-tag':'자율 신약','ph-pharma-h':'PharmaOS DEEP — 5단계 자율 파이프라인','ph-pharma-p':'RAG→SMILES 생성→CythoS 검증→SOTA 랭킹→리포트. 14개 적응증 커버. 자율 retry loop 내장.',
	/* quantum */
	'svc-quantum-h':'양자·과학 <span>AI</span>','svc-quantum-s':'IBM Heron QPU 실측 · NIST 랜덤성 6/6 통과 · 실제 양자 실험 연동.',
	'q-os-tag':'양자 콘솔','q-os-h':'QuantumOS — 양자 시뮬레이션 콘솔','q-os-p':'양자 회로 설계 · 시뮬레이션 · 실행. 실제 IBM QPU 측정 데이터 시각화. NIST 랜덤성(6/6 통과) · min-entropy 0.974 · Bell 부등식 위반(2.371) · VQE · QRAM 실험. #console 탭에서 직접 실행.',
	'q-bench-tag':'리더보드','q-bench-h':'Quantum Bench 리더보드','q-bench-p':'양자 알고리즘 및 시뮬레이터 성능 비교 리더보드. 실 QPU 측정값과 시뮬레이션 결과를 나란히 비교. HF Docker 메타데이터 자동 갱신. 27 likes.',
	/* tools */
	'svc-tools-h':'도구·보안 <span>AI</span>','svc-tools-s':'AI 보안, 코드 에이전트, 로컬 오피스, 법률 AI — 실무 도구 모음.',
	'tl-hansoo-tag':'데이터 주권','tl-hansoo-h':'한수 (韓守) — 완전 로컬 AI 오피스','tl-hansoo-p':'브라우저 기반, 인터넷 없이 동작. 데이터 외부 전송 0. HWP·DOCX·PPT·XLSX·PDF 지원. MIT 라이선스. 출시 2026.04.19.',
	'tl-mouse-tag':'멀티에이전트','tl-mouse-h':'MOUSE — 코드 에이전트','tl-mouse-p':'멀티 에이전트 코드 AI. MAU 150만+ 검증. Darwin 백본 군집 협업. SOMA 다중지능 아키텍처.',
	'tl-chitos-tag':'AI 보안','tl-chitos-h':'Chitos — 코드 보안 스캐너','tl-chitos-p':'AI 기반 코드 보안 취약점 탐지. OWASP Top 10 · 의존성 분석 · 비밀키 노출 검사. Darwin 백본 보안 특화 파인튜닝.',
	'tl-legal-tag':'법률 AI','tl-legal-h':'법률 AI — 환각 제거','tl-legal-p':'판례 기반 정확한 법률 AI. RAG + Darwin 법률 특화 파인튜닝으로 법률 환각을 제거합니다.',
	/* blog */
	'blog-h1':'AI 인사이트, <span style="color:var(--ind)">매일 새롭게</span>',
	'blog-sub':'비드래프트 AI가 매일 선별한 뉴스로 자동 작성하는 AI 에세이 시리즈.',
	'blog-latest':'최신 포스트',
	'blog-more-h':'더 많은 인사이트','blog-more-p':'비드래프트 대표의 AI 인사이트 · 기술 철학 · 산업 분석',
	'blog-more-btn':'브런치 @seawolf에서 보기 →',
	/* papers */
	'paper1-p':'MRI-Trust-Weighted Evolutionary Merging for Training-Free Scaling. 공개 45일: 30만+ 다운로드, 500종 파생.',
	'paper2-p':'Measuring Functional Metacognitive Reasoning in LLMs. MetaCog scaffold +14.05점. 94.8% Error Recovery. 학술대회 심사 중.',
	'paper3-p':'WM 통과 유일 월드 모델 v1.0. 263관절 스켈레톤. Track C 726점 B등급 47 FPS.',
	'paper4-p':'Model-Agnostic Runtime Middleware for LLMs. GPT/Claude/Gemini 환각 70%+ 감소. 코드 한 줄 적용.',
	'paper-link':'논문 보기 →',
	/* all-grid extras */
	'ag-vkaelb-p':'단일 GPU 속도','ag-docker-p':'8종 이미지',
	/* tools extras */
	'tl-paper-tag':'연구 도구','tl-paper-h':'논문 자동 생성','tl-paper-p':'AI 논문 작성·강화 에이전트. 초안 생성·레퍼런스 정리·개선 제안까지 자동화.',
	'tl-galaxy-tag':'모델 탐색','tl-galaxy-p':'22,400+ 모델 sigma.js 인터랙티브 시각화. Darwin·Trending·Multimodal 5개 클러스터. Galaxy / Atlas 2모드.',
	/* blog cards */
	'bc2-tag1':'K-AI 리더보드','bc2-tag2':'다윈 플랫폼',
	'bc2-title':'20위권 11개 — 다윈 플랫폼이 K-AI 리더보드를 점령했다',
	'bc2-desc':'K-AI 리더보드 20위권 안에 다윈 플랫폼으로 생성된 모델과 파생 모델이 11개. 이건 모델 하나의 우연한 성공이 아니라, 반복적으로 모델을 만들고 파생시키는 체계가 작동하고 있다는 신호다.',
	'bc2-s1':'20위권 내','bc2-s2':'HF 다운로드','bc2-s3':'특허 출원',
	'bc2-link1':'K-AI 리더보드 →','bc2-link2':'소개 영상 ▶',
	'bc3-tag1':'추론 가속',
	'bc3-title':'GPU를 만들지 않고도, GPU를 한 대 더 만드는 법',
	'bc3-desc':'추론 가속은 소프트웨어로 같은 칩에서 더 많은 일을 뽑아낸다. VKAE(VIDRAFT Kernel Acceleration Engine)는 같은 GPU에서 일반적인 방식 대비 최대 23.4배 높은 처리량을 기록했다. 빠른데 품질은 그대로.',
	'bc3-s1':'B200 처리량','bc3-s2':'tok/s (다중 요청)','bc3-link':'VKAE 리더보드·데모 →',
	'bc4-tag1':'보안 AI',
	'bc4-title':'취약점을 \'의심\'하는 데서 멈추지 않는다 — CHITOS 자율 보안 AI',
	'bc4-desc':'치토스는 발견했다고 바로 리포트에 올리지 않는다. 허가된 대상 안에서 직접 검증하고, 재현 가능성을 확인하고, 공격 경로를 킬체인으로 연결한다. 3단계: 정적 스캔 → 위협 연구 → 능동 익스플로잇 검증.',
	'bc4-env':'테스트 환경:','bc4-env2':'(IBM 허가 취약 데모 사이트)','bc4-link':'CHITOS 무료 체험 →',
	'bc5-tag1':'신약개발 AI','bc5-tag2':'Polaris 14관왕',
	'bc5-title':'신약을 먼저 읽는 AI — Polaris 글로벌 14관왕',
	'bc5-desc':'약효·용해도·독성·항암 키나아제·ADME 5개 분야 14개 벤치마크 전 세계 1위.',
	'bc5-cat1':'💊 약효 예측','bc5-cat2':'💧 용해도','bc5-cat3':'☠️ 독성 예측','bc5-cat4':'🎯 항암 키나아제 표적 예측','bc5-cat5':'🔬 약물성·ADME 예측',
	'bc5-b1':'약이 표적에 얼마나 강하게 듣는가','bc5-b2':'도파민 D3 수용체 결합 약효 예측','bc5-b3':'약이 물에 얼마나 잘 녹는가','bc5-b4':'약물 유발 간손상 예측','bc5-b5':'DNA 변이·발암 가능성 예측','bc5-b6':'EGFR + L858R 변이 저해 예측','bc5-b7':'EGFR 저해 예측','bc5-b8':'EGFR 신규 탈환 리더보드','bc5-b9':'EGFR 변이 분류 예측','bc5-b10':'LOK·SLK 키나아제 저해 예측','bc5-b11':'KIT 변이 저해 예측','bc5-b12':'먹는 약이 혈류에 도달하는 정도','bc5-b13':'약물이 체내 조직에 퍼지는 정도','bc5-b14':'CYP2D6 효소 대사·약물상호작용 예측','bc5-link':'Polaris 전체 리더보드 →',
	/* footer */
	'ft-addr':'주식회사 비드래프트 (VIDRAFT Inc.)<br>서울특별시 서초구 논현로 175 신한빌딩 7층<br>사업자등록번호 879-87-03063 · ArXivGPT@gmail.com',
	'ft-tech':'기술','ft-achieve':'성과','ft-services':'주요 서비스',
	'ft-paper':'Darwin Family 논문','ft-bench':'벤치마크','ft-patents':'특허 11건','ft-press':'언론보도','ft-meta':'메타인지 어댑터',
	'ft-svc-jgos':'JGOS 시민 AI','ft-svc-admet':'ADMET 신약 예측',
	'ft-copy':'© 2026 주식회사 비드래프트 · VIDRAFT Inc. All rights reserved.','ft-tag':'Pre-AGI · Darwin · AETHER · 한국 AI 1위',
	'nav-company':'회사','co-badge':'우리 크루','co-h1':'우리 대연합<br><span style="color:var(--ind)">이 배를 움직이는 11인</span>','co-sub':'한 배에 오른 열한 명이 회사를 움직입니다.',
	/* team */
	'nav-team':'팀',
	'team-badge':'우리 크루','team-h1':'우리 대연합<br><span style="color:var(--ind)">이 배를 움직이는 11인의 전설</span>','team-sub':'7개 진영 · 하나의 깃발 · 이 배를 움직이는 11명의 전설.',
	'tc-1-role':'의장','tc-1-q':'우리가 지금 만드는 것들이 인류의 미래가 될 것이다.',
	'tc-2-role':'CEO','tc-2-q':'낙천이 전략이고, 확신이 자산이다.',
	'tc-3-role':'COO','tc-3-q':'회장이 소리쳐도, 이 배의 항로는 흔들리지 않는다.',
	'tc-4-role':'CFO','tc-4-q':'숫자는 냉정하게, 팀은 진심으로.',
	'tc-5-role':'CIO','tc-5-q':'이 바닥의 모든 항로를 지도 없이 안다.',
	'tc-6-role':'연구소장 · HEAD OF R&D','tc-6-q':'말없이 자리를 지키고, 결과로 답한다.',
	'tc-7-role':'CTO','tc-7-q':'CEO가 자면 자고, CEO가 코딩하면 코딩한다.',
	'tc-8-role':'인턴 · INTERN','tc-8-q':'정식 크루가 되는 그날까지, 배우겠습니다.',
	'tc-9-role':'인턴 · INTERN','tc-9-q':'칭찬하지 마세요! (매우 기뻐하는 중)',
	'tc-10-role':'CMO','tc-10-q':'명함 한 장에 왕국이 딸려온다.',
	'tc-11-role':'일본 사업 본부장 · JAPAN HEAD','tc-11-q':'일본과 세계를 잇는 유일한 사무라이.'
	}
	};
	function setLang(lang){
	localStorage.setItem('vd-lang',lang);
	document.documentElement.lang=lang; // SEO: <html lang> 동기화
	document.querySelectorAll('[data-i18n]').forEach(function(el){
	var key=el.getAttribute('data-i18n');
	if(T[lang]&&T[lang][key])el.innerHTML=T[lang][key];
	});
	/* language-specific block toggles (long-form blog content) — body class drives CSS */
	document.body.classList.toggle('lang-ko',lang==='ko');
	document.getElementById('btn-en').classList.toggle('active',lang==='en');
	document.getElementById('btn-ko').classList.toggle('active',lang==='ko');
	}
	document.addEventListener('DOMContentLoaded',function(){setLang(localStorage.getItem('vd-lang')\|\|'ko');});

	function toggleNav(){
	var n=document.querySelector('nav'); if(!n) return;
	var open=n.classList.toggle('nav-open');
	var b=n.querySelector('.nav-burger');
	if(b){ b.textContent=open?'✕':'☰'; b.setAttribute('aria-expanded',open?'true':'false'); }
	}
	function closeNav(){
	var n=document.querySelector('nav'); if(!n\|\|!n.classList.contains('nav-open')) return;
	n.classList.remove('nav-open');
	var b=n.querySelector('.nav-burger'); if(b){ b.textContent='☰'; b.setAttribute('aria-expanded','false'); }
	}
	function showPage(id){
	document.querySelectorAll('.page').forEach(p=>p.classList.remove('active'));
	document.querySelectorAll('.nav-links a').forEach(a=>a.classList.remove('active'));
	document.getElementById('page-'+id).classList.add('active');
	document.getElementById('nav-'+id).classList.add('active');
	window.scrollTo({top:0,behavior:'smooth'});
	closeNav(); // 모바일: 메뉴 선택 시 드롭다운 닫기
	}
	function switchTab(page, tab, el){
	// deactivate all tabs in this page
	el.closest('.subtab-bar').querySelectorAll('.stab').forEach(t=>t.classList.remove('active'));
	// find stab-contents in current page
	document.getElementById('page-'+page).querySelectorAll('.stab-content').forEach(c=>c.classList.remove('active'));
	el.classList.add('active');
	document.getElementById(page+'-'+tab).classList.add('active');
	}
	</script>

	<!-- Darwin 모델 카탈로그 렌더러 (darwin_models.json 기반, 갱신은 JSON만 교체) -->
	<script>
	(function(){
	function fmt(n){ return (n\|\|0).toLocaleString('en-US'); }
	function esc(s){ return (s\|\|'').replace(/</g,'<').replace(/>/g,'>'); }
	// ── 셀 렌더러 ──
	function cModel(m){ return '<td><a href="'+m.u+'" target="_blank" rel="noopener">'+esc(m.n)+'</a><span class="m-auth">'+esc(m.a)+'</span></td>'; }
	function cDocker(m){ return '<td><a href="'+m.u+'" target="_blank" rel="noopener">vidraft/'+esc(m.n)+'</a></td>'; }
	function cType(m){ return '<td class="hide-sm m-pipe">'+(esc(m.p)\|\|'—')+'</td>'; }
	function cDesc(m){ return '<td class="hide-sm m-pipe">'+(esc(m.desc)\|\|'—')+'</td>'; }
	function cDate(m){ return '<td class="hide-sm m-pipe">'+(m.c\|\|'')+'</td>'; }
	function cDL(m){ return '<td class="m-dl">'+fmt(m.d)+'</td>'; }
	function cPulls(m){ return '<td class="m-dl">'+fmt(m.pulls)+'</td>'; }
	function c30(m){ return '<td class="hide-sm m-30">'+fmt(m.d30)+'</td>'; }
	function cLk(m){ return '<td class="m-lk">♥ '+fmt(m.l)+'</td>'; }
	// ── 정렬 가능한 표 빌더: 헤더 클릭 → 오름/내림 토글 ──
	function sortable(id, data, cols, defk, defdir){
	var el=document.getElementById(id); if(!el) return;
	var st={k:defk, dir:defdir};
	function colByK(k){ for(var i=0;i<cols.length;i++) if(cols[i].k===k) return cols[i]; return null; }
	function draw(){
	var arr=data.slice(); var cc=colByK(st.k);
	arr.sort(function(a,b){
	var va=a[st.k], vb=b[st.k];
	if(cc && cc.t==='s'){ va=(va\|\|'')+''; vb=(vb\|\|'')+''; return st.dir*(va<vb?-1:(va>vb?1:0)); }
	return st.dir*(((va\|\|0)-(vb\|\|0)));
	});
	var head='<thead><tr><th class="rk">#</th>'+cols.map(function(c){
	var cls=[]; if(c.hide)cls.push('hide-sm'); if(c.k)cls.push('sortable');
	var act=c.k===st.k;
	var ar=c.k?' <span class="sort-ar'+(act?' on':'')+'">'+(act?(st.dir<0?'▼':'▲'):'⇅')+'</span>':'';
	var lbl=c.i18n?'<span data-i18n="'+c.i18n+'">'+c.lbl+'</span>':c.lbl;
	return '<th'+(cls.length?' class="'+cls.join(' ')+'"':'')+(c.al?' style="text-align:'+c.al+'"':'')+(c.k?' data-k="'+c.k+'"':'')+'>'+lbl+ar+'</th>';
	}).join('')+'</tr></thead>';
	var body='<tbody>'+arr.map(function(m,i){
	return '<tr><td class="rk">'+(i+1)+'</td>'+cols.map(function(c){return c.r(m);}).join('')+'</tr>';
	}).join('')+'</tbody>';
	el.innerHTML=head+body;
	el.querySelectorAll('th[data-k]').forEach(function(th){
	th.addEventListener('click',function(){
	var k=th.getAttribute('data-k');
	if(st.k===k){ st.dir=-st.dir; }
	else { st.k=k; var c2=colByK(k); st.dir=(c2 && c2.t==='s')?1:-1; }
	draw();
	});
	});
	if(window.setLang) setLang(localStorage.getItem('vd-lang')\|\|'ko');
	}
	draw();
	}
	var MCOLS=[
	{k:'n', t:'s', i18n:'mth-model', lbl:'Model', r:cModel},
	{k:'p', t:'s', i18n:'mth-type', lbl:'Type', hide:true, r:cType},
	{k:'c', t:'s', i18n:'mth-created', lbl:'Created', hide:true, r:cDate},
	{k:'d', t:'n', i18n:'mth-dl', lbl:'Cumulative DL', al:'right', r:cDL},
	{k:'d30', t:'n', lbl:'30d', hide:true, al:'right', r:c30},
	{k:'l', t:'n', lbl:'♥', al:'right', r:cLk}
	];
	var DCOLS=[
	{k:'n', t:'s', i18n:'dts-th', lbl:'Dataset', r:cModel},
	{k:'c', t:'s', i18n:'mth-updated', lbl:'Updated', hide:true, r:cDate},
	{k:'d', t:'n', i18n:'mth-dl', lbl:'Cumulative DL', al:'right', r:cDL},
	{k:'l', t:'n', lbl:'♥', al:'right', r:cLk}
	];
	var KCOLS=[
	{k:'n', t:'s', i18n:'dth-img', lbl:'Image', r:cDocker},
	{k:'desc', t:'s', i18n:'dth-desc', lbl:'Description', hide:true, r:cDesc},
	{k:'c', t:'s', i18n:'mth-updated', lbl:'Updated', hide:true, r:cDate},
	{k:'pulls', t:'n', i18n:'dth-pulls', lbl:'Pulls', al:'right', r:cPulls}
	];
	function statCard(num,key){ return '<div class="si"><div class="sn">'+num+'</div><div class="sl" data-i18n="'+key+'"></div></div>'; }
	function spacesGrid(list){
	var h='';
	for(var i=0;i<list.length;i++){var s=list[i];
	h+='<a class="card sp-card" href="'+s.u+'" target="_blank" rel="noopener">'
	+'<div class="sp-top"><span class="sp-sdk">'+(esc(s.sdk)\|\|'space')+'</span><span class="sp-lk">♥ '+fmt(s.l)+'</span></div>'
	+'<div class="sp-name">'+esc(s.n)+'</div>'
	+'<div class="sp-auth">'+s.a+'</div></a>';
	}
	return h;
	}
	function setCnt(id,n){ var el=document.getElementById(id); if(el) el.textContent=fmt(n); }
	fetch('./darwin_models.json?v='+Date.now()).then(function(r){return r.json();}).then(function(d){
	var s=d.summary;
	document.getElementById('mdl-stats').innerHTML =
	statCard(fmt(s.grand.count),'mdl-st-total')
	+ statCard((s.grand.variants?fmt(s.grand.variants)+'+':fmt(s.grand.count)),'mdl-st-var')
	+ statCard(fmt(s.grand.dl_all)+'+','mdl-st-dl')
	+ statCard(fmt(s.official.count),'mdl-st-off')
	+ statCard(fmt(s.community.count),'mdl-st-com');
	sortable('tbl-official', d.official\|\|[], MCOLS, 'd', -1);
	sortable('tbl-community', d.community\|\|[], MCOLS, 'd', -1);
	if(d.other){ sortable('tbl-other', d.other, MCOLS, 'd', -1); setCnt('cnt-other', d.other.length); }
	if(d.docker){ sortable('tbl-docker', d.docker, KCOLS, 'pulls', -1); setCnt('cnt-docker', d.docker.length); }
	if(d.spaces){ document.getElementById('grid-spaces').innerHTML = spacesGrid(d.spaces); setCnt('cnt-spaces', d.spaces.length); }
	if(d.datasets){ sortable('tbl-datasets', d.datasets, DCOLS, 'd', -1); setCnt('cnt-datasets', d.datasets.length); }
	document.getElementById('mdl-gen').textContent = d.generated;
	if(window.setLang) setLang(localStorage.getItem('vd-lang')\|\|'ko');
	}).catch(function(){
	var el=document.getElementById('mdl-stats');
	if(el) el.innerHTML='<p style="color:var(--muted);text-align:center;width:100%">Model data unavailable.</p>';
	});
	})();
	</script>