<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>blihp</author><text>Meta&amp;#x2F;Yann LeCun were generating the hype around Galactica that caused expectations to be different.  You can&amp;#x27;t say things like &amp;#x27;Type a text and Galactica will generate a paper with relevant references, formulas, and everything&amp;#x27;[1] and expect your LLM not to make you look foolish.  It wasn&amp;#x27;t about pushing the model to the limit, it was about setting realistic expectations of what it could do.&lt;p&gt;[1] &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;statmodeling.stat.columbia.edu&amp;#x2F;2022&amp;#x2F;11&amp;#x2F;23&amp;#x2F;bigshot-chief-scientist-of-major-corporation-cant-handle-criticism-of-the-work-he-hypes&amp;#x2F;&quot; rel=&quot;nofollow noreferrer&quot;&gt;https:&amp;#x2F;&amp;#x2F;statmodeling.stat.columbia.edu&amp;#x2F;2022&amp;#x2F;11&amp;#x2F;23&amp;#x2F;bigshot-ch...&lt;/a&gt;</text><parent_chain><item><author>janalsncm</author><text>I think the reason is because expectations were different. ChatGPT was released to the general public for general use. Galactica was really only noticed by the egg head press and egg head professionals (like myself) who rightly identified the failure of these statistical language models to have a grounding in facts. People whose job it is to notice details are going to push your model to the limit.&lt;p&gt;But it’s not like ChatGPT was better. If I recall, RLHF actually made hallucinations slightly worse. Even today OpenAI wouldn’t claim to be able to accurately summarize papers. It’s just that there was an endless supply of “write X in the style of Y” that was like catnip for journalists and kept them busy for months.</text></item></parent_chain></comment><story><title>What Meta learned from Galactica, the doomed model</title><url>https://venturebeat.com/ai/what-meta-learned-from-galactica-the-doomed-model-launched-two-weeks-before-chatgpt/</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>otabdeveloper4</author><text>ChatGPT relies very much on confirmation bias to do its magic. You ask something trivial you already know (and could have probably Googled in 15 seconds), you get back something glib and smooth in reply and you are wowed by how smart GPT seems to be.&lt;p&gt;It is significantly less impressive when you ask something you don&amp;#x27;t already know and can&amp;#x27;t Google easily.</text><parent_chain><item><author>janalsncm</author><text>I think the reason is because expectations were different. ChatGPT was released to the general public for general use. Galactica was really only noticed by the egg head press and egg head professionals (like myself) who rightly identified the failure of these statistical language models to have a grounding in facts. People whose job it is to notice details are going to push your model to the limit.&lt;p&gt;But it’s not like ChatGPT was better. If I recall, RLHF actually made hallucinations slightly worse. Even today OpenAI wouldn’t claim to be able to accurately summarize papers. It’s just that there was an endless supply of “write X in the style of Y” that was like catnip for journalists and kept them busy for months.</text></item></parent_chain></comment><story><title>What Meta learned from Galactica, the doomed model</title><url>https://venturebeat.com/ai/what-meta-learned-from-galactica-the-doomed-model-launched-two-weeks-before-chatgpt/</url></story>