<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>williamcotton</author><text>I’ve been using GPT based coding tools for quite awhile. GPT-4 coupled with my extensive experience has enabled me to tackle just about every programming challenge I set for myself, from systems programming, neural networks and up to GUI programming on multiple kinds of devices and languages.&lt;p&gt;I have been programming since the mid-90s so I have strong fundamentals. What I often lack is knowledge of syntax, APIs or libraries. Once presented with this information I am off to the races.&lt;p&gt;Almost the entirety of this codebase was written by GPT:&lt;p&gt;&lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;williamcotton&amp;#x2F;chordviz&quot;&gt;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;williamcotton&amp;#x2F;chordviz&lt;/a&gt;&lt;p&gt;Yes, it required a background in LA and studying various ML techniques in order to understand how to guide the completions. It also frequently produced incorrect code but I was able to isolate the problems and reduce the complexity presented to GPT in order to get functional results.&lt;p&gt;The majority of the time was spent labeling around 12,000 images using the labeling software that I guided GPT to construct.&lt;p&gt;I now have a SwiftUI iOS application that takes a live camera feed and predicts guitar chords based on a PyTorch CNN model trained on images labeled with a React application.</text><parent_chain><item><author>ignoramous</author><text>The hype is not because what the status quo is today (think ARPANet), but because so many experts (not just investors) in the field believe that LLMs (and its multi modal versions) are on an exponential (quadratic?) improvement trajectory.&lt;p&gt;Before today, access to AI was gated by firms like Google, who kept the implementation to themsevles as a competitive advantage (but did publish copious amounts of research). With these LLMs being so general purpose &lt;i&gt;and&lt;/i&gt; made readily accessible to other software shops at affordable rates, things are in for a dramatic shift as far as &lt;i&gt;utility AI&lt;/i&gt; is concerned.&lt;p&gt;A vertical integrator in Apple just demonstrated how the tech is really coming together with its VisionPro launch. For an example closer to home, GitHub was right on the money with Copilot. Personally speaking, I&amp;#x27;ve been using Copilot for some months now, and I can barely program without it. Not because I forgot how to program, but because it is so darn good that I&amp;#x27;d rather not code without it. Surely, I can&amp;#x27;t be the only one that feels this way?&lt;p&gt;If the experts are right about the exponentials, then the world is going to look &lt;i&gt;very&lt;/i&gt; different by the time GPT-6 rolls out, especially if the models get cheaper (even as good as &lt;i&gt;free&lt;/i&gt; bar computer costs, in the case of open source models) as they get more capable.</text></item></parent_chain></comment><story><title>The AI Hype Wall of Shame</title><url>https://criticalai.org/the-ai-hype-wall-of-shame/</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>version_five</author><text>The &amp;quot;experts&amp;quot; are experts in ML: stats and linear algebra and whatnot. Their hot takes about it coming alive or through some other means destroying us are just as irrelevant as any other lay person&amp;#x27;s. From what I can see, a lot of this is about delusions of self importance on the researchers&amp;#x27; part. It&amp;#x27;s not a coincidence, though a bit ironic, that LeCun, who comes across as the most arrogant and contrarian is the least caught up in the &amp;quot;oh what have we done&amp;quot; faux hype and the most realistic about what the technology is.</text><parent_chain><item><author>ignoramous</author><text>The hype is not because what the status quo is today (think ARPANet), but because so many experts (not just investors) in the field believe that LLMs (and its multi modal versions) are on an exponential (quadratic?) improvement trajectory.&lt;p&gt;Before today, access to AI was gated by firms like Google, who kept the implementation to themsevles as a competitive advantage (but did publish copious amounts of research). With these LLMs being so general purpose &lt;i&gt;and&lt;/i&gt; made readily accessible to other software shops at affordable rates, things are in for a dramatic shift as far as &lt;i&gt;utility AI&lt;/i&gt; is concerned.&lt;p&gt;A vertical integrator in Apple just demonstrated how the tech is really coming together with its VisionPro launch. For an example closer to home, GitHub was right on the money with Copilot. Personally speaking, I&amp;#x27;ve been using Copilot for some months now, and I can barely program without it. Not because I forgot how to program, but because it is so darn good that I&amp;#x27;d rather not code without it. Surely, I can&amp;#x27;t be the only one that feels this way?&lt;p&gt;If the experts are right about the exponentials, then the world is going to look &lt;i&gt;very&lt;/i&gt; different by the time GPT-6 rolls out, especially if the models get cheaper (even as good as &lt;i&gt;free&lt;/i&gt; bar computer costs, in the case of open source models) as they get more capable.</text></item></parent_chain></comment><story><title>The AI Hype Wall of Shame</title><url>https://criticalai.org/the-ai-hype-wall-of-shame/</url></story>