241–250 of 434 posts
> Gemini 2.5 PRO | Claude Opus 4 Whether it's vibe coding, agentic coding, or copy pasting from the web interface to your editor, it's still sad to see the normalization of private (i.e., paid) LLM models. I like the progress that LLMs introduce and I see them as a powerful tool, but I cannot understand how programmers (whether complete nobodies or popular figures) dont mind adding a strong dependency on a third part…
+1, I use exclusively free tools for this exact reason. I've been using the same tools for 15 years now (GCC + IDE), and they work great There is a 0% chance that I'm going to subscribe to being able to program, because its actively a terrible idea. You have to be very naïve to think that any of these companies are still going to be around and supporting your tools in 10-20 years time, so if you get proficient with t…
I've been spending time with my team, just a few hours a week, on training them on foundational things, vs every other team in the company just plodding along, trying to do things the same way they always have, which already wasn't working. It's gotten to where my small team of 4 is getting called in to clean up after these much larger teams fail to deliver. I'm pretty proud of my little junior devs.
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Feel free to change careers and get lost, no one is forcing you to be a programmer. If you feel it is stealing your life, then please feel free to reclaim your life at any time. Leave the programming to those of us who actually want to do it. We don't want you to be a part of it either
Don't be rude.
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I think the dev population mostly uses free search, just based on the fact no one has told me to “Kagi it” yet.
When I need a facial tissue I ask for a Kleenex even if the box says Puffs. Because who says "pass me the Puffs"?
> Gemini 2.5 PRO | Claude Opus 4 Whether it's vibe coding, agentic coding, or copy pasting from the web interface to your editor, it's still sad to see the normalization of private (i.e., paid) LLM models. I like the progress that LLMs introduce and I see them as a powerful tool, but I cannot understand how programmers (whether complete nobodies or popular figures) dont mind adding a strong dependency on a third part…
> Gemini 2.5 PRO | Claude Opus 4 Whether it's vibe coding, agentic coding, or copy pasting from the web interface to your editor, it's still sad to see the normalization of private (i.e., paid) LLM models. I like the progress that LLMs introduce and I see them as a powerful tool, but I cannot understand how programmers (whether complete nobodies or popular figures) dont mind adding a strong dependency on a third part…
What I think is more likely is people will realize that every line of code written is, to an extent, a liability, and generating massive amounts of sloppy insecure poorly performing code is a massive liability.
That's not to say that AI's will go away, obviously, but I think when the hype dies down and people get more accustomed to what these things can and can't do well we'll have a more nuanced view of where these things should be applied.
I suppose what's still not obvious to me is what happens if the investment money dries up. OpenAI and Anthropic, as far as I know, aren't anywhere near profitable and they require record breaking amounts of capital to come in just to sustain what they have. If what we currently see is the limit of what LLM's and other generative techniques can do, then I can't see that capital seeing a good return on its investment. If that's the case, I wonder if when the bubble bursts these things become massively more expensive to use, or get taken out of products entirely. (I won't be sad to see all the invasive Copilot buttons disappear..)
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LLMS are basically free? Yes you're rate limited but I have just started paying for them now, before I'd bounce around between the providers but still free
The most cutting edge-models aren't usually free, at least at first.
What advantages are people getting on these new models?
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The thing is, code is quite compact. Why do LLMs need to train on content bigger than the size of the textual internet to be effective? Total newb here.
Many reasons, one being that LLMs are essentially compressing the training data to unbelievably small data volumes (the weights). When doing so, they can only afford to keep the general principles and semantic meaning of the training data. Bigger models can memorize more than smaller ones of course, but are still heavily storage limited. Through this process they become really good at semantic understanding of code a…
Considering as you said, that LLMs are doing a form of compression, and assuming generously that you add extra compression on top, yeah, now I understand a bit more. Even if you focus on non-similar code to get the most coverage, I wouldn't be shocked if a modern, representative source code training data from Github weighed 1TB, which obviously is a lot more than consumer grade hardware can bear.
I guess we need to ramp up RAM production a bunch more :-(
Speaking of which, what's the next bottle neck except for storing the damned things? Training needs a ton of resources but that part can be pooled, even for OSS models, it "just" need to be done "once", and then the entire community can use the data set. So I guess inference is the scaling cost, what's the most used resource there? Data bandwidth for RAM?