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The discussion should stay technical.
Human written code these days feels equivalent to a unique and soulful artisan made item whereas AI code is like a soulless and defected factory made imitation. I’d much, much, much, rather support artisans over factory made slop and even before AI, artisan work has been well known to be significantly higher quality than factory made stuff. For something as foundational and important as a kernel, I really think AI has no place in it.
All I care about is whether it works and is secure. Bonus points for cheaper and faster development. If artisan code gets us there, sure. If AI code gets us there, great. I trust Linus to know what works and what doesn’t.
I suppose the big issue for me is that I’m also an artist and I view code similarly, especially when I combine code with my graphics. I understand though that with a large project you are going to have some amount of people using AI even if you try to filter them out, so I can partially understand his stance. However I really disagree with him when he says it’s a useful tool, given how AI causes brain rot, productivity losses, and environmental destruction.
Even artisans use tools.
Artisans own their tools, that’s what makes them artisans (rather than wage workers). I believe after the bubble pops there will be legitimate uses for the tech, and we’ll be able to run a pretty good iteration in our own hardware, but as it is now I’m uncomfortable with my employer having the power to decide whether I have the tools they want me to use for the job, whereas with code that’s less of a concern.
There’s already pretty decent open weight models that you can run on your own hardware. They won’t be as fast as the models running in a datacenter but they will get the job done while not adding more money to the garbage fire that is ‘The AI Industry’.
I don’t think that the future of AI is as a massive subscription service industry, that is just rampant capitalism on full display (with all of the damage that it causes).
I was thinking more that lots of people don’t have the hardware required to begin with, and it’s really hard to purchase now (especially in poorer countries like mine), hopefully memory prices will come down at some point after the bubble bursts so we can afford shit
It’s really a race between the AI bubble bursting and hardware manufacturers building more production to chase the higher prices.
One of China’s largest chip producers is building several new fabs and their domestic fabs (i.e. ones not made by ASML) are capable of producing DDR5. Once this price shock ends I wouldn’t be surprised to see hardware prices drop to below levels they were pre-2020.
What we’re seeing is the effect of companies having hundreds of billions of dollars in cash on hand and all deciding to dump it into computer hardware at the same time. They can’t burn capital forever and AI isn’t remotely what they’re selling it as so they’re finding a hard time generating any meaningful revenue. All they’re doing is shoveling money to hardware manufacturers, who will use it to build out extra capacity and once the spending frenzy ends we’ll have way more supply than demand.
Of course, given how much money is floating around, that could be 5 years from now.
This “argument” really shines the light on just how dumb pro AI people are.
This ‘ad hominem’ really shines the light on just how toxic anti-AI people are.
Did you have to ask ChatGPT how you felt about my comment then to create a response?
Are you naturally an asshole or do you just enjoy fighting strawmen on the Internet?
That’s why you like AI. You can say anything and have it stroke your ego. Real people challenge you and I bet that feels icky.
All it takes is one person using an LLM tainted with proprietary code which then just gives them that code line for line to undo decades of courtroom defense.
Not only that, but AI output can’t be licensed/copyrighted. The GPL license no longer covers the kernel in legal terms.
The GPL license no longer covers the kernel in legal terms.
The uncopyrightability of AI-written code only applies to the actual strings of code generated by an AI, not to the entire project.
A person could ignore the GPL if they only copied the AI-written portions. But, how could they know for sure which lines were AI generated and which were not? A wrong choice would leave them civilly liable for copyright violation and all they stand to gain would be tiny portions of the Linux kernel code which are worthless by themselves.
There’s no reason to steal the AI generated portions and risk a lawsuit, when you can just generate your own code.
There seems to be legal discussions about that. It’s not quite as simple as you say:
However, there may be cases in which a different assessment is justified, namely when users use and operate the LLM as a tool that merely implements their personal creative intent. This could be compared somewhat more vividly to using a paintbrush. If the brush merely rolls over the paper, for example because it is dropped, no copyright-protected work is created, even if paint remains on the paper. However, if a painter deliberately swings the brush in a certain way, a protected painting can be created. If AI is used in a comparable way a copyright-protected work can indeed be created.
https://kpmg-law.de/en/ai-and-copyright-what-is-permitted-when-using-llms/
Yeah any decision would be on a case by case basis, which is normally something you’d want to avoid.
I’ve seen a couple of Linux devs talk about how they just give a prompt to claude and walk away leaving it alone to spit out the code, none of which can be licensed as GPL. But good luck working out what specific lines of what specific patches of theirs used an LLM vs. were re-written or such.
I’ve seen a couple of Linux devs talk about how they just give a prompt to claude and walk away leaving it alone to spit out the code
While I share Linus opinion on LLMs, I think doing this shit is extremely stupid and lazy.
And extremely abusive, since they don’t review the code fully, but a human must review the whole commit before accepting it. They save their time but consume that of others.
Ist that a common thing that LLMs using proprietary code for coding tasks?
Because I don’t think so.
They use everything for everything, that’s the big issue. Also gpl code. Anything they can trawl through they use. And replicate, in part or in full.
They take code snippets and copy and paste them? Or do they create own code based on what they’ve learned by trawling?
LLMs don’t “create”. Under the hood, they’re tokenizing the queries, looking for “clouds” of tokens that are similar to the query, then returning a sequence of tokens (with some random noise thrown in) that match what their training data says the answer should be.
In short: all LLM code is an amalgamation of their training data by definition. If there’s nothing similar in there, it’s literally not possible for it to be part of any response.
You’re exactly right. I should have used „generate“ instead of „create“.The point is I don’t think LLMs normally use copyrighted code in a way that would hurt open source projects.
Under the hood, they’re tokenizing the queries, looking for “clouds” of tokens that are similar to the query, then returning a sequence of tokens (with some random noise thrown in) that match what their training data says the answer should be.
Lol, so how do humans code in comparison?
Lol, so how do humans code in comparison?
By copy pasting from Stack Overflow
You’re exactly right. I should have used „generate“ instead of „create“
Did you purposely respond like an AI?
Human programmers at least can tell you where they got a snippet they copied, whether it was in the docs, stack overflow or elsewhere, and you can try to keep attribution if you care about compliance. Not only that, but most of our skills are related to designing stuff and recognizing which pattern to use, the specific implementation isn’t necessary the same unless we go look for whatever we saw in the past, as our memories don’t just record everything and repeat it word by word. And after picking up a new language or framework I only need to look around when using a third party library or some API I’m less familiar with, or when something breaks.
The point is I don’t think LLMs normally use copyrighted code in a way that would hurt open source projects.
I don’t know. I’m not a lawyer, and copyright for code was a hot mess even before LLMs got involved. With how many opportunistic copyright/patent trolls there are and how easily convinced judges have been in the past, it could go either way.
Lol, so how do humans code in comparison?
The good programmers normally code by breaking down the problem into constituent parts and logically working through the problem, step by step. What differentiates this from tokenization is that instead of just looking for code that is similar for a similar problem, programmers can usually understand the effects of each line of code, visualize what the state of each variable will be in that step (or dump out the variables to look directly if unsure), and then move on to the next step. This logical problem-solving approach is fundamentally different from a tokenization+noise looking for a similar-looking problem approach. For one thing, you can solve problems that haven’t been solved before.
