| This is an important conversation to have and we should pretty clearly about what the issues are. I didn't see any objection to LLM assisted development in the abstract. The objection is to relying on proprietary AI providers in general, and Gemini in particular, via Shashiko. The problem is that kernel contributions could become gated by hyperscalers who can draw on compute power normal people can't access. Devault mentions data centers' carbon emissions and water usage. I find both of these objections to be distractions. It's not that carbon emissions don't matter. Keeping greenhouse gasses in check is incredibly important. But there are far more productive ways to cut carbon emissions than to block data centers. Heavy industry consumes far more electricity than data centers, for less economic value. This is even truer for water use. If carbon emissions is a major concern (as it should be), there are better targets to go after than data centers. A more compelling argument is the danger that the Linux kernel becomes something that's effectively controlled by proprietary AI providers: Google, Anthropic, OpenAI, Microsoft, etc. The photo of tech company leaders at Trump's inauguration underscores their lack of any moral compass. But if AI-driven kernel development is actually useful and productive, that's going to be hard to turn down. If you believe that LLM use is technically counter-productive, then this whole AI thing is a bubble and you can just wait for it to pop. If you believe that LLMs can be technically productive if used correctly, and the drawbacks are entirely social, then it means giving up something technically useful. That is a real cost. I think Linus is right here: it would be hard for regular kernel developers to coordinate a fork of the project. It might not be that hard for the hyperscalers to simply fork Linux. They would still release the source code under the GPL, but nobody would be able to keep up with it. Ultimately, this could doom the human-written version of the kernel to irrelevance as most people switch to the faster/stronger/harder LLM-derived fork. Maybe a reasonable medium would be to insist on using an open model for code review instead of depending on Gemini or any proprietary model. |