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Linus Torvalds shares his thoughts on Anti-AI coding rules (europe.pub)
submitted 6 days ago by to c/linux@programming.dev
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[–] 28 points 5 days ago (23 children)

Won't anyone think of the environment or small communities? AI is a nice-to-have, not an essential. We need to stop developing technology without thinking long term about the world we live in. We can't use the "oh we didn't know" excuse anymore.

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  • [–] 12 points 4 days ago

    Software Developers need to learn that there is a world outside of their projects. I do not care if it makes your life easier, this technology is having worldwide impacts we are not prepared for. It's leaf blower mentality. They don't care that the neighborhood stinks like 2 stroke exhaust, they don't care that it's loud as hell, they don't care where the leaves go, their yard is clean and that's all that matters.

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  • [+] -10 points 5 days ago (20 children)

    Global solar generation has increased by 50% in the last 2 years, meanwhile a token is something like 900 times less energy consuming than it was a year ago?

    Something comes first, almost free energy and deeply embedded ai usage or total environmental collapse, capitalism deems that we will find out which in due course.

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  • [–] 14 points 5 days ago* (19 children)

    Citations needed.

    I have not heard of a 900x drop. If that was true, we wouldn't be expanding data centres like we are.

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  • [+] -6 points 5 days ago (18 children)

    You're forgetting that usage can still go up while token cost goes down.

    Or rather, efficiency and usage can increase at the same time.

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  • [–] 8 points 5 days ago (7 children)

    The reason I dont believe you, is software efficenies are WAY cheaper than a data centre. If they could devlope existing infrastructure to hold the increase of usage like that, then they wouldn't expand hardware.

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  • [+] -7 points 5 days ago (6 children)

    You're just repeating the same point I've just addressed, so I'll explain in more detail.

    Data centres expanding is perfectly compatible with huge efficiency gains per token. If the cost of inference falls, companies can afford to run vastly more inference, serve more users, use larger models and embed AI into more products.

    It’s the same reason more fuel-efficient cars didn’t eliminate demand for roads or petrol. Efficiency lowers the cost of using something, which can increase total consumption.

    So “if software got more efficient, they wouldn’t need more data centres” is basically backwards. The relevant question is whether total AI demand is growing faster than efficiency is improving.

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  • [–] 7 points 5 days ago (5 children)

    So your really making the claim that there's over a 900x demand for AI in the last year?

    I'm calling bullshit.

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  • [–] -5 points 5 days ago* (4 children)

    No.

    ?

    When you lock onto something really hard in a discussion like this it becomes very obvious you're faltering and dont really have much to contribute.

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  • [–] 7 points 5 days ago* (3 children)

    Ypu claimed up above a 900x increase in token efficiency, and claim that demand is outpacing efficiencies.

    So yes you are.

    I'm calling bullshit on demand outpacing efficiencies in general.

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  • [–] -5 points 5 days ago* (2 children)

    Based on what rationale?

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  • [–] 6 points 5 days ago (1 child)

    You made the claim it is.

    Its based on every company I know pulling back on token spend because it keeps getting more expensive.

    Based on the fact the the growth they anticipate is everyone will use it everywhere. And thats not going to be true any time soon.

    Based on the fact queries cost more and more tokens on the new models.

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  • [–] -3 points 5 days ago

    The original point was that expanding data centres doesn’t disprove a big increase in efficiency per token. Usage, advsnced models/tokens per query and infrastructure can all grow at the same time as the energy required for an individual token falls. And thats an ongoing process.

    Companies you know cutting token spend, you thinking ubiquitous AI adoption is unrealistic, and newer models using more tokens per query are all arguments about future/total demand. None of them actually tell us whether a token is dramatically cheaper or more energy efficient to produce than it was a year ago. Realistically thats a learning curve problem, if someone is throwing a basic question at a model far more complex than it needs they are creating the inefficiency and that needs to be made more obvious/streamlined.

    I've not claimed demand had increased 900x. You inferred that from the existence of new data centres, which was the faulty bit of reasoning I was responding to in the first place.

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  • [–] 6 points 5 days ago (9 children)

    Are you also sayogn there's over a 900x increase in usage?

    Again, citations needed.

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  • [+] -8 points 5 days ago (8 children)

    You can find token energy efficiency information studies online, I was smashed when I pulled that figure out of my arse but the numbers are similarly huge.

    They're already orders of magnitude more energy efficient than we predicted just a few years ago and both the software and the hardware continue to accelerate that.

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  • [–] 12 points 5 days ago (7 children)

    Oh I know its getting more efficient, just no where close to 900x. I'm not gonna research for you. You provided the claim, not me.

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  • [+] -9 points 5 days ago (6 children)

    Yeah I can tell you dont want to look into it, that comes across very clear 😂

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  • [–] 4 points 5 days ago (3 children)

    Affirmanti incumbit probatio.

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  • [+] -6 points 5 days ago* (2 children)

    Ive already said i was wasted when I pulled that figure out of my ass.

    And the other guy has already acknowledged that the underlying sentiment that is has become a lot more efficient is true.

    If they need more than that, its there for them whenever they want.

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