• hello_hello [comrade/them]@hexbear.net
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    21 days ago

    China seems long overdue to overtake the collective West in LLMs. They have societal support, industrial base and government planning to do so.

    Nvidia corporation and government sanctions are really what’s preventing a full takeover (as well as capitalist mutual aid)

  • fox [comrade/them]@hexbear.net
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    21 days ago

    Last year David Cahn wrote an article for VC firm Sequoia Capital titled AI’s $600 Billion Question.. The gist being that AI needs to make that amount of money merely to break even. There’s no shot in hell that with the massive investment in data centers and no changes to pricing that the hole isn’t deepening.

    • Lyudmila [she/her, comrade/them]@hexbear.net
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      20 days ago

      Oh, the pricing is changing, and it’s just gonna deepen the hole even more because most people are gonna go “$20 a month? For what?” and suddenly the user base that is currently the unprofitable product will largely conglomerate onto the remaining free platforms bogging them down so hard they also have to change their pricing model.

      There simply is no way to make the current stuff cost effective at the scale they’re currently using, even with the bleeding edge most efficient models. Models need to become multiple orders of magnitude more efficient to become even remotely viable. Running distills on local machines is the only option that makes sense financially for actual use because you’re putting all of the energy and compute costs onto the user directly.

      The big push right now is to get NPUs into the hardware into every single person’s hands because… reasons. Microsoft Copilot+, Chromebook Plus, Gemini Built-in, Apple Intelligence, etc. are all examples of this which are still highly dependent on cloud computing, but the effort is to make as much as possible local. What they’re actually able to do with that hardware kinda remains to be seen because most of it is barely doing anything at this point.

      “Why waste time on optimization so you could run software locally when instead you could spend 1000x as much on hardware to run inefficient code?” 10/10 dentists software engineers.

    • Thing is, how does this fit in with the neoliberal tech trend of just… losing money?

      The entire gig economy was subsidised by massive loans and investments, with only a few companies just recently reaching any kind of profitability! Uber only turned +$9mil this year after accruing nearly $250mil in debt!!!

      These businesses are run like states: massive debt pools held aloft by the debt and supplementary income that pays off other debts. You might as well be able to buy bonds for these things.

      My question is though, how does this fit into Marxist economic theory? I’m aware of the “reducing rate of profit” and such, but how does this fit for swathes of the economy operating on negative profit as its ideal model? I suppose these firms are “micro” relative to the “macro” of the whole economy.

      Are these gargantuan loss making businesses dragging the whole system down with them?

  • Des [she/her, they/them]@hexbear.net
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    21 days ago

    don’t forget to repeatedly thank chat gpt in the prompt. oh have the AI voice read everything out too

    yes short term energy suck but you are basically contributing the bankrupting this company

    • LanyrdSkynrd [comrade/them, any]@hexbear.net
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      20 days ago

      Microsoft owns most of the upside of OpenAI already. Everything they’ve invested so far is recoupable as 20% of future profits, and much of what was invested was in the form of Azure credits. They have a perpetual license to any OpenAI technology developed to date and in the future until they achieve AGI.

      I don’t see why they’d want OpenAI. What they really want is a bunch of other suckers to come in and keep financing it so they can profit from the previous deal.