Investors are barely breaking even as the venture is hardly making any profits due to a shortage of chips, divided interests, and more.

… OpenAI has already seen a $540 million loss since debuting ChatGPT.

… OpenAI uses approximately 700,000 dollars to run the tool daily.


⚠️ First off, apologies as I didn’t cross check. Take it w/ a grain of salt.


This piece of news, if true, somehow explains why OpenAI has been coming up w/ weird schemes for making $$$ like entering the content moderation space.

On a similar note, I wonder if this had been a key driver (behind the scenes) in the recent investment in open source AI initiatives (Haidra comes to my mind?) Perhaps some corporations who haven’t got enough $$$ to fund their own dedicated research group are looking to benefit from an open source model?

  • TehPers@beehaw.org
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    1 year ago

    Finally, there are positive economic externalities to public AI availability.

    There are positive economic externalities to public everything availability. We don’t live in this kind of world though, someone will always try to claim a larger share due to human nature. That being said, I’m not really interested in arguing about the political feasibility (or lack thereof) of having every resource being public.

    With how many people are already using AI, it’s frankly mind boggling that they’re only losing $700k a day.

    There are significant throttles in place for people who are using LLMs (at least GPT-based ones), and there’s also a cost people pay to use these LLMs. Sure you can go use ChatGPT for free, but the APIs cost real money, they aren’t free to use. What you’re seeing is the money they lost after all the money they made as well.

    You’re also ignoring the fact that costs don’t scale proportionally with usage. Infrastructure and labor can be amortized over a greater user base. And these services will get cheaper to run per capita as time goes on and technology improves.

    I don’t disagree that the services will get cheaper and that costs don’t scale proportionally. You’re most likely right - generally speaking, that’s the case. What you’re missing though is that there is an extreme shortage of components. Scaling in this manner only works if you actually have the means to scale. As things stand, companies are struggling to get their hands on the GPUs needed for inference.

    • Clymene@lemmy.ml
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      1 year ago

      There are positive economic externalities to public everything availability. We don’t live in this kind of world though, someone will always try to claim a larger share due to human nature.

      Saying “Things are inevitably bad because of human nature” is just very weird, since we obviously do have good policies and we try to solve other problems like crime and poverty. It sounds like you already agree that this is good policy? You’re just saying it’s not politically feasible? OK, sure, we probably don’t disagree then.

      That being said, I’m not really interested in arguing about the political feasibility (or lack thereof) of having every resource being public.

      I am obviously NOT arguing that every resource should be public. This discussion is about AI, which was publicly funded, trained on public data, and is backed by public research. This sleight of hand to make my position sound extreme is, frankly, intellectually dishonest.

      there’s also a cost people pay to use these LLMs.

      OK, keep the premium subscription going then.

      What you’re missing though is that there is an extreme shortage of components.

      There’s a shortage, but it’s not “extreme”. ChatGPT is running fine. I can use it anytime I want instantly. You’d be laughed out of the room if you told AI researchers that ChatGPT can’t scale because we’re running out of GPUS. You seem to be looking for reasons to be against this, but these reasons don’t make sense to me, especially since this particular problem would exist whether it’s publicly owned or privately owned.

      • TehPers@beehaw.org
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        1 year ago

        OK, sure, we probably don’t disagree then.

        We probably don’t here, but like I said I’m not really interested in discussing the political feasibility of it.

        I am obviously NOT arguing that every resource should be public. This discussion is about AI, which was publicly funded, trained on public data, and is backed by public research. This sleight of hand to make my position sound extreme is, frankly, intellectually dishonest.

        I don’t think I ever disagreed that the models themselves should be public, and there are already many publicly available models (although it would be nice if GPT-N were). What I disagree with is the service being free. The service costs a company real money and resources to maintain, just like any other service. If it were free, the only entity that could reasonably run the models is the government, but at this point we might as well also have the government run public git servers, public package registries, etc. Honestly, I’m not sure what impression you expected me to get, considering the claim that a privately run service using privately paid-for resources should be free to the public.

        There’s a shortage, but it’s not “extreme”. ChatGPT is running fine. I can use it anytime I want instantly. You’d be laughed out of the room if you told AI researchers that ChatGPT can’t scale because we’re running out of GPUS.

        Actually no, I work directly with AI researchers who regularly use LLMs and this is the exact impression I got from them.