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Cake day: July 7th, 2023

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  • Assuming it cost Microsoft $0 dollars to provide their AI services (this is up there with "Assuming all of physics stops working), and every dollar they make from Copilot was pure profit, it would take Microsoft 384 years to recoup one year of investment in AI.

    And thats without even getting into the fact that in reality these services are so expensive to run that every time a customer uses them its a net loss to the provider.

    When Amazon started out, no one had heard of them. Everyone has heard of Microsoft. Everyone already uses Microsoft’s products. Everyone has heard about AI. It’s the only thing in tech that anyone is talking about. It’s hard to see how they could be doing more to market this. Same story with OpenAI, Facebook, Google, basically every player in this space.

    Even if they can solve the efficiency problems to the point where they can actually make a profit off of these things, there just isn’t enough interest. AI does plenty of things that are useful, but nothing that’s truly vital, and it needs to be vital to have any hope of making back the money that’s gone into it.

    At present, there simply is not a path to profitability that doesn’t rely on unicorn farts and pixie dust.



  • Yes, but the basic problem doesn’t change; you’re spending billions to make millions. And Deepseek’s approach only works because they’re able to essentially distill the output of less efficient models like Llama and GPT. So they haven’t actually solved the underlying technical issues, they’ve just found a way to break into the industry as a smaller player.

    At the end of the day, the problem is not that you can’t ever make something useful with transformer models; it’s that you cannot make that useful thing in a way that is cost effective. That’s especially a problem if you expect big companies like Microsoft or OpenAI to continue to offer these services at an affordable price. Yes, Copilot can help you code, but that’s worth Jack shit if the only way for Microsoft to recoup their investment is by charging $200 a month for it.



  • Testing shows that current models hallucinate more than previous ones. OpenAI rebeadged ChatGPT 5 to 4.5 because the gains were so meagre that they couldn’t get away with pretending it was a serious leap forward. “Reasoning” sucks; the model just leaps to a conclusion as usual then makes up steps that sound like they lead to that conclusion; in many cases the steps and the conclusion don’t match, and because the effect is achieved by running the model multiple times the cost is astronomical. So far just about every negative prediction in this article has come true, and every “hope for the future” has fizzled utterly.

    Are there minor improvements in some areas? Yeah, sure. But you have to keep in mind the big picture that this article is painting; the economics of LLMs do not work if you’re getting incremental improvements at exponential costs. It was supposed to be the exact opposite; LLMs were pitched to investors as a “hyperscaling” technology that was going to rapidly accelerate in utility and capability until it hit escape velocity and became true AGI. Everything was supposed to get more, not less, efficient.

    The current state of AI is not cost effective. Microsoft (just to pick on one example) is making somewhere in the region of a few tens of millions a year off of copilot (revenue, not profit), on an investment of tens of billions a year. That simply does not work. The only way for that to work is not only for the rate of progress to be accelerating, but for the rate of accelleration to be accelerating. We’re nowhere near close to that.

    The crash is coming, not because LLMs cannot ever be improved, but because it’s becoming increasingly clear that there is no avenue for LLMs to be efficiently improved.










  • The key detail is that, like with rear brake lights, they extinguish when the foot is removed from the brake pedal. So it’s not so much the presence of the brake light, but the presence of an inactive brake light that would, serve as a warning that a car is about to start moving. This would be very helpful to drivers on a road when other drivers are pulling out too early from a side road or driveway. That little bit of extra warning is, in many situations, enough for you to pump the brakes, hit the horn, or both.








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