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Cake day: January 12th, 2025

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  • It’s not about hampering proliferation, it’s about breaking the hype bubble. Some of the western AI companies have been pitching to have hundreds of billions in federal dollars devoted to investing in new giant AI models and the gigawatts of power needed to run them. They’ve been pitching a Manhattan Project scale infrastructure build out to facilitate AI, all in the name of national security.

    You can only justify that kind of federal intervention if it’s clear there’s no other way. And this story here shows that the existing AI models aren’t operating anywhere near where they could be in terms of efficiency. Before we pour hundreds of billions into giant data center and energy generation, it would behoove us to first extract all the gains we can from increased model efficiency. The big players like OpenAI haven’t even been pushing efficiency hard. They’ve just been vacuuming up ever greater amounts of money to solve the problem the big and stupid way - just build really huge data centers running big inefficient models.




  • There are many clear use cases that are solid, so AI is here to stay, that’s for certain. But how far can it go, and what will it require is what the market is gambling on.

    I would disagree on that. There are a few niche uses, but OpenAI can’t even make a profit charging $200/month.

    The uses seem pretty minimal as far as I’ve seen. Sure, AI has a lot of applications in terms of data processing, but the big generic LLMs propping up companies like OpenAI? Those seems to have no utility beyond slop generation.

    Ultimately the market value of any work produced by a generic LLM is going to be zero.