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Cake day: June 15th, 2023

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  • Sure, but those are largely the big tech companies you’re talking about, and research tends to come from universities and private orgs.

    Well, that’s because the hyperscalers are the only ones who can afford it at this point. Altman has said ChatGPT 4 training cost in the neighborhood of $100M (largely subsidized by Microsoft). The scale of capital being set on fire in the pursuit of LLMs is just staggering. That’s why I think the failure of LLMs will have serious knock-on effects with AI research generally.

    To be clear: I don’t disagree with you re: the fact that AI research will continue and will eventually recover. I just think that if the LLM bubble pops, it’s going to set things back for years because it will be much more difficult for researchers to get funded for a long time going forward. It won’t be “LLMs fail and everyone else continues on as normal,” it’s going to be “LLMs fail and have significant collateral damage on the research community.”


  • There is real risk that the hype cycle around LLMs will smother other research in the cradle when the bubble pops.

    The hyperscalers are dumping tens of billions of dollars into infrastructure investment every single quarter right now on the promise of LLMs. If LLMs don’t turn into something with a tangible ROI, the term AI will become every bit as radioactive to investors in the future as it is lucrative right now.

    Viable paths of research will become much harder to fund if investors get burned because the business model they’re funding right now doesn’t solidify beyond “trust us bro.”