Obviously you don't need to train new models to operate existing ones.

I think I trust the semianalysis estimate ($250M) more than this estimate ($2B), but who knows? I do see my revenue estimate was for this year, though. However, $4B revenue on $250M COGS...is still staggeringly good. No wonder amazon, google, and Microsoft are tripping over themselves to offer these models for a fee.

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singron 8 hours ago | parent | next [-]

You need to train new models to advance the knowledge cutoff. You don't necessarily need to R&D new architectures, and maybe you can infuse a model with new knowledge without completely training from scratch, but if you do nothing the model will become obsolete.

Also the semianalysis estimate is from Feb 2023, which is before the release of gpt4, and it assumes 13 million DAU. ChatGPT has 800 million WAU, so that's somewhere between 115 million and 800 million DAU. E.g. if we prorate the cogs estimate for 200 DAU, then that's 15x higher or $3.75B.

	▲	ghc 7 hours ago \| parent [-]
		> You need to train new models to advance the knowledge cutoff That's a great point, but I think it's less important now with MCP and RAG. If VC money dried up and the bubble burst, we'd still have broadly useful models that wouldn't be obsolete for years. Releasing a new model every year might be a lot cheaper if a company converts GPU opex to capex and accepts a long training time. > Also the semianalysis estimate is from Feb 2023, Oh! I missed the date. You're right, that's a lot more expensive. On the other hand, inference has likely gotten a lot cheaper (in terms of GPU TOPS) too. Still, I think there's a profitable business model there if VC funding dries up and most of the model companies collapse.

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hamburga 10 hours ago | parent | prev | next [-]

But assuming no new models are trained, this competitive effect drives down the profit margin on the current SOTA models to zero.

	▲	ghc 10 hours ago \| parent [-]
		Even if the profit margin is driven to zero, that does not mean competitors will cease to offer the models. It just means the models will be bundled with other services. Case in point: Subversion & Git drove VCS margin to zero (remember BitKeeper?), but Bitbucket and Github wound up becoming good businesses. I think Claude Code might be the start of how companies evolve here.

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dvfjsdhgfv 4 hours ago | parent | prev [-]

> Obviously you don't need to train new models to operate existing ones.

For a few months, maybe. Then they become obsolete and, in some cases like coding, useless.