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> If I understand correctly, you're saying people are compute-poor but not necessarily GPU-poor because there's a lot of GPUs out there but nowhere to plug them into? If so, I'm not sure that distinction matters to the GP's point that there is too much demand to call this an oversupply.

It's a distinction without a difference if your issue is getting hold of a GPU.

But there's a significance to it if you are trying to use demand for a GPU as a proxy for demand for AI. That is where the industry is making serious mistakes.

> I am not sure Microsoft thinks there will be an oversupply either

https://finance.yahoo.com/news/microsoft-ceo-says-overbuild-...

The rest of your comment I am not going to address because it's kind of unfalsifiable. Hypotheses about what AI might be able to do in principle aren't all that useful when talking about even medium-to-long-term demand for what LLMs and GANs can provably do now.



> https://finance.yahoo.com/news/microsoft-ceo-says-overbuild-...

Oh I think I recall this. However Satya said that more a year and a half ago, eons in AI time, and maybe he even believed it at the time. But since then Microsoft's annual CapEx spend has gone from $65B to $116B. Not the actions of somebody concerned about an overbuild.

> But there's a significance to it if you are trying to use demand for a GPU as a proxy for demand for AI. That is where the industry is making serious mistakes.

Ah I see what you're saying. The AI industry is certainly not looking at just GPU demand as a proxy for AI demand, primarily because they themselves are creating the GPU demand -- but that is in response to other signals they are getting. Actually that's what I hoped to illustrate with the rest of my analysis; rather than a hypothesis of what AI might be able to do, it was more a hypothesis of the signals the industry is looking at (including various economic data sources) that drive its current spending frenzy.




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