Pretty sure this "compute is the new oil" thesis fell flat when OAI failed to deliver on GPT-5 hype, and all the disappointments since.

It's still all about the (yet to be collected) data and advancements in architecture, and OAI doesn't have anything substantial there.

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XorNot 3 days ago | parent | next [-]

It's absolutely no longer about the data. We produce millions of new humans a year who wind up better at reasoning then these models but don't need to read the entire contents of the Internet to do it.

A relatively localized, limited lived experience apparently conveys a lot that LLM input does not - there's an architecture problem (or a compute constraint).

	▲	pphysch 3 days ago \| parent [-]
		AI having societally useful impact is 100% about the data and overall training process (and robotics...), of which raw compute is a relatively trivial and fungible part. No amount of reddit posts and H200s will result in a model that can cure cancer or drive high-throughput waste filtering or precision agriculture.

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kingstnap 3 days ago | parent | prev [-]

I think GPT 5 is pretty good. My use case is vscode copilot and the GPT 5 Codex model and the 5 mini model are a lot better than 4.1. o4 mini was pretty good too.

Its slow as balls as of late though. So I use a lot of sonnet 4.5 just because it doesn't involve all this waiting even though I find sonnet to be kinda lazy.

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pphysch 3 days ago | parent [-]

Sure, GPT-5 is pretty good. So are a dozen other models. It's nowhere near the "scary good" proto-AGI that Altman was fundraising on prior to its inevitable release.

	▲	Libidinalecon 2 days ago \| parent [-]
		Even more so where is the model that is beating GPT-5? This level that fell flat should have been easy to jump over if the scaling narratives were holding.