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Comment by breadwinner | Hacker News Reader

Part of the reason Musk, Zuckerberg, Ellison, Nadella and other CEOs are bragging about the number of GPUs they have (or plan to have) is to attract talent.

Perplexity CEO says he tried to hire an AI researcher from Meta, and was told to ‘come back to me when you have 10,000 H100 GPUs’

See https://www.businessinsider.nl/ceo-says-he-tried-to-hire-an-...

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Maybe DeepSeek ain't it, but I expect a big "box of scraps"[1] moment soon. Constraint is mother of invention, and they are evading constraints with a promise of never-ending scale.

[1] https://youtu.be/9foB2z_OVHc?si=eZSTMMGYEB3Nb4zI

That's a weird way to read into it.

This reminds of the joke in physics, in which theoretical particle physicists told experimental physicists, over and over again, "trust me bro, standard model will be proved at 10x eV, we just need a bigger collider bro" after another world's biggest collider is built.

Wondering if we are in a similar position with "trust me bro AGI will be achieved with 10x more GPUs".

The difference is the AI researchers have clear plots showing capabilities scaling with GPUs and there's not a sign that it is flattening so they actually have a case for saying that AGI is possible at N GPUs.

Sauce? How do you even measure "capabilities" in that regard, just writing answers to standard tests? Because being able to ace a test doesn't mean it's AGI, it means its good at taking standard tests.

This is the canonical paper. Nothing I've seen seems to indicate the curves are flattening, you can ask "scaling what" but the trend is clear.

https://arxiv.org/pdf/2001.08361

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