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Gary Marcus endorses Noam Brown’s claim that “with today’s AI models…

2026-05-13 · 16:04 UTC ·@GaryMarcus ·0 min read

Brief

Gary Marcus amplifies Noam Brown’s claim that, for current AI systems, intelligence scales with inference compute and should be measured as intelligence per token or per dollar (model comparisons became unreliable in 2024). Marcus adds that humans achieve high intelligence on ~20 watts, so new architectures may rival raw compute gains in the long term.

Why it matters

Gary Marcus endorses Noam Brown’s claim that “with today’s AI models, intelligence is a function of inference compute.”

Key details

  • Noam Brown (polynoamial) says model comparisons by a single number became meaningless in 2024 and what matters is intelligence per token or per dollar — crucial for products like Codex.
  • Marcus counters that humans run on roughly 20 watts, arguing future architectural innovations could matter as much as, or more than, raw compute over the long run.
Source evidence

probably correct, from @polynoamial: “with today’s AI models, intelligence is a function of inference compute.”

but what about tomorrow’s models? never forget that humans are remarkably
intelligent (though flawed) on a budget of 20 watts.

in the long run, new architecture innovations may matter as much as more than raw compute.

Noam Brown (@polynoamial)

A hill that I will die on: with today's AI models, intelligence is a function of inference compute. Comparing models by a single number hasn't made sense since 2024. What matters is intelligence per token or per $.

This is especially true when using it in a product like Codex.

— https://nitter.net/polynoamial/status/2047387675762802998#m