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← People and their mental models

Noam Brown's mental models

5 claims Noam Brown made fit 5 mental models. Most often: Bottlenecks, Collective action problems, Incentives. Everything they said here.

Models they name

Their own words name the idea.

Bottlenecks

A system moves only as fast as its narrowest point; speed up anything else and nothing changes.

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There will be no overnight intelligence explosion, because a model's best work takes so much test-time compute that time itself is the bottleneck.

  1. Noam Brown Research scientist at OpenAI and I don't think we're headed to that world largely because of the fact that the models rely so much on large scale test time compute in order to achieve um their greatest intelligence. If you if it requires so much test time on compute to unlock the full capabilities of the model, then that means you're bottlenecked by time Really Big Test-Time Compute in AI Changes Benchmarks, Safety and Research with OpenAI's Noam Brownyoutube.com · 26 Jun 2026 · 26:20 into the videoAll korrents from this video
    and I don't think we're headed to that world largely because of the fact that the models rely so much on large scale test time compute in order to achieve um their greatest intelligence. If you if it requires so much test time on compute to unlock the full capabilities of the model, then that means you're bottlenecked by time

Models we see in what they say

Our reading: their claim applies the idea without naming it. The claim is theirs; filing it here is ours.

Collective action problems

What everyone would gain from, nobody provides alone, so shared goods need someone or something to hold people together.

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Every lab knows the benchmark grid is the wrong way to present a model, and publishes it anyway because everybody else does.

  1. Noam Brown Research scientist at OpenAI And so you kind of end up in this this bad equilibrium where everybody kind of knows that it's a bad equilibrium, but like nobody wants to break out. And I I felt like, okay, well, if I just hopefully come out and say like, look guys, let's all recognize that we're in a bad equilibrium and let's move to this different equilibrium where we're we're plotting things with an X-axis Really Big Test-Time Compute in AI Changes Benchmarks, Safety and Research with OpenAI's Noam Brownyoutube.com · 26 Jun 2026 · 32:57 into the videoAll korrents from this video
    And so you kind of end up in this this bad equilibrium where everybody kind of knows that it's a bad equilibrium, but like nobody wants to break out. And I I felt like, okay, well, if I just hopefully come out and say like, look guys, let's all recognize that we're in a bad equilibrium and let's move to this different equilibrium where we're we're plotting things with an X-axis

Incentives

Look at what people are rewarded for; it explains more behaviour than what they say, your own included.

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Evaluating a model properly would mean delaying its release, and competitive pressure means no lab will.

  1. Noam Brown Research scientist at OpenAI It's actually very difficult because, yeah, you would have to the only way to to really do the evaluations is then delay the model release cycle. Um and you know there's a lot of competitive pressure right now to not do that. Really Big Test-Time Compute in AI Changes Benchmarks, Safety and Research with OpenAI's Noam Brownyoutube.com · 26 Jun 2026 · 16:54 into the videoAll korrents from this video
    It's actually very difficult because, yeah, you would have to the only way to to really do the evaluations is then delay the model release cycle. Um and you know there's a lot of competitive pressure right now to not do that.

Play long games

A longer horizon makes some problems solvable and some short-term wins look like what they are.

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A frontier lab should not spend its researchers harvesting results out of today's models; the payoff is in building the next one.

  1. Noam Brown Research scientist at OpenAI we are trying to encourage people to not spend all their time just like going through all the mathematical open problems physics problems and um just seeing pushing the models to their limits to see what they can prove or disprove. Really Big Test-Time Compute in AI Changes Benchmarks, Safety and Research with OpenAI's Noam Brownyoutube.com · 26 Jun 2026 · 20:14 into the videoAll korrents from this video
    we are trying to encourage people to not spend all their time just like going through all the mathematical open problems physics problems and um just seeing pushing the models to their limits to see what they can prove or disprove.

When a measure becomes a target

Reward a number and people, or machines, will find ways to move the number without the thing it measured (Goodhart's law).

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Running a model five times and keeping the best answer buys a higher benchmark score without buying a better model.

  1. Noam Brown Research scientist at OpenAI Um so if you say okay well we're going to instead of just running this model once we're going to run it five times and take the best of the five responses or like ask a judge which one it thinks is best then you can get much higher scores than that model. And so it's really easy to make something that looks a lot better on paper but is actually not better once you control for the amount of test time compute. Really Big Test-Time Compute in AI Changes Benchmarks, Safety and Research with OpenAI's Noam Brownyoutube.com · 26 Jun 2026 · 7:18 into the videoAll korrents from this video
    Um so if you say okay well we're going to instead of just running this model once we're going to run it five times and take the best of the five responses or like ask a judge which one it thinks is best then you can get much higher scores than that model. And so it's really easy to make something that looks a lot better on paper but is actually not better once you control for the amount of test time compute.