Jeff Dean

speaker

343 appearances 1 recordings 1 series first heard Aug 2026 last heard 1 Aug

Jeff Dean’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Aug 2026 with 1.

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Y Combinator Startup Podcast · Jeff Dean: The 1% Rule for Building in AI · 1 Aug 2026 podcast

So now that completely changes how you would do science, right?

Because now you have 10 million things to screen.

You know, you could do that while you go to lunch rather than it being a six month endeavor where you could try to scrape together enough compute to run all these simulations.

And

I think there's a lot of room in a lot of domains for much faster validation models, possibly learned validation models that can get you a approximation to the true answer much more rapidly.

And that changes how those experimental loops can be thought of and how quickly you can go around those loops.

Yeah.

I mean, I think, uh,

Well, clearly machine learning itself is one.

So can we have a model that is able to recursively self-improve itself by running lots of experiments?

And if you think about how models are improved today in large research teams, what usually happens is people think of some ideas, they run a bunch of small scale experiments, they see if those small scale experiments worked out well.

If so, they take the most promising ones of those and they try them at larger scale.

and that gets then evaluated, and then the results get integrated together into a new recipe for your model.

But I think there's no real impediment to making that be a much more automated loop where the model itself decides it's gonna explore, or maybe with a nudge from some people,

at the various highest level, like, oh, why don't you try some new ideas around model architectures that incorporate this?

And then they will go run lots of experiments, see which ones work, and then those will get incorporated at a much more rapid rate.

And, you know, effectively you want to optimize, you know, your discoveries per unit of compute input.

Yeah.

Yeah, I mean, yeah.

I mean, I think I don't fault the program committee because, you know, a lot of times a paper gets three reviews and someone will look at, one of the reviewers will look at it, and in this case they said, oh, it's unlikely to have significant impact.

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