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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Appearances
It maybe knows how to retrieve relevant information, maybe has a history of other information that it has retrieved for past problems.
And it
can put information into the context of the model.
And the nice thing about that is that information is really clear to the model.
Unlike the training data the model was trained on where it's all kind of like trillions of tokens stirred together into a soup of hundreds of billions or trillions of parameters, but it's all less clear than the actual context that the model sees directly for this particular problem or use case.
And then I think being able to understand what tools are available, which ones are gonna help me solve the, help the model solve this next phase of the problem, how to decompose the problem into a sequence of tool calls, maybe trying multiple approaches to solve the problem and seeing which ones work and be able to evaluate that.
This is the whole orchestration of complex agent and multi-agent systems that I think is
going to be more and more important and super exciting times over there.
Yeah, I think a really good way to do it is to use these models and harnesses and tools and so on to try to solve problems.
And then sometimes you can actually see where the models are failing.
And often you can actually make the model work better and succeed at that kind of problem by not just adjusting the model parameters, which is hard to do from the outside, but from creating better guidelines for the model, writing skills for the model to know how to use different tools that would be incredibly useful for solving this particular class of problem.
And I think as you do that, you end up on this kind of
improving, self-improving of the setup that you're trying to use to solve things.
And that's a really good way to get better at understanding what additional information the model would want in order to become more capable.
Yeah, I mean, I guess Sanjay and I were working a few weeks ago.
And we often do some amount of performance improvement for very low level libraries.
And we have a micro benchmark library we've written at Google where you can write micro benchmarks of how long different kinds of operations take or how long does it take to populate this data structure or whatever.
And sometimes those data structures are used on millions of processes across Google.
So it's actually pretty important to make sure they're high performance.
And so you can write micro benchmarks.
Showing 81–100 of 343 · page 5 of 18
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