Yunzhu Li

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208 appearances 1 recordings 1 series first heard Jul 2026 last heard 28 Jul

Yunzhu Li’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 Jul 2026 with 1.

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The a16z Show · Fei-Fei Li on Spatial Intelligence and Robotics · 28 Jul 2026 podcast

And because our digital environment has proven alignments with the real world, so meaning whatever happens in the scene is also likely to happen in the real environment.

If a checkpoint is working better in the simulation, it's also highly likely to also work better in the real environment, as we have also been discussed in the blog post.

So that actually gives our clients very strong confidence

in actually using the data using the signal from the digital environment to do scalable safe and much faster evaluations of their robotic systems great so that is on the evaluation then on the training so on the training side so basically like i also mentioned it's about controllability

So you want to control all the different possible variations of states, parameters, lighting, frictions, physical parameters, like even object geometry, object types.

So you want to make sure you have sufficient coverage of all different kinds of scenarios, such that we'll be able to generate informative data.

for your robots to be robust.

And this is just going to be so hard to do just in the real environment.

Like we discussed, if you do tidal operation, the speed at which you are collecting data is slow.

You're also limited by how many robots you have, how many tidal operation devices you have.

There's a whole different kind of challenges around all the data operations around it.

But in simulation, everything can be controllable.

Everything can be systematic and everything can be understood at a level where you know exactly and making claims about exactly what distribution you have covered.

To develop confidence about within the distribution, we know the robot will work.

So those kinds of confidence and efficiency and scalability is something that our clients also value to use our digital worlds for the training of robotic systems.

will begin so what we've been building you can imagine is a infrastructure like with the softwares around these infrastructures for people to for them build words such as robot can learn and evaluate and these infrastructures is naturally model agnostic and embodiments agnostic so i just want to be very clear just because this is actually a very subtle for you it's obvious but it's a very subtle point which is um

Yeah.

So for our customers right now, they have all different kinds of robots.

Some are using, for example, single robot arms.

Some are using bi-manual.

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