Zhenzhu (Jinzhu) Wu

speaker

420 appearances 1 recordings 1 series first heard Jul 2026 last heard 13 Jul

Zhenzhu (Jinzhu) Wu’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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Decoder with Nilay Patel · Yes, even Nvidia's head of automotive is fighting for compute · 13 Jul 2026 podcast

Other than the end-to-end model, which is basically you have pixel ink,

You have trajectory out.

We also have a classical stack.

Classical stack means it's more developed based on this safety standard as we know it.

It's a stack with many components, and each component can be verified using this known standard.

That's what I refer to as a classical stack.

And when you have two stacks basically kind of run in parallel, the classical stack is acting like a, sometimes we call it the big brother, but essentially it's a safety guardrail.

Try to verify all the trajectories from the end-to-end model.

and use it, you know, use the, let's say, known safety standard to verify it's safe at every frame.

So that's a very important concept, you know, we have, and not only concept, but the implementation we have in our stack.

And we will take this, obviously, this will be so critical for higher level autonomy L4.

So this is also the foundation of our, you know, kind of L4 stack where we have full redundancy

not only at a sensor set, but at a software architecture set.

So this is, I would say, the second point I want to make to answer your safety question.

And the number three, also basically, when we develop a model, basically, we are also trying to...

make the model reduce the hallucination as much as we can, right?

So the way to do that is really basically through massive validation.

We are looking at, we are building basically massive simulation test data, as I said, for every model we release.

Right now, we're looking at, in our program right now, we are running 5 million, basically, tests every day.

And obviously, roughly every day, we have 10 iterations of the model, the end-to-end model of Mayo.

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