Jensen Huang

Some of the brightest minds.

What's your vision there?

First.

If we're going to be a great AI computing company, we have to understand how AI models are evolving.

One of the things that I love about Nemotron 3 is it's not just a pure transformer model, it's transformer and SSMs.

And we were early in developing the conditional GANs, that progressive GANs, which led step-by-step to diffusion.

And so the fact that we're doing basic research

in model architecture and in different domains gives us visibility into what kind of computing systems would do a good job for future models.

And so it is part of our extreme co-design strategy.

Second, I think we rightfully recognize that on the one hand, we want world-class models as products and they should be proprietary.

On the other hand, we also want AI to diffuse into every industry and every country, every researcher, every student.

And if everything is proprietary, it's hard to do research and it's hard to innovate on top of, around, with.

And so open source is fundamentally necessary for many industries to join the AI revolution.

NVIDIA has the scale and we have the motives to not only skills, scale, and motivation to build and continue to build these AI models for as long as we shall live.

And so therefore, we ought to do that.

We can open up, we can activate every industry, every researcher, every country to be able to join the AI revolution.

There's a third reason, which is recognizing that AI is not just language.

These AIs will likely use tools and models and sub-agents that were trained on other modalities of information.

Maybe it's biology or chemistry or laws of physics or fluids and thermodynamics and

Not all of it is in language structure.