Why NVIDIA Is Giving Away AI Models | Bryan Catanzaro

**Bryan Catanzaro** (0:00)
If you accept as the truth that we're going to be running at the limit, then what that means is that the way to get more intelligence is to be more efficient. We can't get more intelligence by applying more force if we're already at the limit. We have to be more thoughtful about how we use what we have. We build tools, we build external organs that help us solve problems.
We have an external stomach, we call it kitchen. Now we're creating an external brain. What is the implications of an external brain? Pretty profound. Nobody actually really knows.

**Matt Turck** (0:32)
Hi, I'm Matt Turck. Welcome back to The MAD Podcast. Open source AI is having yet another moment with powerful new models arriving almost weekly. My guest today is one of the very best people to unpack it all. Bryan Catanzaro leads Nemotron, Nvidia's family of open foundation models. Now, not everyone realizes Nvidia has a massive effort to build frontier AI models, but it employs hundreds of AI researchers, and Nemotron 3 Ultra immediately became the number one US open weights model when it was released just a couple of weeks ago. We begin this conversation with the state of open source AI and the race between the US and China, and then we go deep inside Nemotron. 4-bit training, hybrid Mamba-Transformer architecture, mixture of experts, multi-token prediction, and multi-teacher distillation all in plain language. And finally, we get a rare look at how a modern AI research organization actually runs. How you get many brilliant minds to build one model instead of a hundred papers. Please enjoy this awesome conversation with Bryan Catanzaro.
All right, Bryan, excited to do this. It seems that open source is having a banner year. So you guys at Nvidia just released Nemotron 3 Ultra, which is an important moment and the best open source, open weight model in the US. That was just a few days ago.
And then, even more recently, GLM 5.2 came out, and that was another moment. So it seems that things are accelerating in open source AI. It feels like a great place to start. What's your assessment about where we are and how wide the gap between closed source and open source currently is?

**Bryan Catanzaro** (2:10)
Well, it's really exciting to see all of the energy going into open technologies for AI, because we know that open technologies make it possible for people to innovate. The Internet is such a great example of that. We actually did have closed Internets. I don't know if you remember things like America Online and Prodigy back in the day, and they were great.
Open Internet has also been amazing. So many different companies have been able to figure out how to transform their work thanks to an open technology. The application of the Internet to retail is very different from the application of the Internet to health care or manufacturing, but all of them have been totally transformed by the Internet. AI, I believe, is also a very transformational technology and also a technology that needs to be applied in very diverse ways. Because of that, I believe that open technologies for AI are really fundamental. It's very exciting to see continued investment and development of open technologies for AI from so many different organizations around the world.
And, you know, I hope that that continues.

**Matt Turck** (3:23)
And what's your sense for how far behind open source is compared to closed source? It's been the big trend of the last few years has been this sort of narrowing gap. Do you think that open source is almost there or the bar keeps getting raised by the closed source models?

**Bryan Catanzaro** (3:43)
Well, I feel like this question, it's maybe a tempting question because, you know, it's fun to set up kind of competition. But I actually feel like the whole AI community is moving very fast.
And if you look, for example, at the progress in AI, whether it's closed or open, just over the past three months, it's been incredible. And so if you're in a field that's moving really, really fast, I think that's more important than any particular gaps that might exist between different models. Because the most important thing is, how is AI developing as a field?

**Matt Turck** (4:17)
What do you think the drivers are to continue to progress in open source AI? Is that the communities and big companies like Nvidia being behind it? Is that the global competition with China? What propels open source AI forward?

**Bryan Catanzaro** (4:34)
I think there's a number of things that are pushing open technologies for AI forward. One is just the demand. There's so many organizations that want to customize AI and want to integrate it deeply into their work in a way that really requires open technologies for AI.