About this episode

Matt Turck interviews Bryan Catanzaro about NVIDIA's approach to AI research and open models.

NVIDIA is a chip company. So why does it put hundreds of researchers on building AI models — and then give them away for free? Bryan Catanzaro is VP of Applied Deep Learning Research at NVIDIA and one of the people whose work quietly underpins modern AI: he helped create cuDNN (NVIDIA's first deep learning product), co-invented DLSS, and named and built Megatron, the framework behind how much of the industry trains large models. Today he leads Nemotron, NVIDIA's family of open models — and Nemotron 3 Ultra, released just weeks ago, is one of the strongest open-weights models to come out of the US. Matt Turck sits down with Bryan for a genuinely deep conversation: the real business logic behind a chip company building its own models, the state of open vs. closed AI, and whether the US is falling behind China in open models. Then they go inside Nemotron itself — four-bit (NVFP4) pretraining, hybrid Mamba-Transformer architecture, mixture-of-experts, multi-token prediction, and multi-teacher distillation — all explained in plain language. Plus a rare look at how a modern AI research org actually runs, what it was like working alongside Andrew Ng and Dario Amodei at Baidu, why Bryan…

People in this episode

Host: Matt Turck

Guest: Bryan Catanzaro

Topics covered

• AI research
• open models
• NVIDIA
• deep learning
• technology
• business logic of AI

Keywords

• NVIDIA
• AI models
• open source AI
• deep learning
• Nemotron
• cuDNN
• DLSS
• Megatron
• technology

Mentioned in this episode

Organizations: NVIDIA

Products: cuDNN, DLSS, Megatron, Nemotron, Nemotron 3 Ultra, NVFP4, Mamba-Transformer

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