Jensen Huang on NVIDIA, Extreme Co-Design, CUDA, and the AI Revolution
In this Lex Fridman Podcast excerpt, Jensen Huang discusses how NVIDIA approaches the AI era through extreme co-design: optimizing not just chips, but the full system stack from software and algorithms to racks, power, and cooling. He explains why modern AI workloads must be distributed across many machines and why that creates deep challenges in computation, networking, and system architecture. Huang also reflects on NVIDIA’s long transition from a GPU accelerator company to a broader computing platform, including key steps such as programmable shaders, FP32, Cg, and CUDA. The conversation emphasizes the strategic decisions that helped NVIDIA expand its reach and become foundational to AI infrastructure.