#494 – Jensen Huang: NVIDIA – The $4 Trillion Company & the AI Revolution

Faster chips deliver limited gains when other parts of a computing job dominate its running time. In his interview with Lex Fridman, NVIDIA's chief executive explains why the company designs processors, networking, software, power and cooling together. Large AI workloads span many computers, making communication and coordination part of the performance problem.

His example makes the limit tangible: if computation accounts for half the elapsed time, making that computation effectively instantaneous can only double overall speed. NVIDIA's stated approach is therefore to redesign the whole system around the workload, including how work and data are distributed. A chip's standalone speed describes only part of that system.

“I always say that NVIDIA is the house that GeForce built, because it was GeForce that took CUDA out to everybody.”

Jensen Huang

“inference is thinking, and I think thinking is hard. Thinking is way harder than reading.”

Jensen Huang

“And I think OpenClaw did for agentic systems what ChatGPT did for generative systems. And I just think it's a very big deal.”

Jensen Huang

“Three decades, I don't know how many tens, hundreds of billions of dollars of business we've done through them, and we don't have a contract.”

Jensen Huang

“It wasn't three people that made CUDA successful. It was 43,000 people that made CUDA successful.”

Jensen Huang