NVIDIA’s Jensen Huang on Reasoning Models, Robotics, and Refuting the “AI Bubble” Narrative
Timestamps are as accurate as they can be but may be slightly off. We encourage you to listen to the full context.
Podcast Summary
NVIDIA CEO Jensen Huang joins Sarah Guo and Elad Gil for a comprehensive discussion on the state of AI as we enter 2026. (00:17) Huang reflects on the biggest breakthroughs of 2025, including dramatic improvements in AI reasoning and grounding that addressed skepticism around hallucination, while highlighting the profitability of inference tokens with companies like OpenEvidence achieving 90% gross margins. (02:22) The conversation covers critical themes including job creation versus displacement, the importance of open source AI for innovation, the role of energy infrastructure in AI growth, and why the "doomer" narratives around AI may be counterproductive to technological advancement.
- Main themes focus on AI's practical applications across industries, the infrastructure boom driving job creation, the strategic importance of US-China relations in AI development, and debunking extreme narratives about AI's impact on employment and society.
Speakers
Jensen Huang
Jensen Huang is the President, Founder, and CEO of NVIDIA, the technology company that has become synonymous with AI acceleration and computing. Under his leadership, NVIDIA has pioneered accelerated computing and become the world's leading provider of AI infrastructure, powering everything from chatbots to autonomous vehicles to digital biology research.
Sarah Guo
Sarah Guo is a venture capitalist and co-host of the No Priors podcast, focusing on AI and technology investments. She brings deep expertise in evaluating AI companies and understanding market dynamics in the rapidly evolving artificial intelligence landscape.
Elad Gil
Elad Gil is a technology investor, entrepreneur, and co-host of No Priors podcast. He has extensive experience in Silicon Valley, having worked with numerous high-growth technology companies and providing insights on AI strategy and market development.
Key Takeaways
Focus on Purpose Over Tasks When Evaluating AI Impact
Jensen Huang emphasized the critical distinction between the tasks people perform in their jobs versus the ultimate purpose of their work. (09:03) He illustrated this with radiologists, where AI now powers 100% of radiology applications, yet the number of radiologists has actually increased because their purpose—diagnosing disease and conducting research—has expanded, not diminished. This framework helps explain why productivity gains from AI typically lead to job growth rather than elimination, as professionals can focus on higher-value work while AI handles routine tasks.
Open Source AI Is Essential for American Innovation
Huang stressed that open source AI is not optional but essential for maintaining America's competitive edge across industries. (18:55) Without open source models, startups, universities, and established companies in manufacturing, healthcare, and other sectors would be "suffocated" in their AI development. He argued that whatever policies are implemented, they must not damage the open source innovation flywheel that enables diverse applications and prevents any single entity from controlling AI development.
AI Infrastructure Creates Massive Job Opportunities
The shift to AI is creating three entirely new types of industrial plants: chip manufacturing facilities, supercomputer plants, and AI inference factories. (06:53) This infrastructure buildout requires enormous numbers of construction workers, electricians, plumbers, technicians, and network engineers. Huang noted with excitement that electricians are seeing their paychecks double and traveling for business trips, highlighting how the AI revolution is creating high-paying jobs for skilled trades across America.
Costs Are Dropping Exponentially While Capability Increases
The cost of AI is decreasing at unprecedented rates—Huang estimates that building the equivalent of the first ChatGPT now costs tens of thousands of dollars versus the original billions, achievable on a weekend project. (30:54) With hardware improving 5-10x annually and compounding effects across the technology stack, he predicts token generation costs could drop by a billion times over ten years. This dramatic cost reduction opens new applications and keeps AI accessible to startups and smaller organizations.
Energy Growth Is Critical for AI Leadership
Huang credited President Trump's "drill, baby, drill" energy policy for preventing America from losing the AI industrial revolution to other countries. (54:06) Without adequate energy infrastructure, there can be no new industry growth, and the AI infrastructure boom has actually become the biggest driver of sustainable energy innovation as companies seek behind-the-meter power solutions, battery storage, and alternative energy sources to meet their massive computational demands.
Statistics & Facts
- Companies like OpenEvidence are achieving 90% gross margins on AI token generation, demonstrating that AI applications can be highly profitable. (02:25) This statistic shows the economic viability of AI applications in professional services.
- Jensen Huang's average elevation in 2025 was approximately 17,000 feet due to extensive international travel, highlighting the global nature of AI policy discussions. (03:23)
- NVIDIA's autonomous vehicle business is approaching $10 billion in revenue, with their self-driving car safety stack rated number one in the world. (67:48) This demonstrates AI's expansion beyond chatbots into physical applications.
