Audio · 2026-01-08 · 1h 16m · 6 moments

NVIDIA’s Jensen Huang on Reasoning Models, Robotics, and Refuting the “AI Bubble” Narrative

Even if ChatGPT never existed, the tech giant NVIDIA would still be winning. The end of Moore’s Law—says NVIDIA President, Founder, and CEO Jensen Huang—makes the shift to accelerated computing inevitable, regardless of any talk of an AI “bubble.” Sarah Guo and Elad Gil are joined by Jensen Huang for a wide-ranging discussion on the state of artificial intelligence as we begin 2026. Jensen reflects on the biggest surprises of 2025, including the rapid improvements in reasoning, as well as the pr ✦ AI generated

Apple Podcasts ↗

GUEST Jensen Huang HOST Sarah Guo HOST Elad Gil

timeline · colored by role

Claim

The entire AI industry addressed the biggest skeptical response — hallucination — through reasoning and grounding, and the improvements across language, vision, robotics, and self-driving cars were big leaps.

Jensen praises the industry's 2025 progress in grounding and reasoning, which addressed the hallucination problem and made AI more trustworthy across fields.

transcript

Jensen Huang: I think the whole industry addressed one of the biggest skeptical responses of AI, which is hallucination and generating gibberish and all of that stuff. I thought that this year, the whole industry, everything from every field, from language to vision to robotics to self-driving cars, the application of reasoning and the grounding of the answers, big, big leaps, would you guys say, this year?

explains mechanism · 1

Data◆

Token generation — especially reasoning tokens — is growing at multiple exponentials simultaneously, and these tokens are now profitable, proving their value.

Jensen is surprised by the explosive growth of reasoning token generation and notes that companies like OpenEvidence, Cursor, Claude, and OpenAI are achieving strong margins, proving the tokens are valuable.

transcript

Jensen Huang: probably a little bit surprised, in fact, that token generation rate for inference, especially reasoning tokens, are growing so fast, several exponentials at the same times, it seems. And I'm so pleased that these tokens are now profitable. that people are generating, I heard somebody, heard today that OpenEvidence, speaking of them, 90% gross margins. I mean, those are very profitable tokens. And so they're obviously doing very profitable or very valuable work. Cursor, their margins are great. Claude's margins are great. For the enterprise use of OpenAI, their margins are great. So anyways, it's really terrific to see that we're now generating tokens. that are sufficiently good, so good in value that people are willing to pay good money for.

explains mechanism · 1supports · 1

Mechanism◆

AI will not eliminate jobs because it automates tasks, not the purpose of a job — when the task is automated, the professional can fulfill more of the purpose, which increases demand and hiring.

Jensen argues that AI replaces tasks, not job purposes, using the example of radiologists: Hinton predicted they'd be obsolete, yet their numbers rose because AI let them study more scans, diagnose more diseases, and do more research — creating more demand for their services.

transcript

Jensen Huang: A job has tasks and has purpose. And in the case of a radiologist, the task is to study scans, but the purpose is to diagnose disease... the fact that they're able to study more scans more deeply, they're able to request more scans, do a better job diagnosing disease, the hospital's more productive, they can have more patients, which allows them to make more money, which allows them to want to hire more radiologists. And so the question is, what is the purpose of the job versus what is the task that you do in your job?

explains mechanism · 1gives example · 1provides context · 1rebuts · 1supports · 5

Prediction

Robotics and AI will address the severe and worsening labor shortage, not destroy jobs — and a billion robots would create the largest repair industry on the planet.

Jensen argues that the economy is limited by labor shortages in factory work, trucking, and other sectors. Robots will fill those gaps, and just as cars created a mechanic industry, a billion robots would create an enormous repair industry.

transcript

Jensen Huang: We don't have enough factory workers. Our economy is actually limited by the number of factory workers we have... We also know that the number of truck drivers in the world is severely short. And the reason for that is people don't want those jobs... So I think the first part is that having robotic systems is going to allow us to cover the labor shortage gap, which is really, really severe and getting worse because of aging population... just imagine we have a billion robots. It's going to be the largest repair industry on the planet.

extends · 1rebuts · 1supports · 2

Claim

Open source AI is essential for startups, traditional industries, higher education, and research — damaging it with policy would break the innovation flywheel.

Jensen argues that while frontier labs may choose closed models, open source is vital for startups, industrial companies, and healthcare — without it, most organizations would be 'suffocated' and unable to adapt AI to their domains. He warns policymakers not to damage the open source innovation flywheel.

transcript

Jensen Huang: Without open source, as you know, startups would be challenged. Companies that are in different industries, whether it's manufacturing or transportation or... healthcare. Without open source today, all of that AI work would be suffocated... Open source without open source, higher ed. Education research startups. I mean, the list goes on. And so we talk all day long about the tip, the most visible part of that... But underneath that is such an important space of open source AI. And whatever we decide to do with policies, do not damage that innovation flywheel.

Claim

The idea of 'God AI' arriving soon is unhelpful and not grounded in reality — it won't arrive next week or next year, and the whole world needs to advance practically in the meantime.

Jensen dismisses the 'God AI' narrative as not practically useful, arguing that no company or researcher is close to building an AI that masters all domains — language, genomics, proteins, physics — and that the world needs to move forward with practical AI now rather than waiting for a hypothetical monolithic superintelligence.

transcript

Jensen Huang: I think it's not helpful to go from where we are today to God AI. And I don't think any company practically believes they're anywhere near God AI. And nor do I see any researchers having any reasonable ability to create God AI... the ability to understand human language and genome language and molecular language and protein language and amino acid language and physics language, all supremely well. That God, AI just doesn't exist. And yet we have a lot of industries that need AI... God AI is not showing up next week. I'm fairly certain of that. Okay, that's great. And God AI is not going to show up next year, but the whole world needs to move forward next week, next year, next decade.

Highlight slides

Reasoning Token Growth Is Accelerating✦ from: Token generation — especially reasoning tokens — is growing at multiple exponentials simultaneously, and these tokens are now profitable, proving their value.Reasoning Tokens Now Profitable✦ from: Token generation — especially reasoning tokens — is growing at multiple exponentials simultaneously, and these tokens are now profitable, proving their value.AI automates tasks, not job purposes✦ from: AI will not eliminate jobs because it automates tasks, not the purpose of a job — when the task is automated, the professional can fulfill more of the purpose, which increases demand and hiring.Automation paradox — more radiologists, not fewer✦ from: AI will not eliminate jobs because it automates tasks, not the purpose of a job — when the task is automated, the professional can fulfill more of the purpose, which increases demand and hiring.Why demand rises after task automation✦ from: AI will not eliminate jobs because it automates tasks, not the purpose of a job — when the task is automated, the professional can fulfill more of the purpose, which increases demand and hiring.

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