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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 profitability of inference tokens. He also talks about why AI will increase productivity without necessarily taking away jobs, and how physical AI and robotics can help to solve labor shortages. Finally, Jensen shares his 2026 outlook, including why he’s optimistic about US-China relations, why open source remains essential for keeping the US competitive, and which sectors are due for their “ChatGPT moment.” Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @nvidia Chapters: 00:00 – Jensen Huang Introduction 00:17 – Biggest AI Surprises of 2025 04:12 – AI and Jobs: New Infrastructure and Demand for Skilled Labor 09:03 – Task vs. Purpose Framework in Labor 12:31 – Solving Labor Shortages with Robotics 15:14 – The Layer Cake of AI Technology 18:39 – The Importance of Open Source 21:52 – The Myth of “God AI” and Monolithic Models 23:54 – Addressing the “Doomer” Narrative and Regulation 29:25 – The Plummeting Cost of Compute and Tokenomics 35:09 – The Return to Research 37:49 – Future of Coding and Software Engineering 43:20 – The Industries Due For Their “ChatGPT” Moments 46:00 – The Evolution of Self-Driving Cars and Robotics 54:06 – Energy Demand and Growth for AI 58:49 – 2026 Outlook: US-China Relations and Geopolitics 1:04:43 – Is There An AI Bubble? 1:16:20 – Conclusion

Elad GilhostJensen HuangguestSarah Guohost
Jan 7, 20261h 16mWatch on YouTube ↗

At a glance

WHAT IT’S REALLY ABOUT

Jensen Huang argues AI’s next wave is grounded, embodied, diverse

  1. Huang frames 2025 as a year of major practical improvements—better grounding, reasoning, and “routers” that trigger research—reducing hallucinations and making enterprise tokens economically valuable.
  2. He argues AI is not just software but new infrastructure that requires “AI factories,” creating demand for skilled labor (construction, electricians, technicians) while shifting work from tasks to higher-level job purposes.
  3. He strongly defends open source as essential for startups, legacy industries, and research, rejecting the idea of a single “God AI” or monolithic model that makes vertical apps obsolete.
  4. Looking ahead, he predicts “ChatGPT moments” in digital biology (protein/chemical generation), rapid robotics progress via end-to-end + reasoning models, and sustained growth constrained primarily by energy and capacity rather than demand; he also calls for nuanced US–China policy and rejects the “AI bubble” framing as overly chatbot-centric.

IDEAS WORTH REMEMBERING

5 ideas

Grounding and reasoning shifted AI from impressive demos to trusted tools.

Huang highlights industry-wide advances that reduce hallucinations: stronger grounding, better reasoning, tighter integration with search, and “routers” that decide when to do additional research based on confidence.

AI is becoming infrastructure, and infrastructure creates broad-based jobs.

Because AI generates tokens anew each use, it needs continual compute—driving buildouts of chip fabs, supercomputer manufacturing, and data-center-scale “AI factories,” which pull in construction and skilled trades at scale.

Productivity gains change what work is, not whether work exists.

Using radiology as the example, he argues AI automates tasks (reading scans) while expanding the purpose (better diagnosis, more patients, more research), which can increase headcount rather than reduce it.

Robotics is positioned to scale faster than self-driving did.

He describes four eras of autonomy (sensors → modular stacks → end-to-end → end-to-end + reasoning) and claims robotics benefits from lessons learned and modern foundation-model techniques, reducing the “10–15 year slog.”

Open source is a prerequisite for most real-world AI verticalization.

Closed frontier models can coexist with open models, but Huang argues that without open source, startups, higher education, and century-old industrial firms would be “suffocated” because they need adaptable pretrained foundations.

WORDS WORTH SAVING

5 quotes

AI is software… but it’s not prerecorded software.

— Jensen Huang

A job has tasks and has purpose… the task is to study scans, but the purpose is to diagnose disease.

— Jensen Huang

I guess someday we will have God AI… that someday is probably on biblical scales… galactic scales.

— Jensen Huang

DeepSeek… [was] probably the single greatest contribution to American AI last year.

— Jensen Huang

Without energy, there can be no new industry.

— Jensen Huang

Reasoning + grounding improvements; research-triggering routersToken economics and profitable inferenceAI as infrastructure: chip plants, supercomputer plants, AI factoriesJobs impact: purpose vs task framework; labor shortagesRobotics and self-driving: end-to-end + reasoning eraAI technology “layer cake”: energy → chips → infrastructure → models → applicationsOpen source importance; China’s open models and knowledge spilloversDoomer narratives, regulation, and concerns about regulatory captureCompute cost curves: hardware + algorithms + architectures (MoE, SSM)Energy constraints and demand-driven climate/energy innovation2026 outlook: US–China coupling and export controlsRefuting the “AI bubble” narrative beyond chatbots

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