Dwarkesh Patel

What Dwarkesh Patel Says About Artificial Intelligence

18 episodes about artificial intelligence

Deeply researched interviews

Key Insights on Artificial Intelligence

AI democratization hinges on whether five big companies control systems or if new architectures enable broader access and competition

  • Ken Griffin reversed from AI skeptic to believer, reporting 15-25% productivity boosts at Citadel using AI for high-skilled finance work previously requiring weeks
  • Microsoft AI CEO predicts 18 months for all white-collar work automation, while Anthropic's CEO forecasts 10% overall and 50% entry-level unemployment
  • College graduates are booing AI mentions at commencement speeches, reflecting anxiety about job displacement from technology whose architects promise career destruction
  • Meta laid off 8,000 employees (10% of staff) while installing screen tracking software allegedly for AI training, creating 'new lows' in company morale
  • The AI doom cycle progresses through skepticism, AI psychosis, doom desperation, real-world recalibration, and finally enlightened anxiety
  • Economist Alex Emos's What Will Be Scarce explores how human-centric 'relational sectors' may grow as AI automates other work categories
  • SpaceX's IPO debut soared 20%, making Elon Musk a trillionaire and signaling massive investor appetite for AI-related companies

Episodes

The data black hole at the center of AI

The data black hole at the center of AI

Eric Jang – Building AlphaGo from scratch

Eric Jang – Building AlphaGo from scratch

Reiner Pope – The math behind how LLMs are trained and served

Reiner Pope – The math behind how LLMs are trained and served

Jensen Huang – TPU competition, why we should sell chips to China, & Nvidia’s supply chain moat

Jensen Huang – TPU competition, why we should sell chips to China, & Nvidia’s supply chain moat

Michael Nielsen – How science actually progresses

Michael Nielsen – How science actually progresses

Terence Tao – Kepler, Newton, and the true nature of mathematical discovery

Terence Tao – Kepler, Newton, and the true nature of mathematical discovery

Dylan Patel β€” Deep dive on the 3 big bottlenecks to scaling AI compute

Dylan Patel β€” Deep dive on the 3 big bottlenecks to scaling AI compute

I’m glad the Anthropic fight is happening now

I’m glad the Anthropic fight is happening now

Dario Amodei β€” "We are near the end of the exponential"

Dario Amodei β€” "We are near the end of the exponential"

Elon Musk – "In 36 months, the cheapest place to put AI will be space”

Elon Musk – "In 36 months, the cheapest place to put AI will be space”

An audio version of my blog post, Thoughts on AI progress (Dec 2025)

An audio version of my blog post, Thoughts on AI progress (Dec 2025)

Ilya Sutskever – We're moving from the age of scaling to the age of research

Ilya Sutskever – We're moving from the age of scaling to the age of research

Satya Nadella β€” How Microsoft is preparing for AGI

Satya Nadella β€” How Microsoft is preparing for AGI

Richard Sutton – Father of RL thinks LLMs are a dead end

Richard Sutton – Father of RL thinks LLMs are a dead end

β€œI find it almost disturbing that the universe favors life this strongly” – Nick Lane

β€œI find it almost disturbing that the universe favors life this strongly” – Nick Lane

Andrej Karpathy β€” β€œWe’re summoning ghosts, not building animals”

Andrej Karpathy β€” β€œWe’re summoning ghosts, not building animals”

Andrej Karpathy β€” AGI is still a decade away

Andrej Karpathy β€” AGI is still a decade away

Some thoughts on the Sutton interview

Some thoughts on the Sutton interview

Books on artificial intelligence

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