The Perfect Summary Podcast

Australian comic James McCann on losing a job mid-move to Ohio, finding his feet in Austin, Australian gatekeeping, and AI worries.

Luis J. Gomez and Joe Rogan riff on outrage culture, independent platforms, AI, wealth, odd laws, lucid dreams and ibogaine.

David Cross and Joe Rogan revisit the Boston comedy boom, Mr. Show and NewsRadio, then worry about AI, kids online and war.

RZA talks his new film, Shaolin-style discipline, channeling anger into art, cobalt mining, quitting weed and why movies belong in theaters.

Criminal psychologist Julia Shaw on why nobody is born evil, what really drives murder, how false memories form, and green crime.

Norman Ohler on methamphetamine in the Wehrmacht, Hitler's opioid use, the Berlin resistance, and how LSD went from Sandoz to the CIA.

John Hopfield explains associative memory, why feedback and collective behavior matter, and what biology does that AI still ignores.

Simon Sinek tells Lex Fridman why life and business have no finish line, and why passion comes from purpose, not pressure.

Philosopher Nick Bostrom walks through the simulation argument step by step, then turns to the promise and risk of superintelligent AI.

Richard Dawkins on why evolution is wasteful yet brilliant, how memes spread, where morals come from, and why even a simulator needs explaining.

Filmmaker Alex Garland on truly alien aliens, Ava's smile in Ex Machina, Silicon Valley's veneer of virtue, and a universe without free will.

Howie Mandel tells Joe Rogan how a dare made him a comic, how he copes with OCD and depression, and why he embraces AI while Rogan worries.

John Wick director Chad Stahelski explains how the franchise was built, from stunts, dogs and gun work to editing, and what AI may mean for film.

Jitendra Malik explains why vision is hard, why self-driving is far off, and why AI should learn the way children do.

OpenAI's Ilya Sutskever explains why deep learning keeps exceeding expectations, what GPT-2 shows, and how AGI should be built and governed.

Stephen Wolfram explains why simple rules produce endless complexity, and how that idea drives his hunt for the rule behind physics.

Bioinformatics professor Dmitry Korkin explains how his lab modeled the new coronavirus's proteins and what that reveals for drugs and vaccines.

Joscha Bach tells Lex Fridman why the self is a story the brain tells itself, what consciousness is for, and why civilization may not last.

Steven Pressfield on war as a metaphor for the inner fight, where Resistance comes from, serving the muse, and the daily routine of a working writer.

Turing Award winner David Patterson on why simple instruction sets won, open RISC-V, Moore's law slowing, machine learning chips, RAID, and teaching.

Ben Goertzel on where the term AGI came from, his OpenCog design, decentralized AI, the truth about Sophia the robot, and why death is bad.

Marcus Hutter explains AIXI, his mathematical model of perfect intelligence, and why compression, understanding and prediction are one.

Brian Kernighan recalls how UNIX and C took shape at Bell Labs, why AWK endures, and how he sees programming languages, AI, and computing today.

Turing Award winner Richard Karp explains P vs NP, NP-completeness, randomized algorithms, and why he doubts machines will match human intelligence.

Berkeley's Sergey Levine explains why robot minds lag robot bodies, how reinforcement learning works, and what it will take for machines to keep improving.

Lex Fridman maps eight long-term futures for Neuralink, from easing suffering and telepathy to saved memories and merging with AI.

Daphne Koller on using stem cells and machine learning to find new drugs, lessons from Coursera, and why AI must know when it is unsure.

Michael Shellenberger unpacks the Twitter Files, government-backed censorship, COVID, AI, nuclear power and why he stays hopeful.

Minds founder Bill Ottman and Joe Rogan on decentralized social media, censorship laws, open source AI, Neuralink and UFOs.

Andrew Ng on the first MOOCs, betting on scale at Google Brain, learning deep learning, and bringing AI into factories.