The Perfect Summary Podcast
Every summary, narrated: the GIST of great conversations and books in minutes, so you can decide if you want the REST.
FiltersArtificial IntelligenceCreativityLongevityParentingPhilosophySleepClear
Pick as many as you like: any of them matches within a group.
RZA talks his new film, Shaolin-style discipline, channeling anger into art, cobalt mining, quitting weed and why movies belong in theaters.
Fertility doctor Natalie Crawford on AMH testing, egg freezing myths, lifestyle and supplements, and what harms eggs and sperm.
Social scientist Kasley Killam explains why adult friendship feels hard, which reasons for cancelling are excuses, and small ways to reconnect.
Criminal psychologist Julia Shaw on why nobody is born evil, what really drives murder, how false memories form, and green crime.
Snowboarder Chloe Kim on competing with a dislocating shoulder, her father's all-in bet, therapy, a new ADHD diagnosis and self-worth.
Marc Brackett explains what emotion regulation really is, why no emotion is bad, and tools like the Meta-Moment and precise labeling.
Norman Ohler on methamphetamine in the Wehrmacht, Hitler's opioid use, the Berlin resistance, and how LSD went from Sandoz to the CIA.
Stanford epigenetics researcher Dr. Lucia Aronica explains which foods signal your genes and the kitchen tricks that unlock them.
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.
MIT's Robert Langer on early rejection, starving tumors of blood, engineered tissue, patents, biotech startups, and why his students are his proudest work.
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.
Ms. Pat tells Joe Rogan how she turned a brutal childhood into a hit sitcom, a tour and a family, with plenty of jokes along the way.
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.