The Perfect Summary Podcast

Matt Damon and Ben Affleck talk to Joe Rogan about The Rip, how streaming is reshaping movies, paying crews fairly, AI, forgiveness and greatness.

Author Pamela McCorduck recalls AI's founders, its roots in ancient myth, why she rejects the AI winter story, and what drew her to the field.

Neuroscientist Christof Koch explains what consciousness is, how to measure it, and how VR, meditation and psychedelics can widen our view of reality.

Jeremy Howard on fast.ai's mission, transfer learning, training fast on one GPU, programming languages, bootstrapped startups and learning.

Neuroscientist Christof Koch explains what consciousness is, how to measure it, and how VR, meditation and psychedelics can widen our view of reality.

iRobot's Colin Angle on why Roomba worked, cheap cameras over lasers, privacy in the home, and robots as partners rather than automatons.

Dr. David Fajgenbaum explains how approved drugs can treat other diseases, and how one saved his own life after five near-fatal relapses.

Neuroscientist Poppy Crum explains how technology reshapes the brain, how to use AI to learn instead of offloading, and what digital twins can do.

Andrew Huberman explains the brain's threat reflex and why undoing fear means detailed re-exposure followed by a new, positive association.

Keras creator François Chollet on why intelligence won't explode, what deep learning can't do, and the real risks of recommendation algorithms.

Skiing champion Mikaela Shiffrin explains why thinking about winning makes her lose, and how she learned to race through anxiety.

Neuroscientist David Berson tours the brain from retina to cortex: color vision, the body clock, balance, motion sickness and plasticity.

Andrew Huberman explains how the lymphatic system clears fluid and waste, and how movement, breathing, side sleeping and cardio keep it flowing.

Greg Fitzsimmons and Joe Rogan riff on censorship, the moon landing, AI's dark side, an Alaskan prank and what makes a comedy scene thrive.

Time researcher Laura Vanderkam shares nine tested rules, from a set bedtime to Friday planning, for finding free time in a busy week.

MIT's Regina Barzilay on how cancer changed her research, why medical AI is held back by data and adoption, and machine learning for drugs.

Yann LeCun explains why deep learning works, why human intelligence is not general, and why self-supervised world models are the next step for AI.

Mel Robbins shares five small steps, from a brain dump to claiming one win, for getting back on track within a day.

Peter Norvig on rewriting the standard AI textbook, fairness trade-offs, trust in machines, online learning, Lisp, Python and early Google search.

Leonard Susskind on intuition in physics, what quantum computers are for, what string theory achieved and why time has a direction.

Stanford lecturer Matt Abrahams shares drills and frameworks for clear, confident speaking, from stage fright to small talk.

Gary Marcus argues deep learning lacks common sense and abstraction, and that trustworthy AI needs a hybrid with symbolic reasoning.

Physicist Michio Kaku speculates on alien contact, string theory, brain-linked internet, immortality and settling Mars.

Garry Kasparov on what drove him at the board, what Deep Blue really proved, how humans should work with AI, and life as a Putin critic.

Eckhart Tolle on why suffering comes from the mind's story, how to befriend the present moment, and manifesting from fullness, not lack.

Evan Hafer and Joe Rogan talk archery, coffee, courage, Rogan's path from taekwondo to comedy, and their worries about AI.

Michael Malice and Joe Rogan on online hysteria, AI risks, New York's mayor, assisted dying, immigration, lifting and starting stand-up.

Simon Sinek on why posting pain online is not vulnerability, how to measure a good day, co-created boundaries, AI fear and inequality.

The creator of C++ explains its roots in Simula, the zero-overhead principle, concepts, the standards process and his doubts about fuzzy AI.

Watson lead David Ferrucci explains how the Jeopardy system worked and why real machine understanding needs shared human frameworks.