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2:08:26ENSatisfying Lectures Don't Stick: Grant Sanderson on Feynman, Fear, and Hitting Publish게스트 Grant Sanderson · 진행자 Lex FridmanThe 3Blue1Brown creator talks with Lex Fridman about why the nicest explanations can fail, why he envies Bell Labs, and why the experts most qualified to teach are the ones least willing to post.
2:56:24ENIt Is Knowing We Will Die That Makes Us Human게스트 Sheldon Solomon · 진행자 Lex FridmanSheldon Solomon tells Lex Fridman how death anxiety, from an eight-year-old's stamp collection to 28-millisecond lab primes, quietly runs politics, religion, and everyday life.
1:41:35ENThe Smallest Lights: Sara Seager on Finding Life Beyond the Sun게스트 Sara Seager · 진행자 Lex FridmanThe MIT planetary scientist talks with Lex Fridman about exoplanets, biosignature gases, a flower-shaped starshade, and the grief that sent her looking for another Earth.
2:10:06ENYou Might Have to Understand the World to Understand the Letter A게스트 Dileep George · 진행자 Lex FridmanDileep George on recursive cortical networks, why a five-year-old can read any new CAPTCHA, and what the Wright brothers actually learned from birds.
2:48:46ENLet Physics Walk: Russ Tedrake on Underactuated Robots, Contact, and Barefoot Commutes게스트 Russ Tedrake · 진행자 Lex FridmanMIT’s Russ Tedrake talks with Lex Fridman about gravity-powered walkers, a dead trout that swims upstream, why contact still breaks classical control, and what the DARPA Robotics Challenge taught him about testing.
2:29:24ENWe Are the Descendants of the First Digital Computer게스트 Manolis Kellis · 진행자 Lex FridmanMIT computational biologist Manolis Kellis tells Lex Fridman why life is digital, why any two humans are 99.9 percent identical, and what evolutionary signatures reveal inside SARS-CoV-2.
1:34:10ENAll-In E6: Antitrust, Startup Acquisitions and Platform Speech진행자 Jason Calacanis, Chamath Palihapitiya, David Sacks, David FriedbergA July 2020 debate on Big Tech hearings, marketplace power and the presidential election.
2:01:15ENNobody Died from the Fukushima Reactors게스트 Ian Hutchinson · 진행자 Lex FridmanMIT plasma physicist Ian Hutchinson on fusion, a hundredfold carbon cut, scientism, and why faith is more than believing unproven claims.
2:07:32ENRichard Karp: Either All These Problems Are Easy, or None of Them Are게스트 Richard Karp · 진행자 Lex FridmanThe Turing Award winner walks Lex Fridman from a geometry proof that stopped him at 13 through NP-completeness, randomized algorithms, and why no program yet outthinks a six-month-old.
11:41ENFive Ways to Calculate the Wait for a Successful ShotSawyer · Jane StreetA 20% success rate leads to an expected wait of five attempts—but two consecutive successes take 30. Explore the reasoning through series, recursion and a long-run argument.
1:41:37ENThe Fallacy of the Successful First Step: Jitendra Malik on Why Seeing Still Isn't Solved게스트 Jitendra Malik · 진행자 Lex FridmanBerkeley's Jitendra Malik tells Lex Fridman why computer vision keeps underestimating itself, why full self-driving still needs cognition, and why vision is the parent of language.
3:40ENBrian Kernighan on JavaScript and Software Dependencies게스트 Brian Kernighan · 진행자 Lex FridmanA 2020 conversation about language evolution and package complexity.
1:43:10ENKen Thompson's Wife Left for Three Weeks. He Wrote Unix.게스트 Brian Kernighan · 진행자 Lex FridmanBrian Kernighan walks Lex Fridman through Bell Labs, C, AWK, AMPL, and a lifetime of tools that millions of people still run — including all of his mistakes.
10:32ENReal Numbers: Expected Time Between Exams and a Half-Court Shot ChallengeSawyer · Jane StreetSawyer solves an exam-scheduling problem in several ways, then asks how many basketball attempts it takes to make one shot or two in a row.
1:37:31ENThe Robot That Brought the Beer Was Being Teleoperated게스트 Sergey Levine · 진행자 Lex FridmanSergey Levine tells Lex Fridman why hardware is almost closed, why common sense has to be lived, and why offline reinforcement learning is the missing on-ramp from logs to robots that keep getting better.
6:04ENFinals Week and the Expected Number of Snowboards UsedSawyer · Jane StreetSawyer poses a new exam-scheduling puzzle and uses indicator variables in two ways to solve the previous snowboard problem.
6:16ENIndicator Variables: Marching Bands and SnowboardsSawyer · Jane StreetSawyer uses linearity of expectation to count in-step rows, then poses a six-snowboard challenge.
1:09:14ENSuffering Is a State You'd Rather Not Be In — Peter Singer on Animals, Robots, and Us게스트 Peter Singer · 진행자 Lex FridmanOn Lex Fridman's podcast, the Princeton bioethicist defines suffering, extends it from factory farms to possible machine minds, and still puts extreme poverty first.
9:40ENReal Numbers: A Marching Band Challenge, Expected Damage, and Bayes’ RuleSawyer · Jane StreetSawyer introduces a marching-band expected-value puzzle and uses linearity and Bayesian updating to solve a monster-attack problem.
10:08ENExpected Damage and a Golden-Ratio Window PuzzleSawyer · Jane StreetSawyer introduces expected value with an unknown video-game monster, then uses geometry to solve a painting-through-a-window problem.
2:00:32ENSlow Synapses Grow Fast Learners — Warmth Is the Harder Problem게스트 Matt Botvinick · 진행자 Lex FridmanDeepMind neuroscience director Matt Botvinick tells Lex Fridman how prefrontal cortex, meta-reinforcement learning, and dopamine research meet the human question of what a better life with AI would actually look like.
45:31ENYou Are Your Own Existence Proof: Karl Friston on Free Energy, Life, and Self-Awareness진행자 Lex FridmanKarl Friston explains how the free energy principle reframes existence, life, planning, and self-awareness as inference problems.
7:55ENThe Art Thief’s Window and a Toy Boat’s Return JourneySawyer · Jane StreetSawyer poses a geometric window puzzle and solves the previous episode’s river-crossing problem in two ways.
1:02:14ENThe 28-year wait: Robert Langer on rejection, polymers, and a thousand students게스트 Robert Langer · 진행자 Lex FridmanThe MIT bioengineer talks with Lex Fridman about drug delivery, tissue engineering, patents, and the long path from a Folkman hypothesis to Avastin.
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