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113 件
並び順
26:02EN
Lex Fridman· 2020年2月9日ポッドキャストMoore’s Law Is Not Dead—It Is a Cascade of S-Curvesホスト Lex FridmanJim Keller explains why transistor scaling keeps outrunning its obituary, and how exponential hardware changes the mathematics AI can attempt.インフラとデプロイSemiconductorsScaling Laws+3
1:13:51EN
Lex Fridman· 2020年1月19日ポッドキャストAnswering Questions Without Seeing the Data: Andrew Trask on the Privacy-Preserving AI Stackホスト Lex FridmanA tour of remote execution, differential privacy, secure multiparty computation, and the societal consequences of making private data usable.セキュリティと安全性Privacy & data governanceOpen-source ecosystems+3
46:25EN
Lex Fridman· 2019年1月17日ポッドキャストDeep Learning at the Edge of 2019: BERT, Autopilot, and the Ideas That Broke Throughホスト Lex FridmanA tour of the architectural, applied, and automation breakthroughs that defined deep learning in 2018 and set up 2019.モデルと学習Deep LearningAI research+3
1:00:38EN
Lex Fridman· 2017年12月6日ポッドキャストThe Race Car and the Rulebook: Chris Gerdes on Automated Vehicle Safetyホスト Lex FridmanA Stanford engineer and former DOT innovation chief explains how autonomous racing, voluntary safety guidance, and data sharing could shape safer self-driving cars.セキュリティと安全性Autonomous Driving安全性とガバナンス+3
1:29:03EN
Lex Fridman· 2016年9月27日ポッドキャストFrom Word Vectors to Memory Networks: The Building Blocks of Deep NLPホスト Lex FridmanRichard Socher explains how word embeddings, recurrent models, GRUs, pointer mixtures, and dynamic memory networks turn language tasks into trainable end-to-end systems.モデルと学習Deep Learning機械学習の基礎+2
1:00:51EN
Lex FridmanポッドキャストDeep Learning From the Ground Up: Hugo Larochelle's One-Hour Tour of Neural Network Foundationsホスト Lex FridmanA fast, equation-level walk through feed-forward networks, backpropagation, practical training tricks, dropout and batch normalization, from the 2016 Deep Learning School.モデルと学習Deep Learning機械学習の基礎+1
1:07:29EN
Lex FridmanポッドキャストDeep Reinforcement Learning from First Principles: Rewards, Q-Learning, Policy Gradients and AlphaZeroホスト Lex FridmanLex Fridman's MIT 6.S091 opening lecture walks from the basic RL framework through DQN, actor-critic methods and AlphaZero to the unsolved problem of moving from simulation to the real world.モデルと学習Reinforcement LearningDeep Learning+3
9:59EN
Lex FridmanポッドキャストIs Language or Vision Harder? Ilya Sutskever on the Unity of Machine Learningホスト Lex FridmanIn a short clip from his 2020 conversation with Lex Fridman, Ilya Sutskever explains why vision, language and reinforcement learning share the same few principles, and why asking which problem is harder is the wrong question.モデルと学習機械学習の基礎Deep Learning+3
19:24EN
Lex FridmanポッドキャストLex Fridman's 30-Day Challenge: 20,000 Push-ups and Pull-ups, With Advice From David Gogginsホスト Lex FridmanLex Fridman explains how a tweet became a month-long physical and mental test, and what David Goggins told him about suffering, injuries and habit.
21:41EN
Lex FridmanポッドキャストFrom Simulated Majorities to "You Are Probably Simulated": Bostrom on the Missing Step in the Simulation Argumentホスト Lex FridmanNick Bostrom explains to Lex Fridman why the simulation argument rests on a much weaker assumption than the Doomsday argument, and where its physical limits might lie.Simulation HypothesisPhilosophyExistential Risk
13:55EN
Lex FridmanポッドキャストResistance Is the Ego's Voice: Steven Pressfield on Fear, the Self and the Next Ideaホスト Lex FridmanSteven Pressfield explains where the force he calls Resistance comes from and why the real fight happens at the most mundane level.PhilosophyCreativityPsychology
54:58EN
Lex FridmanポッドキャストEric Weinstein on Geometric Unity: One Canvas, Fourteen Dimensions and a Theory of Everythingホスト Lex FridmanEric Weinstein talks with Lex Fridman about releasing his Oxford lecture, why academia resists his ideas, and how Geometric Unity tries to derive matter from the geometry of spacetime.Philosophy of ScienceMathematicsScience Communication
1:25:16EN
Lex FridmanポッドキャストFrom Hand-Built Features to ResNets: Andrej Karpathy's Crash Course in Convolutional Networksホスト Lex FridmanA 2016 Deep Learning School talk covering how convnets work, how the ImageNet winners evolved, and how to apply them without being a hero.モデルと学習Deep LearningComputer Vision+3
25:06EN
Lex FridmanポッドキャストLiving Inside the Brain's Story: Joscha Bach on Simulation, Self and Consciousnessホスト Lex FridmanIn a clip from his conversation with Lex Fridman, Joscha Bach argues that consciousness, identity and even God are software-like patterns, and that we exist inside a narrative our brain generates.PhilosophyPhilosophy of MindConsciousness & Intelligence+3
11:51EN
Lex FridmanポッドキャストBuilding a Brain: Paola Arlotta on the Choreography of Human Brain Developmentホスト Lex FridmanA Harvard stem cell biologist walks through how the embryo builds the cerebral cortex, why order and environment matter, and why development continues into our twenties.Neuroscience & AIComputational BiologyNeuroscience+1
1:24:43EN
Lex FridmanポッドキャストFrom Sparse Coding to GANs: A Tour of Unsupervised Deep Learning in 2016ホスト Lex FridmanRuslan Salakhutdinov walks through autoencoders, Boltzmann machines, variational autoencoders and adversarial networks at the Deep Learning School, with candid notes on what did and did not work.モデルと学習Deep Learning機械学習の基礎
58:46EN
Lex FridmanポッドキャストCaging the Neural Network: How Aptiv Thinks About Safe Self-Drivingホスト Lex FridmanAptiv Autonomous Mobility's Karl Iagnemma and Oscar Beijbom explain why end-to-end learning is hard to trust in cars, and show how PointPillars and nuScenes push lidar perception forward.モデルと学習Autonomous DrivingDeep Learning+3
14:49EN
Lex FridmanポッドキャストElon Musk Rates Memes and Ends Up Defending Nuclear Power, the British Museum and the Cheeseburgerホスト Lex FridmanIn a lighthearted excerpt from his conversation with Lex Fridman, Elon Musk scores a stack of printed memes on a one-to-eleven scale and gives serious answers whenever a joke touches a real topic.Science CommunicationHistory
1:15:59EN
Lex FridmanポッドキャストSteering Through Time: How Recurrent Networks and LSTMs Learn from Sequencesホスト Lex FridmanLex Fridman's MIT 6.S094 lecture walks from backpropagation basics to LSTMs and the way they are used to predict steering in self-driving cars.モデルと学習Deep Learning機械学習の基礎+2
23:37EN
Lex FridmanポッドキャストPave Your Own Path: Lex Fridman on Impostor Syndrome, Envy and Gratitudeホスト Lex FridmanIn an Ask Me Anything episode, Lex Fridman answers listeners' questions about self-doubt by arguing against comparison, for finding your own passion, and for pairing self-criticism with gratitude.Career GrowthPhilosophyPersonal Growth
29:54EN
Lex FridmanポッドキャストSeven Levels of a Pandemic: Pain, Challenge and Hope From Biology to Philosophyホスト Lex FridmanLex Fridman maps the coronavirus onto seven levels of attack on society and proposes a response and a reason for hope at each one.Public HealthExistential RiskPhilosophy+2
10:17EN
Lex FridmanポッドキャストWhy Great Robots Fail as Businesses, and What iRobot Got Rightホスト Lex FridmaniRobot co-founder Colin Angle explains why so many robotics companies collapse and how cost, vision and a clear user need shaped the Roomba.プロダクトと UXCompany BuildingProduct-Market Fit+3
18:46EN
Lex FridmanポッドキャストDeep Learning Plus One Idea: Ilya Sutskever on Building AGIホスト Lex FridmanIn a May 2020 conversation, Sutskever discusses self-play, simulation, bodies and consciousness, tests of intelligence, and how an AGI might be governed and aligned.モデルと学習AGI(汎用人工知能)Reinforcement Learning+3
22:59EN
Lex FridmanポッドキャストPenrose on Why Consciousness Can't Be a Computationホスト Lex FridmanRoger Penrose explains how a dissatisfaction with AI optimism, a tip about microtubules and a rethink of quantum mechanics led him to Orch OR.Philosophy of MindConsciousness & IntelligenceAI research+3
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