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113개
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26:02EN
Lex Fridman· 2020년 2월 9일팟캐스트Moore’s Law Is Not Dead—It Is a Cascade of S-Curves진행자 Lex FridmanJim Keller explains why transistor scaling keeps outrunning its obituary, and how exponential hardware changes the mathematics AI can attempt.인프라와 배포SemiconductorsScaling Laws+3
1:13:51EN
Lex Fridman· 2020년 1월 19일팟캐스트Answering Questions Without Seeing the Data: Andrew Trask on the Privacy-Preserving AI Stack진행자 Lex FridmanA tour of remote execution, differential privacy, secure multiparty computation, and the societal consequences of making private data usable.보안과 안전Privacy & data governanceOpen-source ecosystems+3
46:25EN
Lex Fridman· 2019년 1월 17일팟캐스트Deep Learning at the Edge of 2019: BERT, Autopilot, and the Ideas That Broke Through진행자 Lex FridmanA tour of the architectural, applied, and automation breakthroughs that defined deep learning in 2018 and set up 2019.모델과 학습Deep LearningAI research+3
1:00:38EN
Lex Fridman· 2017년 12월 6일팟캐스트The Race Car and the Rulebook: Chris Gerdes on Automated Vehicle Safety진행자 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.보안과 안전Autonomous Driving안전과 거버넌스+3
1:29:03EN
Lex Fridman· 2016년 9월 27일팟캐스트From Word Vectors to Memory Networks: The Building Blocks of Deep NLP진행자 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.모델과 학습Deep Learning머신러닝 기초+2
1:00:51EN
Lex Fridman팟캐스트Deep Learning From the Ground Up: Hugo Larochelle's One-Hour Tour of Neural Network Foundations진행자 Lex FridmanA fast, equation-level walk through feed-forward networks, backpropagation, practical training tricks, dropout and batch normalization, from the 2016 Deep Learning School.모델과 학습Deep Learning머신러닝 기초+1
1:07:29EN
Lex Fridman팟캐스트Deep Reinforcement Learning from First Principles: Rewards, Q-Learning, Policy Gradients and AlphaZero진행자 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.모델과 학습Reinforcement LearningDeep Learning+3
9:59EN
Lex Fridman팟캐스트Is Language or Vision Harder? Ilya Sutskever on the Unity of Machine Learning진행자 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.모델과 학습머신러닝 기초Deep Learning+3
19:24EN
Lex Fridman팟캐스트Lex Fridman's 30-Day Challenge: 20,000 Push-ups and Pull-ups, With Advice From David Goggins진행자 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 Fridman팟캐스트From Simulated Majorities to "You Are Probably Simulated": Bostrom on the Missing Step in the Simulation Argument진행자 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 Fridman팟캐스트Resistance Is the Ego's Voice: Steven Pressfield on Fear, the Self and the Next Idea진행자 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 Fridman팟캐스트Eric Weinstein on Geometric Unity: One Canvas, Fourteen Dimensions and a Theory of Everything진행자 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 Fridman팟캐스트From Hand-Built Features to ResNets: Andrej Karpathy's Crash Course in Convolutional Networks진행자 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.모델과 학습Deep LearningComputer Vision+3
25:06EN
Lex Fridman팟캐스트Living Inside the Brain's Story: Joscha Bach on Simulation, Self and Consciousness진행자 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 Fridman팟캐스트Building a Brain: Paola Arlotta on the Choreography of Human Brain Development진행자 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 Fridman팟캐스트From Sparse Coding to GANs: A Tour of Unsupervised Deep Learning in 2016진행자 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.모델과 학습Deep Learning머신러닝 기초
58:46EN
Lex Fridman팟캐스트Caging the Neural Network: How Aptiv Thinks About Safe Self-Driving진행자 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.모델과 학습Autonomous DrivingDeep Learning+3
14:49EN
Lex Fridman팟캐스트Elon Musk Rates Memes and Ends Up Defending Nuclear Power, the British Museum and the Cheeseburger진행자 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 Fridman팟캐스트Steering Through Time: How Recurrent Networks and LSTMs Learn from Sequences진행자 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.모델과 학습Deep Learning머신러닝 기초+2
23:37EN
Lex Fridman팟캐스트Pave Your Own Path: Lex Fridman on Impostor Syndrome, Envy and Gratitude진행자 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 Fridman팟캐스트Seven Levels of a Pandemic: Pain, Challenge and Hope From Biology to Philosophy진행자 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 Fridman팟캐스트Why Great Robots Fail as Businesses, and What iRobot Got Right진행자 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.제품과 UXCompany BuildingProduct-Market Fit+3
18:46EN
Lex Fridman팟캐스트Deep Learning Plus One Idea: Ilya Sutskever on Building AGI진행자 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.모델과 학습AGI(범용 인공지능)Reinforcement Learning+3
22:59EN
Lex Fridman팟캐스트Penrose on Why Consciousness Can't Be a Computation진행자 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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