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5 diapositivas8:05EN
Matthew Berman· 29 mar 2023A 2023 Guide to Running the Original GPT4All Model LocallyMatthew Berman · Forward FutureMatthew Berman demonstrates an early CPU-based GPT4All release, its terminal installation and the resources available for fine-tuning.Open-weight modelsModelos y entrenamientoInfraestructura y despliegue
3 diapositivas6:50EN
Matthew Berman· 19 mar 2023Running LLaMA and Alpaca Locally: A 2023 Dalai TutorialMatthew Berman · Forward FutureMatthew Berman demonstrates an early local-model setup on a MacBook Air and explains the settings that control generation.Local inferenceModelos y entrenamientoAjuste fino+1
5 diapositivas7:55EN
Matthew Berman· 20 feb 2023How to Train a Custom Image Model in Leonardo.aiMatthew Berman · Forward FutureMatthew Berman walks through Leonardo.ai’s 2023 model galleries, training-set guidance, and custom model workflow, then shares results from several experiments.Generative mediaModelos y entrenamiento
8 diapositivas1:03:29ZH
跟李沐学AI· 12 ene 2023多模态论文串讲:BLIP、CoCa 与 BEiT-3从图文数据清理到统一预训练,梳理三种视觉语言模型的结构、目标函数与相互联系。Multimodal AIModelos y entrenamientoData quality & curation
6 diapositivas1:07:10ZH
跟李沐学AI· 29 dic 2022InstructGPT 论文精读:从人工反馈到语言模型对齐从监督微调、奖励模型到 PPO,梳理 InstructGPT 的训练流程、实验结果与局限。Reinforcement LearningModelos y entrenamiento
3:28:47EN
Lex Fridman· 29 oct 2022Pódcast · 2 vocesKarpathy Calls Trained Neural Nets Complicated Alien ArtifactsInvitado: Andrej Karpathy · Presenta: Lex FridmanOn Lex Fridman's podcast, Andrej Karpathy refuses the brain analogy, walks the Fermi paradox through Nick Lane's chemistry, and treats the Transformer as a general-purpose differentiable computer.Modelos y entrenamientoAGIAutonomous Driving+3
2:10:08EN
Lex Fridman· 26 jul 2022Pódcast · 2 vocesGato Is Only the BeginningInvitado: Oriol Vinyals · Presenta: Lex FridmanDeepMind's Oriol Vinyals talks with Lex Fridman about generalist agents, thrown-away weights, and whether human-level AGI arrives in his lifetime.Modelos y entrenamientoAGIAI research+3
2:10:39EN
Lex Fridman· 1 jul 2022Pódcast · 2 vocesDemis Hassabis: Solve Intelligence, Then Solve Everything ElseInvitado: Demis Hassabis · Presenta: Lex FridmanThe DeepMind CEO tells Lex Fridman why the Turing Test is the wrong exam, how AlphaFold rewrote biology, and why the quiet radio sky suggests we are probably alone.Modelos y entrenamientoAI researchAGI+3
2:45:10EN
Lex Fridman· 22 ene 2022Pódcast · 2 vocesA Teenager Learns to Drive in Twenty Hours. A Car Still Cannot.Invitado: Yann Lecun · Presenta: Lex FridmanYann LeCun tells Lex Fridman why self-supervised world models are the missing dark matter of intelligence, and why machines are not even at the level of a house cat.Modelos y entrenamientoWorld modelsComputer Vision+3
2:31:57EN
Lex Fridman· 20 sept 2021Pódcast · 2 vocesJay McClelland on How Thought Emerges From Neural NetworksInvitado: Jay McClelland · Presenta: Lex FridmanThe Stanford cognitive scientist talks with Lex Fridman about connectionism, backpropagation, David Rumelhart, and why intuition discovers what logic later proves.Modelos y entrenamientoFundamentos de MLDeep Learning+3
2:51:33EN
Lex Fridman· 29 ago 2021Pódcast · 2 vocesThe Self Is a GPT Prompt: Wojciech Zaremba on Consciousness, Codex, and Fermi's SilenceInvitado: Wojciech Zaremba · Presenta: Lex FridmanOpenAI co-founder Wojciech Zaremba tells Lex Fridman he thinks we might be alone in the universe — and that GPT-3, Codex, and a one-handed robot already hint at how intelligence is built.Modelos y entrenamientoAgentes de programaciónFundamentos de ML+3
2:18:29EN
Lex Fridman· 8 ago 2021Pódcast · 2 vocesYour Cortex Is 150,000 Brains Voting on a Coffee CupInvitado: Jeff Hawkins · Presenta: Lex FridmanJeff Hawkins tells Lex Fridman that intelligence is learning a model of the world, the neocortex is tens of thousands of independent maps that vote, and the fastest path to machine intelligence is reverse-engineering that sheet.Modelos y entrenamientoNeuroscience & AIFundamentos de ML+3
2:30:30EN
Lex Fridman· 31 jul 2021Pódcast · 2 vocesThe Fallacy of the Successful First StepInvitado: Ishan Misra · Presenta: Lex FridmanBerkeley's Jitendra Malik explains why computer vision still looks easy, why fully autonomous driving is not near, and what children know that today's networks do not.Modelos y entrenamientoComputer VisionMultimodal AI+3
1:56:17EN
Lex Fridman· 19 abr 2021Pódcast · 2 vocesIf You Reran Earth a Million Times, Would Anything Like Us Appear?Invitado: Risto Miikkulainen · Presenta: Lex FridmanRisto Miikkulainen on neuroevolution, hyena raids, basil that never sleeps, and why variation-plus-selection still finds solutions backpropagation cannot see.Modelos y entrenamientoFundamentos de MLAI research+3
2:01:07EN
Lex Fridman· 12 dic 2020Pódcast · 2 vocesMichael Littman isn’t waiting for a runaway god. He’s watching us.Invitado: Michael Littman · Presenta: Lex FridmanThe Brown reinforcement-learning researcher tells Lex Fridman why accidental superintelligence feels like a 747 assembling itself — and why social media, rote language, and theory of mind worry him more.Modelos y entrenamientoReinforcement LearningAGI+3
2:10:06EN
Lex Fridman· 14 ago 2020Pódcast · 2 vocesYou Might Have to Understand the World to Understand the Letter AInvitado: Dileep George · Presenta: 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.Modelos y entrenamientoNeuroscience & AIWorld models+3
1:41:37EN
Lex Fridman· 21 jul 2020Pódcast · 2 vocesThe Fallacy of the Successful First Step: Jitendra Malik on Why Seeing Still Isn't SolvedInvitado: Jitendra Malik · Presenta: 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.Modelos y entrenamientoVisión y vídeoAutonomous Driving+3
1:37:31EN
Lex Fridman· 14 jul 2020Pódcast · 2 vocesThe Robot That Brought the Beer Was Being TeleoperatedInvitado: Sergey Levine · Presenta: 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.Modelos y entrenamientoRoboticsReinforcement Learning+3
2:00:32EN
Lex Fridman· 3 jul 2020Pódcast · 2 vocesSlow Synapses Grow Fast Learners — Warmth Is the Harder ProblemInvitado: Matt Botvinick · Presenta: 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.Modelos y entrenamientoNeuroscience & AIReinforcement Learning+3
3:00:18EN
Lex Fridman· 13 jun 2020Pódcast · 2 vocesOnly a Simulation Can Be ConsciousInvitado: Joscha Bach · Presenta: Lex FridmanJoscha Bach tells Lex Fridman why a neuron cannot feel anything, why existence is the default, and why this dying world is still the best level of the game.Modelos y entrenamientoConsciousness & IntelligencePhilosophy of Mind+3
1:37:28EN
Lex Fridman· 8 may 2020Pódcast · 2 vocesWe Are Still Massively Underestimating Deep LearningInvitado: Ilya Sutskever · Presenta: Lex FridmanIlya Sutskever tells Lex Fridman why 2012 was about conviction, why bigger models can get worse before they get better, and what he would do with an AGI.Modelos y entrenamientoDeep LearningFundamentos de ML+3
1:48:01EN
Lex Fridman· 3 abr 2020Pódcast · 2 vocesDavid Silver: AlphaGo Won by Taking Human Knowledge OutInvitado: David Silver · Presenta: Lex FridmanThe DeepMind researcher behind AlphaGo and AlphaZero tells Lex Fridman how an unclaimed million-dollar Go prize, a BBC Micro at age seven, and a honeymoon insight led to superhuman self-play.Modelos y entrenamientoReinforcement LearningDeep Learning+3
1:12:48EN
Lex Fridman· 29 feb 2020Pódcast · 2 vocesJohn Hopfield's Physics of Mind: Glitches Become FeaturesInvitado: John Hopfield · Presenta: Lex FridmanThe Princeton physicist walks Lex Fridman from a wobbly London bridge to Hopfield networks, consciousness-as-story, and why his famous model still does not explain learning.Modelos y entrenamientoNeuroscience & AIFundamentos de ML+3
1:44:55EN
Lex Fridman· 14 feb 2020Pódcast · 2 vocesIf You Need 60,000 Digits, You Have Not Found IntelligenceInvitado: Vladimir Vapnik · Presenta: Lex FridmanVladimir Vapnik tells Lex Fridman that intelligence is the art of shrinking a sea of functions with a few good predicates — and that MNIST, solved with sixty examples per class, is the test.Modelos y entrenamientoFundamentos de MLAI research+3
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