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1:05:22EN
Unsupervised Learning: With Jacob EffronPódcastBuild First, Optimize Later: Harrison Chase on LangChain, Evals, and the State-Machine Future of AgentsPresenta: Jacob EffronHarrison Chase explains how LangChain grew from an orchestration layer into LangSmith and LangGraph, why evaluation datasets force product clarity, and why reliable agents look more like state machines than autonomous loops.
56:20EN
No Priors: AI, Machine Learning, Tech, & StartupsPódcast · 2 vocesBiohub's Bet: Building Open AI World Models of Biology From Proteins Up to CellsPresenta: Sarah Guo, Elad GilMark Zuckerberg, Priscilla Chan and Alex Rives explain why Biohub pairs a frontier AI lab with frontier wet-lab biology, and why it releases tools like ESMFold2 as open source.
1:11:06ENUnsupervised Learning: With Jacob EffronPódcastReplit's Amjad Masad on Building Your Own Model, Latency, and the Next Billion Software CreatorsPresenta: Jacob EffronThe Replit founder explains why AI should be native to the product, why he trained a small in-house model, and why he thinks software engineering is about to split in two.
40:00ENUnsupervised Learning: With Jacob EffronPódcastThe Winds of Change: How Mistral Plans to Win the Open-Model EraPresenta: Jacob EffronArthur Mensch explains Mistral's open-source strategy, enterprise distribution, model research, and views on AI regulation and sovereignty.
1:12:15ENUnsupervised Learning: With Jacob EffronPódcastThe Open-Model Vibe Check: China, Containment, and the Data MoatPresenta: Jacob EffronJacob Effron and guests debate Chinese open-weight models, distillation, containment policy, the OpenAI–Hugging Face incident, and Cursor's data advantage.
1:03:25EN
Lex FridmanPódcastTheano in an Hour: Symbolic Graphs, Automatic Gradients and a Compiler That Rewrites Your MathPresenta: Lex FridmanPascal Lamblin of MILA walks through how Theano builds, differentiates, optimizes and runs computation graphs, then trains logistic regression, a convnet and an LSTM.
50:23ENUnsupervised Learning: With Jacob EffronPódcastOpenAI’s Platform Bet: Where AI Value Accrues, Why Open Source Trails, and When Superintelligence ArrivesPresenta: Jacob EffronPeter Welinder explains OpenAI’s platform strategy, the case for proprietary frontier models over open source, the enterprise hallucination problem, and his speculative timeline for AGI and superintelligence.
1:34:27EN
Lenny's PodcastPódcast · 2 vocesMatt Mullenweg on Open Source Ideals, the WP Engine Fight and Why Llama Isn't Really OpenInvitado: Matt Mullenweg · Presenta: Lenny RachitskyThe WordPress co-creator and Automattic CEO gives his side of the WP Engine dispute, explains his open source philosophy, and talks AI, community building and acquisitions with Lenny Rachitsky.
1:02:06ENLex FridmanPódcastLearning TensorFlow Hands-On: From a Mystery Line to Handwritten DigitsPresenta: Lex FridmanGoogle Brain's Sherry Moore walks a Deep Learning School audience through how TensorFlow works and two core labs, linear regression and MNIST digit recognition.
33:31ENNo Priors: AI, Machine Learning, Tech, & StartupsPódcast · 2 vocesOpen Source Catches Up, Regulation Can Wait: Sarah Guo and Elad Gil Answer Listener QuestionsPresenta: Sarah Guo, Elad GilTwo AI investors cover open-source models, autonomous agents, whether to regulate AI, where startups can win, and why healthcare innovation is so hard.
1:47:58ENLenny's PodcastPódcast · 3 vocesBridging the Divide: How Community Notes Built a Trusted Fact-Checking System on DisagreementInvitado: Keith Coleman, Jay Baxter · Presenta: Lenny RachitskyKeith Coleman and Jay Baxter, the team behind Community Notes, explain how the algorithm works, how a tiny team built it, and why it survived four leaders at Twitter and X.