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52:10EN
Matthew Berman· 3 jun 2023James Briggs on Vector Databases, Retrieval and AI MemoryMatthew Berman, James Briggs · Forward FuturePinecone’s developer advocacy manager explains embeddings and external knowledge, recounts the surge after ChatGPT and AutoGPT, and considers long context windows.
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No Priors: AI, Machine Learning, Tech, & Startups· 4 may 2023Pódcast · 2 vocesUse Retrieval for a Wi-Fi Password. Use Experts for a Company's Private Language.Presenta: Sarah Guo, Elad GilGoogle Brain's Kelvin Guu on REALM, FLAN, model surgery, and why personalizing large models is still an unsolved interface problem.
1:56:16EN
Cognitive Revolution "How AI Changes Everything"· 6 abr 2023PódcastThey Used Humans as Stand-In AIs. Now 250,000 People Run Elicit.Presenta: Nathan LabenzOught's founders tell Nathan Labenz why open-ended reasoning has to be decomposed, supervised, and grounded—not scaled until it merely looks persuasive.
5:08ENMatthew Berman· 3 abr 2023Chatting with a PDF in Colab Using LangChain and a Vector IndexMatthew Berman · Forward FutureMatthew Berman demonstrates a 2023 PDF question-answering notebook; its retrieval workflow does not fine-tune model weights and its revenue example is incorrect.
35:36ENNo Priors: AI, Machine Learning, Tech, & Startups· 16 mar 2023Pódcast · 2 vocesFeatured snippets stalled at 7%. A Google veteran used language models to hit 70%Presenta: Sarah Guo, Elad GilNeeva founder Sridhar Ramaswamy tells No Priors why answers always beat links, why privacy never sold the switch, and why most queries do not need the biggest model.
1:44:19ENCognitive Revolution "How AI Changes Everything"· 14 mar 2023PódcastTen People Versus Google’s $282 Billion Search MachinePresenta: Nathan LabenzPerplexity founder Aravind Srinivas tells Nathan Labenz why citations, speed, and value per minute — not chat bubbles — are how a tiny team competes with Google.
1:26:20ENCognitive Revolution "How AI Changes Everything"· 2 mar 2023PódcastForty Dollars to Index Joe Rogan: Chroma, Shovels, and the Wright Flyer Era of MLPresenta: Nathan LabenzChroma co-founder Anton Troynikov on embeddings as the storage layer for language-model apps, Stable Attribution, and why machine learning is still flying on intuition.
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Lex Fridman· 11 oct 2019Pódcast · 2 vocesWatson Won Jeopardy Without Understanding. Ferrucci Wants AI That Can Explain ItselfInvitado: David Ferrucci · Presenta: Lex FridmanLex Fridman talks with David Ferrucci about IBM Watson, why prediction is not understanding, and why high-stakes decisions need machines that can reason with us.
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Lenny's PodcastPódcast · 2 vocesStop Chasing AI News: Chip Huyen on What Actually Makes AI Products BetterInvitado: Chip Huyen · Presenta: Lenny RachitskyAuthor of AI Engineering walks through pre-training, post-training, RL, evals and RAG, then explains what separates companies that get value from AI from those that stall.
1:11:56ENLenny's PodcastPódcast · 2 vocesHow to Get ChatGPT to Recommend Your Product: A Practical Guide to Answer Engine OptimizationInvitado: Ethan Smith · Presenta: Lenny RachitskyGraphite CEO Ethan Smith explains how AEO differs from SEO, which levers move the needle, and how to measure and test what works.
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Unsupervised Learning: With Jacob EffronPódcastDo the Dumb Thing First: A CTO's Playbook for Building an AI Coding AssistantPresenta: Jacob EffronSourcegraph CTO Beyang Liu on which AI coding features actually earn daily use, how new models get shipped and evaluated, and why retrieval is still a search problem.
23:54ENNo Priors: AI, Machine Learning, Tech, & StartupsPódcast · 2 vocesBeyond GPT-7: The Customization Toolkit, Meta's Open Source Bet and the Return of Consumer AIPresenta: Sarah Guo, Elad GilIn a host-only episode, the No Priors hosts map the six levers for 10x to 100x better AI, explain fine-tuning, RAG and AI feedback, and ask why consumer social is suddenly interesting again.
57:25ENUnsupervised Learning: With Jacob EffronPódcastFrom RAG to Reasoning: Why the Future of AI Is a System, Not a ModelPresenta: Jacob EffronDouwe Kiela explains what OpenAI's o1 reveals about test-time compute, why enterprise AI must be specialized, and where post-training and evaluations are heading.
51:55ENUnsupervised Learning: With Jacob EffronPódcastThe Search Engine Under AI Apps: Why Bigger Context Windows Aren't EnoughPresenta: Jacob EffronTurbopuffer CEO Simon on object-storage databases, vector-search trade-offs, and the AI features that will become SaaS table stakes.
46:48ENUnsupervised Learning: With Jacob EffronPódcastSnowflake's AI Stack: Small Models, the Text-to-SQL Iceberg, and Why Governance Comes FirstPresenta: Jacob EffronSnowflake head of AI Baris Gekken explains how Arctic and Cortex were built, where enterprise AI actually works today, and why precision, governance and evaluation matter more than raw model capability.
1:06:22ENUnsupervised Learning: With Jacob EffronPódcastPerplexity's Bet: Search Becomes Answers, and Answers Become a BusinessPresenta: Jacob EffronThe Perplexity CEO explains how a consumer AI search product is built, sequenced, and defended against Google.
32:41ENLex FridmanPódcast · 2 vocesHow IBM Watson Won Jeopardy: A Moonshot Built on Engineering, Not a BreakthroughInvitado: David Ferrucci · Presenta: Lex FridmanDavid Ferrucci tells Lex Fridman how he talked IBM into the Jeopardy challenge and how his team built Watson's search, scoring and confidence machinery in about four years.
1:01:13ENUnsupervised Learning: With Jacob EffronPódcastPinecone's Vector Database Bet: Scaling Through the ChatGPT TsunamiPresenta: Jacob EffronEdo Liberty explains how Pinecone scaled through the generative AI boom, why vector search is more than a database add-on, and where he sees the next AI infrastructure shifts.