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AI Engineer今日硅谷101昨日PragerU一昨日Y Combinator一昨日SemiAnalysis3 日前a16z3 日前GOTO Conferences3 日前Latent Space4 日前Dwarkesh Patel4 日前Adrian Twarog5 日前

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15 件
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トピック検索拡張生成（RAG）長さ30 分以上人数2 人
44:49EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年9月5日ポッドキャスト · 2 人How OpenEvidence Became the Clinical OS for 40% of U.S. Doctorsホスト Sarah Guo, Elad GilFounder Daniel Nadler tells No Priors how a free search tool for physicians, not an answer engine for patients, took high-stakes clinical knowledge in 18 months.RAG とナレッジ検索拡張生成（RAG）Search & retrieval+3
44:16EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年11月21日ポッドキャスト · 2 人Cohere's Aidan Gomez: The Model Curve Is Flattening, and $20 Million Now Buys GPT-4ホスト Sarah Guo, Elad GilThe Attention Is All You Need co-author tells No Priors why enterprises should stop waiting for the next model and start putting today's models into production.企業と戦略エンタープライズ AIAI Strategy+3
38:28EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年10月8日ポッドキャスト · 2 人Half of Production AI Is RAG. Fine-Tuning Almost Disappeared.ホスト Sarah Guo, Elad GilBraintrust CEO Ankur Goyal tells No Priors what Notion, Zapier, and Vercel actually ship — and which hyped techniques they quietly dropped.評価とオブザーバビリティ評価（Evals）検索拡張生成（RAG）+3
3:02:16EN
Lex Fridman· 2024年6月19日ポッドキャスト · 2 人The journey begins after the answer: Perplexity CEO Aravind Srinivas on search and curiosityゲスト Aravind Srinivas · ホスト Lex FridmanIn 2022, Perplexity's first hire asked about health insurance — and four PhDs could not get a clear answer from Google.RAG とナレッジProduct StrategyAI interface design+3
36:20EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年6月6日ポッドキャスト · 2 人A Hundred Million Tokens in Context Would Cost $10 Million. Tengyu Ma Runs the RAG Mathホスト Sarah Guo, Elad GilThe Stanford professor and Voyage AI founder argues that retrieval, not a giant context window, is how enterprises should manage private knowledge.RAG とナレッジ検索拡張生成（RAG）Embeddings+3
42:14EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年3月7日ポッドキャスト · 2 人Meta’s $197 Billion Day Was a Partial Answer to AI’s $200 Billion Questionホスト Sarah Guo, Elad GilSarah Guo and Elad Gil walk through Gemini, Mistral, NVIDIA’s upgrade cycle, Klarna’s support bot, and why the real AI spend still sits with the hyperscalers.企業と戦略AI Strategyエンタープライズ AI+3
31:28EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年2月22日ポッドキャスト · 2 人Bolt Memory onto GPT-4 and Cut Hallucinations by up to 50%ホスト Sarah Guo, Elad GilPinecone CEO Edo Liberty tells Sarah Guo and Elad Gil how RAG, serverless vectors, and keeping knowledge outside the model make LLMs more reliable.RAG とナレッジ検索拡張生成（RAG）Vector search+3
42:07EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年2月15日ポッドキャスト · 2 人Notion’s Ivan Zhao: RAG Will Make Organizing Optionalホスト Sarah Guo, Elad GilThe Notion CEO tells No Priors why he bet the company on GPT-4, why embeddings matter as much as agents, and why software is entering a bundling cycle.RAG とナレッジ検索拡張生成（RAG）Embeddings+3
46:36EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年1月18日ポッドキャスト · 2 人After a decade of code search, Sourcegraph’s CTO says the coding-AI fight is outside the modelホスト Sarah Guo, Elad GilBeyang Liu on Cody, why keyword search still does most of RAG, and why CS fundamentals get more valuable as AI compresses the middleware.コーディングエージェント検索拡張生成（RAG）コンテキストエンジニアリング+3
37:18EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年5月4日ポッドキャスト · 2 人Use Retrieval for a Wi-Fi Password. Use Experts for a Company's Private Language.ホスト Sarah Guo, Elad GilGoogle Brain's Kelvin Guu on REALM, FLAN, model surgery, and why personalizing large models is still an unsolved interface problem.RAG とナレッジ検索拡張生成（RAG）ファインチューニング+3
35:36EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年3月16日ポッドキャスト · 2 人Featured snippets stalled at 7%. A Google veteran used language models to hit 70%ホスト 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.RAG とナレッジ検索拡張生成（RAG）Search & retrieval+3
2:24:31EN
Lex Fridman· 2019年10月11日ポッドキャスト · 2 人Watson Won Jeopardy Without Understanding. Ferrucci Wants AI That Can Explain Itselfゲスト David Ferrucci · ホスト 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.RAG とナレッジ検索拡張生成（RAG）AI research+3
1:22:36EN
Lenny's Podcastポッドキャスト · 2 人Stop Chasing AI News: Chip Huyen on What Actually Makes AI Products Betterゲスト Chip Huyen · ホスト 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.プロダクトと UXファインチューニング検索拡張生成（RAG）+3
1:11:56EN
Lenny's Podcastポッドキャスト · 2 人How to Get ChatGPT to Recommend Your Product: A Practical Guide to Answer Engine Optimizationゲスト Ethan Smith · ホスト Lenny RachitskyGraphite CEO Ethan Smith explains how AEO differs from SEO, which levers move the needle, and how to measure and test what works.企業と戦略AI in sales & marketingGo-to-Market+3
32:41EN
Lex Fridmanポッドキャスト · 2 人How IBM Watson Won Jeopardy: A Moonshot Built on Engineering, Not a Breakthroughゲスト David Ferrucci · ホスト 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.モデルと学習AI HistorySearch & retrieval+1