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32:48ENFourteen People, $200 Million of Compute, and the Reliability Bottleneck for Agents진행자 Sarah Guo, Elad GilImbue co-founders Kanjun Qiu and Josh Albrecht on why agents fail, why language models cannot learn general algorithms, and why they are spending a giant round on GPUs rather than headcount.
1:32:32ENDes Traynor on AI Products, Competition and Building Intercom게스트 Des Traynor · 진행자 Harry StebbingsThe Intercom co-founder discusses customer-service automation, model dependence, product differentiation and leadership in a changing market.
1:21:50ENA 16K Context Window Holds About 350 Rows. That's Why Tables Need an Agent.진행자 Nathan LabenzGretel AI founder Alex Watson tells Nathan Labenz why most company data is still a spreadsheet, why GPT-4 is the wrong tool for generating it, and how differential privacy lets a model learn a disease without learning a patient.
1:03:08ENRyan Petersen on Flexport, Velocity and the Cost of Moving Too Fast게스트 Ryan Petersen · 진행자 Harry StebbingsThe Flexport founder discusses customer feedback, overhiring, cross-functional logistics and why direction matters as much as speed.
2:53ENJoey Zwillinger on the Founding of Allbirds게스트 Joey Zwillinger · 진행자 Harry StebbingsThe co-founder recounts the combination of footwear design and materials experience.
57:34ENChris Degnan on Building Snowflake's Sales Team from the First Customer게스트 Chris Degnan · 진행자 Harry StebbingsSnowflake's revenue chief explains prospecting, customer feedback, forecasting and his unconventional view of customer success.
13:43ENPrivateGPT 2.0: A 2023 Guide to Local Document Chat and Its RoadmapMatthew Berman, Iván Martínez · Forward FutureMatthew Berman demonstrates the 2023 PrivateGPT local setup, document ingestion and API, then speaks with project creator Iván Martínez about privacy and planned features.
2:16:46ENPhysics is the law. Everything else is a recommendation게스트 Elon Musk · 진행자 Lex FridmanOn his fourth Lex Fridman podcast, Elon Musk runs first-principles math on Gaza, Ukraine, Grok, aliens, and the coming shortage of useful compute per watt.
32:57ENA 7-billion-parameter model on a MacBook: Mistral's CEO reruns the cost of AI진행자 Sarah Guo, Elad GilArthur Mensch tells No Priors why Chinchilla made small models valuable, why open-sourcing Mistral 7B is not a bioweapon risk, and why guardrails belong on the application.
1:36:39ENOpenAI’s $5 Million Bet: A 60-Person Team Wants GPT-4V to Give Cars Common Sense진행자 Nathan LabenzGhost Autonomy cofounder John Hayes tells Cognitive Revolution why a multimodal model on the driving path could reset self-driving after two decades of DARPA-era stacks.
1:03:48ENDanny Cohen on Investing in Attention, Talent and Storytelling게스트 Danny Cohen · 진행자 Harry StebbingsThe former BBC television director explains how Access Entertainment invests across media, why discovery is harder, and what creative leaders can learn from managing talent.
1:14:48ENDevDay Probably Created Thousands of Startups, Says OpenAI's Logan Kilpatrick진행자 Nathan LabenzThe day after OpenAI's first developer conference, Dev Relations lead Logan Kilpatrick tells Nathan Labenz why thin wrappers were never companies, why agents were deliberately not shipped fully autonomous, and what $2 million custom models are for.
11:05ENTesting Dolphin 2.2, a Mistral 7B Fine-TuneMatthew Berman · Forward FutureMatthew Berman tries a small open-weight model on coding, formatting and reasoning prompts, with mixed results.
17:43ENOpenAI DevDay 2023: GPT-4 Turbo, Custom GPTs and Developer ToolsMatthew Berman, Sam Altman, Satya Nadella · Forward FutureMatthew Berman reviews OpenAI’s 2023 announcements, from longer context and cheaper API calls to custom GPTs and their implications for developers.
52:14ENJoey Zwillinger on Allbirds’ Market Decline and Turnaround Plan게스트 Joey Zwillinger · 진행자 Harry StebbingsThe Allbirds co-founder discusses the company’s 2023 share-price decline, inventory and distribution changes, and its goals for profitability.
1:03:46ENWhen Code Costs a Dime, You Throw the App Away진행자 Nathan LabenzLindy founder Flo Crivello tells Nathan Labenz how an AI employee learns APIs from documentation, why GPT-4 made quality the only metric that matters, and why even he wants aviation-style rules for AI.
57:16ENJack Altman, Auren Hoffman and Jason Lemkin Debate Founder-Led Venture Funds게스트 Jack Altman, Auren Hoffman, Jason Lemkin · 진행자 Harry StebbingsThe operators and investors discuss founder advice, limited-partner obligations, time trade-offs and whether their model can scale.
41:58ENReliability is the bottleneck. Autonomy is what would make AI feel alive.진행자 Sarah Guo, Elad GilIlya Sutskever talks with Sarah Guo and Elad Gil about AlexNet, OpenAI’s capped-profit bet, why smaller models mainly lose reliability, and the line he draws for digital life.
16:14ENAGI Timelines and AI Safety Commitments: The 2023 DebateA historical comparison of forecasts, the Bletchley summit and research on model behavior.
1:16:06ENDavid Meyer on Product Management, Customer Curiosity and Building Teams게스트 David Meyer · 진행자 Harry StebbingsThe Databricks product leader explains why product work is a balancing act, how to test assumptions with customers, and what he looks for when hiring.
1:32:40ENThe Historian Who Taught GPT-3.5 to Beat GPT-4진행자 Nathan LabenzMark Humphries on a kilometer of unread paper, fur-trade jargon that embeddings cannot see, and why cheap processing will force history to be rewritten.
5:31ENConnecting MemGPT to AutoGen AgentsMatthew Berman · Forward FutureIn a 2023 tutorial, Matthew Berman configures a MemGPT-backed coding agent alongside an AutoGen product manager and runs a short group chat.
1:16:45ENNick Tomaino on Crypto Investing, FTX and the NFT Debate게스트 Nick Tomaino · 진행자 Harry StebbingsThe 1confirmation founder discusses fund discipline, token incentives, OpenSea and the limits of conviction in a 2023 conversation.
17:11ENNext.js 14 in Context: Server Actions and Partial PrerenderingTheo Browne · Ping LabsTheo explains the 2023 release and its rendering tradeoffs.
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