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1:56:38ENo3 took ARC from 20% to 87%. Nathan Labenz sketches early superintelligenceAnime : Nathan LabenzOn Consistently Candid, the Cognitive Revolution host argues that math and coding will be superhuman by 2026, and that a reasoning core plus specialist “intuitive physics” may already be enough.
54:12ENJulian Teixeira on Hiring Sales Teams and Building a Repeatable ProcessInvité : Julian Teixeira · Anime : Harry StebbingsThe 1Password CRO discusses early hires, team goals, outbound prospecting, compensation and inspecting deals as a company scales.
12:30ENQwQ-32B: A Smaller Reasoning Model and Its TradeoffsMatthew Berman · Forward FutureMatthew Berman examines Qwen’s reinforcement-learning recipe, tests a coding task, and compares benchmark scores and hardware requirements with DeepSeek-R1.
12:10ENMercury Coder and Diffusion Language Models: Speed, Demos and LimitsMatthew Berman · Forward FutureMatthew Berman explores Inception’s 2025 coding model, comparing iterative text refinement with autoregressive generation and examining speed claims.
1:31:35ENThirty Years of Research, Collapsed into One SentenceAnime : Nathan LabenzImmunologist Derya Unutmaz on writing a medical patent in half an hour, treating o1 Pro as a professor-level collaborator, and why he no longer trusts his own expertise until he asks the model.
45:06ENMike Schroepfer: AI’s Bottleneck Is Electricity, and One Tanker of Fusion Fuel Could Power the U.S. for a YearAnime : Jacob EffronMeta’s former CTO tells Redpoint why hyperscaler demand is the climate story, why Llama was an access play, and why tomorrow’s CTO still lives or dies on a priority queue.
36:24ENThe Man Behind Humanity's Last Exam Says Superintelligence Strategy Should Copy NukesAnime : Sarah Guo, Elad GilDan Hendrycks tells No Priors that labs can only do basic anti-terror refusals, while the real risk-management problem is a geopolitical deterrent he calls mutually assured AI malfunction.
21:48ENVibe Coding With Cursor and Windsurf: Berman’s 2025 WorkflowMatthew Berman · Forward FutureMatthew Berman shares project rules, testing habits and version-control practices from early experiments with coding agents.
49:39ENAnton Osika on Lovable’s Launch, Early Retention and Building AI Products in EuropeInvité : Anton Osika · Anime : Harry StebbingsThe Lovable co-founder explains the transition from an open-source experiment to a fast-growing app builder, and discusses hiring, fundraising and the limits of early retention data.
1:04:52ENThe Consumer Playbook That Put Medical AI in 100,000 Exam RoomsOpenEvidence CEO Daniel Nadler explains how a free App Store product, trained only on peer-reviewed literature, reached as much as a quarter of U.S. physicians in a year.
1:02:41ENMike Krieger on AI Products, Model Competition and the Future of CodingInvité : Mike Krieger · Anime : Harry StebbingsAnthropic’s chief product officer explains how he thinks about product design, model differentiation and the limits of current AI tools.
3:22:47ZH肖弘:从 Monica 到 Manus,如何在技术变化中创业Invité : 肖弘 · Anime : 张小珺两次访谈记录肖弘的创业经历、AI 产品判断,以及 Manus 发布前对智能体的设想。
1:08:51ENChip Controls Are Meant to Buy Ten Years, Not Win the AI RaceAnime : Nathan LabenzEconomist Noah Smith tells Nathan Labenz that U.S. export controls are a piece of conventional deterrence against China — not a plan to kneecap DeepSeek.
19:32ENGPT-4.5’s Launch: Conversational Style, Benchmarks and CostMatthew Berman · Forward FutureMatthew Berman examines OpenAI’s February 2025 research preview, its selected demonstrations, reported evaluations and high launch pricing.
52:59ENGeorge Bonaci on Growth Experiments, Hiring and Finding New ChannelsInvité : George Bonaci · Anime : Harry StebbingsRamp’s growth leader discusses balancing speed with rigor, measuring results and building a team that can find opportunities beyond an existing playbook.
2:33:39ENThe Attacker Goes Second: Why Nicholas Carlini Keeps Breaking AI DefensesAnime : Nathan LabenzA Google DeepMind security researcher on simple loss functions, 70% robust accuracy, and why the fix has to live in the system, not the model.
40:33ENModerna was only company 18. The real product is the company factoryAnime : Sarah Guo, Elad GilNoubar Afeyan tells No Priors how Flagship Pioneering turned starting companies into a profession, underwrites scientific uncertainty, and wants AI to run discovery the way Waymo drives.
10:31ENGrok 3 and AI-Assisted Game Prototypes: A Tour of Creator DemosMatthew Berman · Forward FutureMatthew Berman explores browser games and generative art shared in February 2025, then recreates a simple 3D maze.
1:09:19ENOscar Pierre on Glovo’s Fight for Funding, Expansion and Sale to Delivery HeroInvité : Oscar Pierre · Anime : Harry StebbingsThe Glovo founder recounts a pivotal McDonald’s deal, repeated financing crises, a costly Brazil expansion and the decision to join Delivery Hero.
32:46ENDon't draw the flowchart: OpenAI's Deep Research team on training agents end to endIsa Fulford and Josh Tobin explain why Deep Research was trained with reinforcement learning on hard browsing tasks instead of a human-written graph of model calls.
7:59ENGrok 3’s Brief Misinformation Filter and the Question of AI BiasMatthew Berman · Forward FutureMatthew Berman examines an instruction that told Grok to disregard sources linking Elon Musk and Donald Trump to misinformation, and xAI’s explanation of how it reached users.
57:41ENA Hundred Million Cells, Four People, Three Days: Biology's ImageNet MomentAnime : Sarah Guo, Elad GilVevo Therapeutics and the Arc Institute open-sourced Tahoe-100M and a 230-million-cell atlas in the same week — and argued that virtual cells, not just protein folders, are the next language model of biology.
9:35ENClaude 3.7 Sonnet and Claude Code: An Early Coding TestMatthew Berman · Forward FutureMatthew Berman reviews Anthropic’s 2025 launch benchmarks and builds an AI-controlled Snake game, then tests math and recent information.
1:18:09ENSteeve Morin on AI Inference, Chips and the Cost of Switching HardwareInvité : Steeve Morin · Anime : Harry StebbingsThe ZML founder explains the difference between training and production inference and offers a competitive view of the AI hardware market.
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