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15:37ENMatthew Berman on Qwen3.8-Max, AI Costs and Open-Weight CompetitionMatthew Berman · Forward FutureA 2026 review of reported benchmark results and research demonstrations leads to questions about deployment economics and geopolitical dependence.
1:09:26ENAnastasios Angelopoulos on Arena, Open Models and AI EvaluationInvité : Anastasios Angelopoulos · Anime : Harry StebbingsArena’s CEO discusses real-world model comparisons, enterprise AI control, security and the economics of evaluation.
2:16:29ENFrom Two Papers a Month to Sixty: What Two Weeks in China Revealed About AI SafetyAnime : Nathan LabenzNathan Labenz argues that the familiar 'China will never slow down' line does not survive contact with the actual Chinese AI safety ecosystem.
1:05:02ENJoon Sung Park on Simulating Human Behavior and Building SimileInvité : Joon Sung Park · Anime : Harry StebbingsThe Simile co-founder explains his research on generative agents, the challenges of validating simulations, and his ambitions for a business built around modeling people.
34:30ENNetic's Agents Answer the Phone When the Heat BreaksAnime : Sarah Guo, Elad GilFounder Melisa Tokmak tells Elad Gil how a two-year-old platform became the AI operations layer for HVAC, roofing, pet care, and other essential services.
1:04:14ENThe Man Who Helped Stand Up Colossus in 120 Days Is Betting on an AI That Lives in Your HouseAnime : Jacob EffronxAI co-founder Igor Babuschkin left to start River AI, arguing coding agents have crossed a threshold, closed labs are getting squeezed, and the next prize is personal, local intelligence.
1:43:45ENA $300 Universal Jailbreak: Why FAR.AI Now Thinks Defense Can WinAnime : Nathan LabenzAdam Gleave walks through FAR.AI’s first head-to-head AI security leaderboard, and explains why a decade of offense-dominant thinking is starting to crack.
1:20:22EN20VC Roundtable on Open Weights, AI Spending and Software InvestingInvité : Jason Lemkin, Rory O’Driscoll · Anime : Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate AI safety, chip investment, enterprise budgets and the future of software.
49:12ENThe People Writing the Transformer’s Eulogy Want a Lab That Can Take Vacation Without Themo1’s reasoning lead and a Gemini pre-training lead argue the architecture, not more scale, is now the bottleneck — and that replacing it starts with automating kernel generation.
2:59:03ENYou Kaichao on How vLLM Grew from Open-Source Project to AI Infrastructure CompanyInvité : You Kaichao · Anime : 张小珺Inferact co-founder You Kaichao traces vLLM’s path from Berkeley research to a company, then explains why model, inference, hardware and agent design increasingly have to move together.
3:46:18ENIf You Take Slavery Out of the Picture, There Is No Civil WarInvité : Gary Gallagher · Anime : Lex FridmanIn 1860, enslaved people were worth more than every railroad and factory in the United States combined.
2:23:43ENHe Bought an Android, Two SIMs, and Left Claude Watching His InboxAnime : Nathan LabenzNathan Labenz asked a dozen friends how to visit China and got two irreconcilable answers.
1:06:45ENMatt Murphy on Anthropic, Open Models and the New Venture PlaybookInvité : Matt Murphy · Anime : Harry StebbingsThe Menlo Ventures partner explains his investments in Anthropic, Lovable and Legora, and debates AI margins, model competition and venture fund strategy.
1:02:42ENMercor’s Osvald Nitski on AI Training Data, Product and Customer ConcentrationInvité : Osvald Nitski · Anime : Harry StebbingsMercor’s head of product discusses how the company supplies expert data to AI labs, designs its marketplace and plans to reach more enterprise customers.
52:29ENClaude Opus 5: Benchmarks, Cost per Task, and Early ImpressionsMatthew Berman · Forward FutureMatthew Berman reacts to the model launch, examines reported benchmark and pricing data, and explains why the cost of completing a task matters more than token price alone.
49:20ENHalf of Ask DoorDash Orders Hit a New Restaurant. In Ten Years There Will Be More Dashers, Not Fewer.Anime : Sarah Guo, Elad GilCo-founders Andy Fang and Stanley Tang tell Sarah Guo how a conversational ordering interface moved DoorDash's hardest metric, why they built a 300-pound delivery robot in-house, and why autonomy means more human riders, not less.
1:27:39EN20VC Roundtable on Open Models, AI Economics and Payments DealsInvité : Jason Lemkin, Rory O’Driscoll · Anime : Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll discuss model security, inference investment and a reported PayPal proposal.
1:15ENUsing Codex to Negotiate a Return and Subscription RefundMatthew Berman · Forward FutureMatthew Berman describes delegating two customer-service conversations to an AI agent and reports the outcomes.
51:31ENThey Refunded Nearly $2 Million. Then Factory’s CEO Explained the Dark FactoryMatan Grinberg on being two years early, why a model-agnostic harness beats lab co-design, and why 90 percent of coding tokens will soon run with the lights off.
27:13ENKimi K3 and the Debate Over Open-Weight AIMatthew Berman · Forward FutureMatthew Berman examines model economics, competition and security arguments after Moonshot AI’s Kimi K3 announcement.
1:28:42ENLin Qiao on Specialized AI, Open Models and the Economics of InferenceInvité : Lin Qiao · Anime : Harry StebbingsThe Fireworks AI CEO explains her case for customized models, discusses infrastructure trade-offs and forecasts lower AI costs and higher use.
1:52ENAnthropic, Compute Capacity and the Competition for AI SubscribersMatthew Berman · Forward FutureMatthew Berman weighs a claimed compute constraint against model quality, subscription limits and the possibility of future self-improvement.
1:29:35ENFred Turner on Curative’s Pandemic Pivot, Health Insurance and AI AutomationInvité : Fred Turner · Anime : Harry StebbingsCurative’s CEO recounts building a COVID testing operation, moving into health insurance and using AI agents across the company’s workflows.
1:13:48ENCarriers Spend $200 Billion a Year. The Money Went Up the StackAnime : Jacob EffronBenedict Evans tells Jacob Effron why analogizing AI to past platforms is a dead end, and why looking at how those platforms actually made money is not.
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