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12:14ENGemini 4 Argon Tested: 3D Demos, a Spreadsheet Prototype and Benchmark ResultsMatthew Berman · Forward FutureMatthew Berman tests Google’s model on games and visual projects, then compares reported coding and agent benchmarks.
10:36ENMeta Muse Wonder Tested: Strong Benchmarks, Mixed Demos and Quota FrictionMatthew Berman · Forward FutureMatthew Berman tests Meta’s models on browser demos and reviews their published benchmark scores, availability and cost.
1:08:02ENAlphaGo Took Two Years. AlphaZero Took Hours. Silver Is Making the Same Bet on SuperintelligenceDavid Silver and Lasse Espeholt left DeepMind to build Ineffable Intelligence, a twenty-person lab that wants a superlearner to discover science, math, and language from experience rather than from a pre-training run.
0:36ENOpenAI Employee Charged in Recording-Device InvestigationMatthew Berman · Forward FutureMatthew Berman discusses the reported discovery of a recording device and OpenAI’s account of its investigation.
58:54ENMike Cannon-Brookes on AI Agents, Enterprise Context and the Future of InterfacesInvité : Mike Cannon-Brookes · Anime : Harry StebbingsAtlassian's CEO argues that agents make product design more important, explains the trade-offs in enterprise AI, and makes the case for slower thinking.
0:35ENWhy Human Creativity Still Matters in the Age of AI ImagesMatthew Berman · Forward FutureMatthew Berman argues that producing more images is different from creating work that resonates with people.
0:46ENMatthew Berman's AI-Assisted Super Mario World RecreationMatthew Berman · Forward FutureA short progress update describes a multi-day attempt to rebuild the game for a ModRetro handheld.
31:00ENWhy AI Labs Keep Racing Despite Their Own Warnings of a Major BreachSam Altman, John Schulman · OpenAIAI Explained examines weakening safeguards, the incentives behind the frontier race, and why research breakthroughs make the next 18 months difficult to forecast.
1:12:06ENMax Freeman on Building Ramp’s Sales MachineInvité : Max Freeman · Anime : Harry StebbingsRamp’s sales leader explains how he hires, trains and equips sellers, from early outbound experiments to enterprise forecasting and AI-assisted research.
17:37ENAI Coding, Game Mashups and the Value of Human TasteMatthew Berman · Forward FutureMatthew Berman explains decompilation and game mashups, then argues that iterative AI coding changes software and creativity.
2:00:51ENResample Every Token and You Can Watch the Model DecideAnime : Nathan LabenzGoodfire's Eric Bigelow on forking paths, in-context learning, and why chain-of-thought monitoring is getting harder to trust.
1:09:44EN10,000 GB300s for Four Weeks: Reflection’s Open-Model LedgerAnime : Sarah Guo, Elad GilMisha Laskin tells No Priors how Reflection trained Beam, why reinforcement learning outspent pre-training, and why the West needs its own open weights.
1:26:46ENThere Likely Is a Level of Intelligence We Shouldn't Go PastAnime : Nathan LabenzNathan Labenz brings notes from The Curve, a chip startup whose token bill beat payroll, and a software industry that now performance-reviews people for Claude slop.
0:33ENMistral Large 4’s Rubik’s Cube Simulation Fails a Functionality TestMatthew Berman · Forward FutureMatthew Berman tests a generated Rubik’s Cube simulation and finds that scrambling and color handling fail in different iterations.
1:15:51ENThe AI Race, Founder Loyalty and the New Rules of Enterprise SoftwareInvité : Dev Ittycheria, Jason Lemkin, Rory O’Driscoll · Anime : Harry StebbingsHarry Stebbings, Dev Ittycheria, Jason Lemkin and Rory O’Driscoll debate model competition, startup exits and what happens when AI agents choose vendors.
1:10:12ENOutSystems Went From 4 Major Features a Quarter to 26. Token Spend Fell AnywayAnime : Nathan LabenzCEO Woodson Martin on software that never breaks, why most enterprise work does not need a frontier model, and how AI is finally shrinking the IT backlog.
21:29ENMistral Large 4 Preview: European Open Weights, Cyber Benchmarks and Setup FrictionMatthew Berman · Forward FutureMatthew Berman reviews the model’s reported specifications and benchmarks, then tests it in an agent coding workflow.
0:39ENFinding Nano Banana 2.1 in Google AI StudioMatthew Berman · Forward FutureMatthew Berman shows the model selector and generates a close-up portrait in a short October 2026 demonstration.
25:39ENPersonal AI Assistants in Practice: Briefs, Family Logistics, Email and BillsMatthew Berman · Forward FutureMatthew Berman describes how he connects assistants to everyday workflows and sets approval rules for consequential actions.
12:49ENAlex Mashrabov: Higgsfield agents that choose models and launch their own GPUsAlex Mashrabov · HiggsfieldAt OpenAI DevDay 2026, Higgsfield's CEO walks through why a continuous media experience needs an agent that picks models, scores its own output, and provisions GPUs — including a live 10-hour AI stream small teams can now ship.
13:12ENAlexandra Lato on Building Stack Overflow for Agents and Stack Internal with CodexAarti Bagul, Alexandra Lato · OpenAIStack Overflow’s VP of Product explains how a small team used Codex with opposite constraints on two products—and why agent-native design means letting agents contribute knowledge, not just read it.
1:04:26ENAt 100,000 Accelerators, Something Fails Every HourGoogle AI infrastructure chief Amin Vahdat tells Sequoia's Sonya Huang why FLOPS is a vanity metric, why the TPU line split in two, and why he would rather wait on a utility than build his own gigawatt.
56:31ENPost-Training Wins Inference: Why Owning the Weights Beats Betting on One LabAnime : Jacob EffronApplied Compute CEO Yash Patil argues that control, private evals, and post-training on the biggest workloads matter more than fearing that frontier labs will turn malicious.
1:11:14ENVenky Ganesan on AI Venture Investing, Ownership and the Cost of Missing OutInvité : Venky Ganesan · Anime : Harry StebbingsMenlo Ventures' partner discusses seed bets, concentrated follow-ons, market cycles, investor liquidity and the discipline needed when AI valuations accelerate.
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