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0:32ENFigure’s Humanoid Robots and Natural-Language InstructionsMatthew Berman · Forward FutureMatthew Berman comments on a 2025 Figure Robotics demonstration and the potential for household chores.
44:34ENThe Cheaper Intelligence Gets, the More of It We'll BuyHost Jacob EffronAmazon AGI Lab head David Luan on what DeepSeek actually meant, why next-token prediction is not enough, and why agents are still stuck on reliability.
0:51ENMira Murati Announces Thinking Machines LabMatthew Berman · Forward FutureMatthew Berman reviews the new AI lab’s stated goals in its February 2025 announcement.
1:00:09ENDeepSeek's Jailbreaks Don't Matter. Giving the Model Arms and Legs DoesPalo Alto Networks CEO Nikesh Arora tells Sequoia's Training Data why cheap brains scramble the AI order, why attackers already move faster than defenders, and why refusing to experiment is the real risk.
13:24ENGrok 3’s 2025 Launch: Benchmarks, Reasoning and DeepSearchMatthew Berman, Elon Musk · Forward FutureMatthew Berman reviews xAI’s launch charts, a historical user-preference leaderboard and an early product demonstration.
1:25:52ENJonathan Ross on Groq, Inference Economics and the AI Infrastructure RaceGuest Jonathan Ross · Host Harry StebbingsThe Groq CEO explains his bet on inference chips, compares his company’s architecture with GPUs, and discusses the financing and power needed to scale.
53:07ZH → EnglishZhang Yaqin on the AGI Roadmap: Information, Physical, and Biological IntelligenceGuest 张亚勤 · Host 张小珺Zhang Yaqin divides AGI’s development into information, physical, and biological intelligence. Information intelligence may approach human levels within five years, general-purpose robots may take about ten, and biological intelligence could expand human memory and health in twenty. He also discusses how large models can give autonomous vehicles and robots more data, common sense, and ability to act.
18:05ENOpenAI’s Coding-Competition Study: o1-ioi, o3 and the Limits of the ResultsMatthew Berman, Sam Altman · Forward FutureMatthew Berman interprets OpenAI’s 2025 paper on reinforcement learning and programming contests. The results are strong on the studied benchmarks, but do not establish AGI or remove humans from model development.
3:20:53ZH → EnglishHe Junxian Explains DeepSeek’s Papers: From Base Models to ReasoningGuest 何俊贤 · Host 张小珺Follow the research through MoE, attention caches, training efficiency and reinforcement learning.
45:31ENJerry Chow on Quantum Computing, Encryption, AI and Error CorrectionMatthew Berman, Jerry Chow · Forward FutureIBM’s quantum systems director explains qubits, cryogenic hardware, software and the work needed to make quantum computers useful.
1:29:02ENShe Never Sees a Row of Your Data. The Answers Still Clear 95%.Host Nathan LabenzIllumex CEO Inna Tokarev Sela tells Nathan Labenz how a Platonic industry ontology, trained only on metadata, collapses enterprise software into one conversation.
1:09ENUsing AI’s Benefits While Considering Its RisksA speaker distinguishes faster adoption from unchecked scaling.
1:07ENHow Interacting AI Agents Could Change the Wider SystemA speaker argues that simultaneous AI adoption could create unexpected interactions between agents.
8:04ENOpenAI’s February 2025 GPT-5 Roadmap and the Case for a Unified InterfaceMatthew Berman · Forward FutureMatthew Berman explains the proposed model-routing experience, GPT-4.5 and GPT-5 plans, and the product choices that prompted them.
1:20:53ENSolly Solomou on Building LADbible, Social Media and Expanding to the USGuest Solly Solomou · Host Harry StebbingsThe founder recounts buying a Facebook page, creating a media business and learning to lead through rapid change.
49:36EN86 Out of 100: Harvey's Playbook for Selling AI Into LawHost Sarah Guo, Elad GilWinston Weinberg on a Reddit blind test, expanding-and-collapsing product design, and why Harvey started with century-old firms instead of the mid-market.
44:26ENAn AI Application Is Still an ApplicationMongoDB's Sahir Azam tells Sequoia why vector search is a new primitive for unstructured data, not a replacement for transactions, and why retrieval quality is the last mile that gets AI into conservative enterprises.
15:33ENLatent Reasoning and Recurrent Depth: Scaling Compute Before the Next TokenMatthew Berman, Yann Lecun · Forward FutureMatthew Berman examines a 3.5-billion-parameter research model that repeats internal computations, and asks how it relates to language, planning and chain of thought.
0:59ENWhat Is Vibe Coding? Matthew Berman Explains His WorkflowMatthew Berman · Forward FutureBerman describes using voice input and an AI coding editor to build software, test it, and feed errors back without reading the code.
1:08ENWhen Should AI Agents Cooperate?Two participants consider mutual benefit, conflicting incentives and the line between cooperation and collusion.
1:15:33ENFabien Pinckaers on Odoo’s Business Model, Culture and CompetitionGuest Fabien Pinckaers · Host Harry StebbingsThe Odoo founder discusses open core, pricing, ownership and his approach to building an integrated business software suite.
1:30:28ENA Perfect Score Is 32,000 Units: Only Claude Built a Cooperative SocietyHost Nathan LabenzThe same donor game, run for ten generations, can bank 32,000 resource units if everyone cooperates—and three frontier models miss that ceiling by an order of magnitude.
6:50ENDeepScaleR: A Small Reasoning Model Tested on Competition MathMatthew Berman · Forward FutureMatthew Berman reviews a 1.5B model’s reported benchmark results and runs a quantized version locally on one AIME problem.
2:07ENHow Eratosthenes Estimated Earth’s SizeA short geometric explanation using sunlight, angles and distance.
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