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17:56ENHow Bridgewater Keeps Its AI Analyst Inside Permission BoundariesNikhil Benesch, Aaron Linsky · turbopufferAaron Linsky and Nikhil Benesch explain why search over an enterprise vault must honor document permissions without sacrificing recall or speed. Their solution combines vector indexing with native filtering to search hundreds of millions of vectors in roughly 120 milliseconds.
35:19ENSallyAnn DeLucia: How to Write Your First AI EvalSallyAnn DeLucia · Arize AITurn an agent’s real traces into concrete pass/fail criteria, then build an LLM judge you can test, align with people, and run in production.
0:26ENSam Altman on Human Values and Problem-Solving in an AI WorldSam Altman · OpenAIIn a short interview excerpt, Altman considers the enjoyment of solving hard problems and the human role in interpreting results.
20:58ENVinoo Ganesh on Making Financial AI Cite Every NumberVinoo Ganesh · KeplerKepler CEO Vinoo Ganesh explains why financial AI should retrieve and cite figures while deterministic software handles the math. His design makes traceability, retrieval quality, and tenant security part of the answer itself.
18:31ENJanie Gu and Suyeol Yun: Why Frontier Models Fail as Buy-Side AnalystsJanie Gu, Suyeol Yun · Google DeepMindJanie Gu explains why benchmark scores can mislead, while Suyeol Yun presents MandateBench, which tests whether a model can turn a fund mandate into a defensible investment memo. The two talks show why real workflows, reproducible grading, and evidence-backed reasoning matter.
0:36ENKimi K3.1 and a Rubik’s Cube Solver DemonstrationMatthew Berman · Forward FutureMatthew Berman shows a scrambled virtual cube being solved and gives the Kimi K3.1 test a favorable assessment.
15:27ENWhat AI Engineers Do Now: Build the Loop Around AgentsAparna Dhinakaran · Arize AIAparna Dhinakaran argues that AI engineers are moving from shipping individual features to building systems that let agent teams improve them. At Arize, that means tracing agent behavior, evaluating its work against human judgment, and feeding those signals back into an always-on agent.
19:37ENJay Sahnan and Arik Bird on Building Financial Agents for the Whole WebJay Sahnan, Arik Bird · BrowserbaseBrowserbase’s Jay Sahnan and Arik Bird show how browser agents reach financial data hidden behind logins and bot defenses. Their Ramp, Bill, and Stripe examples connect reliable cloud browsers with Stagehand’s more adaptive controls.
1:08ENElon Musk Proposes Competitor Review Before AI Model ReleasesGast: Elon Musk · Moderation: Walter IsaacsonA short exchange with Walter Isaacson about safety coordination.
1:25:47ENRob Snyder’s PULL Framework for Finding Early DemandGast: Rob Snyder · Moderation: Lenny RachitskyA practical conversation about customer urgency, alternatives, early sales and retention.
19:24ENBuilding an Agent Regression Loop from Production TracesSofia Jakovcevic · Arize AISofia Jakovcevic demonstrates how to compare agent changes across safety, task completion and other dimensions before deployment.
1:50:48ENWhy Inference Matters 12× More Than TrainingFrançois Chaubard, Dan Fu, Jeff Morgan, Joe Fioti, Liangsheng Yin · Y CombinatorYC Paper Club walks the inference stack from an API request down to GPU kernels. Four talks from Together AI, Ollama, Luminal, and SGLang argue that serving quality, not just training FLOPs, is where most of the compute and the money now sit.
27:09ENLaurie Voss on the Product Engineer After AI Coding AgentsLaurie Voss · Arize AIAs code generation accelerates, Voss argues that review, operations and defining user needs become successive constraints—and that junior training must change.
0:21ENAn AI-Generated Kimi Benchmark Chart Used Invented ScoresMatthew Berman · Forward FutureMatthew Berman asks for a graph of Kimi K3.1 Pro benchmarks, then discovers that the displayed figures are illustrative placeholders.
1:28:36ENAI’s Pace: Interpretability, GPU Credit and the Physical Supply ChainGast: Zvi Mowshowitz, Evan Conrad, Lonis Hamaili · Moderation: Nathan Labenz, Prakash NarayananA weekly highlights episode weighs uncertain AI research trajectories against finance, infrastructure, security and regulation.
21:52ENJosef Witt-Doerring on Gen Z Mental Health, Isolation, and Psychiatric PrescribingShabbos Kestenbaum, Josef Witt-Doerring, Scott Galloway · PragerUOn The Brief, Shabbos Kestenbaum and psychiatrist Josef Witt-Doerring discuss why young adults are struggling, how prescribing incentives shape care, and the place of relationships and daily habits in treatment.
16:44ENHow Bridgewater Built the Vault for Human Researchers and AI AgentsSam Green, Aaron Linsky · Bridgewater AssociatesSam Green and Aaron Linsky explain how Bridgewater organized more than 100 million documents and built search and proactive research tools around them.
25:50ENKimi K3.1 Pro Tested: Strong 3D Demos, Uneven Results and Competitive PricingMatthew Berman · Forward FutureMatthew Berman tests the open-weight model on coding, 3D rendering and visual explanations, then compares benchmark results and prices.
1:13:26ENNaveen Rao on Energy, AI Hardware, Verification and the Future of RoboticsGast: Naveen Rao · Moderation: Harry StebbingsThe Unconventional AI founder argues that energy efficiency will shape AI hardware, while the growing volume of model output makes verification more valuable.
47:08ENHow Farza Majeed Makes Product Demo VideosAaron Epstein, Farza Majeed · Y CombinatorA founder’s approach to frequent launches, storytelling and measuring the audience that converts.
58:25ENThe Theranos Documentary, Reporting and What the Film Leaves OpenGast: Rob Copeland, Erin Griffith, John Carreyrou · Moderation: Max ReadHard Fork discusses You Can See Everything, a new venture and the evidence behind the Theranos story.
0:43ENTheo Distinguishes Security Vulnerabilities from Active AttacksTheo Browne · Ping LabsA short explanation of why disclosed software flaws and reported attacks are different kinds of security news.
32:20ENWho Is Local AI For? The Costs, Trade-offs and a Hybrid FutureMatthew Berman · Forward FutureMatthew Berman weighs data control and independence against hardware cost, setup complexity and inference speed.
0:54ENSam Altman: Seek Major Life Advice From People, Not AISam Altman · OpenAIThe OpenAI CEO distinguishes practical AI assistance from consequential life advice and argues for assistants that can push back.
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