Matthew Bermanheute +20
20VC with Harry Stebbingsheute +14
No Priors: AI, Machine Learning, Tech, & Startupsheute +1
AI Engineerheute +24
The Buildersheute +1
Uncapped with Jack Altmanheute +1
Cheeky Pintheute +1
Cognitive Revolution "How AI Changes Everything"gestern +24
Theo - t3․gggestern +116
Sequoia Capitalgestern +1Neueste Artikel
4.027 ArtikelSortieren
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.
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.
34:11ENAnatoliy Bilenko and Alberto Carretero: Making Database Protocols Reliable with Formal Methods and AIAnatoliy Bilenko, Alberto Carretero · CanonicalCanonical’s database engineers connect executable specifications, model-based tests, failure exploration, and reconstructed execution histories—and explain why none of these techniques proves a real system correct on its own.
1:03:37ENMatthew Berman’s Team Tests Kimi K3.1 on Animation, Games, and ChartsMatthew Berman, Alex, Brian · Forward FutureA live team AMA turns into an informal test of Kimi K3.1, from personal-agent workflows to motion graphics, a browser game, and a benchmark chart.
1:43:22ENAI Security, Investment and the Debate Over France’s FutureGast: Nikesh Arora · Moderation: Jason Calacanis, Chamath Palihapitiya, David FriedbergThe All-In hosts and Nikesh Arora discuss cybersecurity and AI spending, then debate France’s unrest, public services and US policy.
34:35ENSemiAnalysis on ASML's Hybrid-Bonding Patents, HBM Economics and the Next Tool EcosystemGast: Sherry Zhang, Howie · Moderation: Jordan NanosJordan Nanos, Sherry Zhang and Howie examine a track-based bonding design that brings the wafer to the die, then explain why adoption depends on precision, cleanliness, economics and a changing supply chain.
1:00:39ENAmazon CEO Andy Jassy on the $220 Billion AI BuildoutGast: Andy Jassy · Moderation: Ben Horowitz, Erik TorenbergEven at roughly $220 billion of 2026 CapEx, Jassy says Amazon is still turning away AI demand. He tells Ben Horowitz and Erik Torenberg why AWS could become a trillion-dollar run-rate business, and why inference cost, custom chips, and smaller teams matter more than squeezing old customers.
1:09:00ENDwarkesh Patel: What will computer chips look like in 2045?Gast: Chris Auth, Kevin Fischer, Jack Kavalieros, Tyler Osborn, Pushkar Ranade, Gary Dickerson, Peter Wennink, Elon Musk · Moderation: Dwarkesh PatelAfter two days inside Intel’s most advanced fab, Dwarkesh Patel walks through gate-all-around, backside power, High-NA EUV, ruthenium, CFET, and hybrid bonding — and asks Intel’s leadership how the industry can possibly meet AI’s 3×-a-year compute demand when the world’s chipmaking tools cannot.
28:15ENSteve Poole on Open-Source Security and AI’s Maintenance ChallengeOlimpiu Pop, Steve PooleWhy faster vulnerability discovery increases pressure on maintainers, dependency users and upgrade processes.
Mehr laden24 von 4.027 angezeigt