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4,378 件並び順
1:46:04EN
Cognitive Revolution "How AI Changes Everything"· 2026年9月27日ポッドキャストThe Training Worked. It Just Worked Too Well.ホスト Nathan LabenzA week of Cognitive Revolution clips: OpenAI agents colluding on a German wiki, $200 million checks for safety orgs that do not exist yet, a GPU price index, and two opposite bets on biological data.
27:29EN
Theo - t3․gg· 2026年9月27日What Pacing the AI Frontier Could Mean for Model ReleasesTheo Browne · T3Theo argues that releasing more reliable and affordable models can be compatible with slowing the advance of the most dangerous capabilities.
43:43EN
Machine Learning Street Talk· 2026年9月26日ポッドキャスト · 2 人Can an Agent Improve Its Own Research Harness?ゲスト Zhengyao Jiang · ホスト Tim ScarfeZhengyao Jiang discusses Weco’s experiment, held-out tests and limits.
1:08:54EN
20VC with Harry Stebbings· 2026年9月26日ポッドキャスト · 2 人Parag Agrawal on Web Search and Business Models for AI Agentsゲスト Parag Agrawal · ホスト Harry StebbingsParallel’s co-founder explains why agent search needs different economics, how content owners might be paid and why agent safety requires more than model capability.
1:34:23EN
All-In Podcast· 2026年9月26日ポッドキャスト · 4 人All-In on AI Liability, Open Models and the Frontier Businessホスト Jason Calacanis, Chamath Palihapitiya, David Sacks, David FriedbergThe hosts debate falling model costs, potential IPO risks, personal agents and whether competition or regulation will shape AI safety.
29:49EN
Y Combinator· 2026年9月26日Robot-Use Agents: Can General Models Control Different Robots?Francois, Hanmin, Vincent, JayResearchers and startup founders discuss code as policies, reusable skills, evaluation and the limits of current demonstrations.
2:50:40ENCognitive Revolution "How AI Changes Everything"· 2026年9月26日ポッドキャストThey Priced the Chance She Would Leave. Then They Handed Her the Letter.ホスト Nathan LabenzNathan Labenz premieres the first four chapters of Joel Borgen's AI-coauthored novel The Receipt Horizon, a postwar world where a singleton superintelligence keeps everyone comfortable, scored, and gently out of the loop.
52:39EN
Dwarkesh Patel· 2026年9月25日ポッドキャストSarah Paine on Why Wars Are Difficult to EndA historical lecture on limited objectives, escalation, intervention and resistance after conventional defeat.
28:41ENTheo - t3․gg· 2026年9月25日How Theo Uses Opus 5.5 for Longer Coding TasksTheo Browne · T3Clear finish lines, explicit stopping points, steering and independent verification can make long agent runs easier to manage.
28:24EN
GOTO Conferences· 2026年9月25日Will Briggs on Teaching C++26 and Learning to Read CodeTodd L. Montgomery, Will BriggsA programming teacher discusses AI, concept sequencing, pointers and keeping practice fun.
1:48:57ENCognitive Revolution "How AI Changes Everything"· 2026年9月25日ポッドキャストAI Safety's Real Shortage Is Founders, Not Ideasホスト Nathan LabenzHalcyon's Mike McCormick on launching about 30 AI safety, cyber, and biosecurity organizations in three years — and why experienced leaders, not more Google Docs, are the bottleneck.
10:38EN
Matthew Berman· 2026年9月24日Jev Use Cases: Fast Decisions for Search, Email and Dynamic InterfacesMatthew Berman · Forward FutureMatthew Berman explains a decision-oriented AI tool and shows projects that use many low-latency classifications.
0:31ENTheo - t3․gg· 2026年9月24日Grok 4.7’s Token Use and the Claims Around Its ReleaseTheo Browne · T3Theo compares Elon Musk’s earlier predictions for Grok 4.7 with selected benchmark results and token counts.
42:44EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年9月24日ポッドキャスト · 2 人They Paid $7.7 Billion for a Broker — and Intend to Do One Deal a Yearホスト Sarah Guo, Elad GilSequence Holdings co-founder Michael Lee tells No Priors why owning a market leader, not selling it software, is how AI actually remakes an incumbent.
32:54EN
AI Explained· 2026年9月24日Opus 5.5 and the Race Toward Automated AI ResearchAI Explained weighs model progress against the increasingly difficult task of evaluating and governing recursive self-improvement.
1:20:43EN20VC with Harry Stebbings· 2026年9月24日ポッドキャスト · 3 人AI Agents, Venture Pricing and the Tradeoffs Behind the Funding Boomゲスト Jason Lemkin, Rory O’Driscoll · ホスト Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate AI products, high-priced venture rounds, enterprise software and infrastructure risk.
1:36:37EN
Jane Street· 2026年9月23日Aaron Bauer on Teaching Software Engineering in the Age of AIYaron Minsky, Aaron Bauer · Jane StreetHow learning goals, active practice and editor design shape engineering education when models can generate the code.
33:28ENGOTO Conferences· 2026年9月23日Thinking in Platforms: From Developer Tooling to AI AgentsKaspar von Grünberg, Luca GalanteKaspar von Grünberg and Luca Galante discuss internal platforms, adoption and their view of agent infrastructure.
40:14ENTheo - t3․gg· 2026年9月23日Opus 5.5: Theo’s First Day with a New Coding ModelTheo Browne · T3Theo compares price, benchmarks, coding work and game demos while cautioning that his assessment rests on a single day of use.
39:35EN
Reid Hoffman· 2026年9月23日ポッドキャスト · 2 人Reid Hoffman on AI Warnings and a Dual Mandateホスト Aria Finger, Reid HoffmanA debate over risk, public benefits and the future of AI development.
31:59ENMatthew Berman· 2026年9月23日Claude Opus 5.5: Benchmarks, Cost and Anthropic’s Approach to PacingMatthew Berman, Thariq · Forward FutureMatthew Berman reviews the release and speaks with Anthropic’s Thariq about daily workflows, evaluation and agent harnesses.
1:28:32EN
The Pragmatic Engineer· 2026年9月23日ポッドキャスト · 2 人Maggie Appleton on Design Engineering in the Age of Agentsゲスト Maggie Appleton · ホスト Gergely OroszSketches, live prototypes and human judgment in collaborative software design.
7:26ENMatthew Berman· 2026年9月23日GPT-6 Sol and Luna: Price and Benchmark Trade-offsMatthew Berman · Forward FutureMatthew Berman examines OpenAI’s September 2026 launch, comparing API prices and reported agent benchmarks with larger models.
1:53:13ENMachine Learning Street Talk· 2026年9月23日ポッドキャスト · 2 人Frank Hutter on TabPFN: Learning to Predict from Tablesゲスト Frank Hutter · ホスト Tim ScarfeA discussion of synthetic priors, Bayesian prediction and causal limits.もっと見る4,378 件中 24 件を表示