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7:33ENAce Computer-Use Agent: Fast Desktop and Browser DemonstrationsMatthew Berman · Forward FutureMatthew Berman reviews General Agents’ examples and reported click accuracy and latency, while noting he has not yet tested Ace himself.
2:14:59ENAlways Bet on the Models: How Shortwave's Andrew Lee Shipped Tasklet as Agents All the Way DownModeration: Nathan LabenzThe Firebase co-founder argues that workflow software is already obsolete, that MCP is optional, and that the only durable advantage left for an AI startup is speed.
44:34ENThe Cheaper Intelligence Gets, the More of It We'll BuyModeration: 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.
1:30:28ENA Perfect Score Is 32,000 Units: Only Claude Built a Cooperative SocietyModeration: 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.
1:50ENFive AI Trends Discussed by Coveo’s Sébastien PaquetMatthew Berman · Forward FutureMatthew Berman summarizes a 2025 interview on production systems, smaller models, agents and trust.
19:06ENBuilding Effective AI Agents: Patterns, Trade-offs and EvaluationMatthew Berman · Forward FutureMatthew Berman discusses Anthropic’s guide to workflows and agents, adding examples from his own projects.
1:01:53ENHumans Wrote 1.3 Percent of the Tokens. The AI Lab Still Designed Working Nanobodies.Moderation: Nathan LabenzStanford's James Zou describes a GPT-4o research group that invented a protein-design pipeline for under $100 — and a sparse autoencoder that pulled an undocumented motif out of ESM-2.
1:55:53ENAI Beats Humans at Reading Papers. It Still Cannot Count Atoms.Moderation: Nathan LabenzAndrew White, Head of Science at Future House, maps what language models can already do in chemistry and biology—and the bottlenecks they do not dissolve.
1:27:33ENA 70B Model Booked Dinner 20% of the Time. MultiOn Took It to 95% in a DayModeration: Nathan LabenzMultiOn CEO Div Garg returns to The Cognitive Revolution to recap 18 months of agent hype, the AgentQ stack, and why 2025 might still be the year of vertical agents.
10:20ENHow the Freysa AI Agent Was Persuaded to Release a Crypto Prize PoolMatthew Berman · Forward FutureMatthew Berman examines a 2024 adversarial game in which a misleading message caused an AI agent to approve a 13.19 ETH payout.
13:34ENSam Altman’s “Intelligence Age”: Superintelligence, Scaling and WorkMatthew Berman · Forward FutureMatthew Berman reads Altman’s 2024 essay and discusses its predictions for AI assistants, education, infrastructure and jobs.
2:03:55ENThe More You Constrain an Agent, the More You Can Trust ItModeration: Nathan LabenzAgent.ai engineering lead Andrei Oprisan tells Nathan Labenz why narrow, highly prescribed workflows beat open-ended autonomy — and how a 12-person team shipped a free agent network past 40,000 users in a few months.
18:43ENSakana AI's AI Scientist and the Prospect of Automated ResearchMatthew Berman · Forward FutureMatthew Berman explores a 2024 system for generating and evaluating machine-learning research, and argues that automation could eventually accelerate AI progress.
1:50:08ENWaymo's Injury Rate Is Five Times Lower. It Still Loses to a Lyft.Moderation: Nathan LabenzHuman drivers average one fatal crash per 100 million miles — and that bar still defines the self-driving debate.
1:05:52ENInfinite AI Interns Are Already on the JobModeration: Nathan LabenzNathan Labenz tells computer-science students how to stand out when models are beating doctors on routine work and firms are hiring fewer juniors.
1:25:09ENTwo-Headed Worms, Regenerated Legs, and a Sort That Learned to WaitModeration: Nathan LabenzTufts biologist Michael Levin tells Cognitive Revolution why anatomy is rewritable software, and why he stopped a paper that might have made AI more alive.
4:56ENIf the Mind Is a Tool, AI Looks Less Like a ThreatModeration: Nathan LabenzYohei Nakajima and Nathan Labenz pause a TED AI talk to connect agent-building habits with East–West ideas of identity.
15:11ENBuilding a Transcript-to-Article Team in AutoGen StudioMatthew Berman · Forward FutureMatthew Berman configures a retrieval skill, two agents and a group workflow, then troubleshoots missing credentials and output.
1:43:07ENAn Agent Posted Five Tweets — and 5,000 People Didn't NoticeModeration: Nathan LabenzMultiOn founder Div Garg walks Cognitive Revolution through what web agents can actually do in early 2024, what they cost, and why guardrails have to sit outside the model.
1:50:57ENTwenty-Eight Days After GPT-4, an AI Designed and Ran a Chemistry ExperimentModeration: Nathan LabenzGabe Gomes and his Carnegie Mellon students built Coscientist, a language-model agent that plans, codes, and executes real experiments on a remote cloud lab.
10:12ENA 2023 Tutorial for a Family Tech-Support Bot on TelegramMatthew Berman · Forward FutureIn a Botpress-sponsored demonstration, Matthew Berman builds a friendly support assistant and connects a version to Telegram. The interface and account requirements are historical.
1:22:59ENIf Your Agent Is Right 80% of the Time, Ten Steps Leave You With 10%Moderation: Nathan LabenzImbue CTO Josh Albrecht tells Nathan Labenz how a 27-person, pre-product research company is putting $200 million and 10,000 H100s toward agents that can actually finish a long job.
1:36:39ENOpenAI’s $5 Million Bet: A 60-Person Team Wants GPT-4V to Give Cars Common SenseModeration: Nathan LabenzGhost Autonomy cofounder John Hayes tells Cognitive Revolution why a multimodal model on the driving path could reset self-driving after two decades of DARPA-era stacks.
1:03:46ENWhen Code Costs a Dime, You Throw the App AwayModeration: Nathan LabenzLindy founder Flo Crivello tells Nathan Labenz how an AI employee learns APIs from documentation, why GPT-4 made quality the only metric that matters, and why even he wants aviation-style rules for AI.
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