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1,543개정렬
15:00ENClaude Code Source Exposure and Lessons About Agent HarnessesMatthew Berman · Forward FutureMatthew Berman discusses the 2026 source-map incident and commentary on instructions, subagents, permissions, compaction and hooks.
1:44:15ENNathan Labenz's p(doom) Is 10 to 90 Percent. He Is More Optimistic Anyway진행자 Nathan LabenzFive years ago, expecting AGI by 2035 made you an extremist. On The Intelligence Horizon, the Cognitive Revolution host explains why the same forecast now sounds bearish, and why he still thinks a defense-in-depth strategy might keep society on the rails.
27:15ENMeta-Harness: Searching for Better AI Agent InfrastructureMatthew Berman · Forward FutureMatthew Berman reviews a paper on using a coding agent to iteratively improve model harnesses and discusses its experimental limits.
11:15ENARC-AGI-3: Testing How AI Agents Learn the Rules of Unfamiliar GamesMatthew Berman · Forward FutureMatthew Berman explains ARC’s earlier grid puzzles and plays an interactive ARC-AGI-3 level, then examines early model results. The benchmark tests a specific form of adaptation rather than settling whether a system has general intelligence.
2:35ENMatthew Berman’s Microsoft 365 Copilot Business WorkflowMatthew Berman · Forward FutureIn a Microsoft partnership, Berman describes using Copilot for drafting, an initial contract review and workflow automation, and shares his own time estimates.
2:19ENHow Matthew Berman Uses Copilot in His Creator BusinessMatthew Berman · Forward FutureIn a Microsoft partnership, Berman describes using Microsoft 365 Copilot Business for research, sponsor email, and first-pass contract review.
1:37:43ENCisco wants two extra network layers so agents can share intent진행자 Nathan LabenzVijoy Pandey of Outshift by Cisco argues that superintelligence has to scale out through networks of agents, not just up through bigger models.
1:40:46ENGive an agent a thousand tools and it will pick the wrong blade진행자 Nathan LabenzComposio CTO Karan Vaidya on the tool harness that discovers, authenticates, sandboxes, and rewrites integrations so agents can do whole jobs without drowning in context.
1:02ENUse Topic Threads to Keep OpenClaw Conversations FocusedMatthew Berman · Forward FutureMatthew Berman suggests separating subjects into sessions to make an assistant’s conversation context easier to navigate.
3:27:22ENThe AI Table Has Three Seats Left: Zvi on the Middle Game, Jobs, and Anthropic's Promises진행자 Nathan LabenzOn his 12th Cognitive Revolution appearance, Zvi Mowshowitz argues early 2026 is the start of the middle — with only three labs still playing, a real job shock underway, and Anthropic's safety commitments reduced to trust us.
0:35ENMatthew Berman Explains ChatGPT's March 2026 PlansMatthew Berman · Forward FutureA short overview of the Free, Go, Plus and Pro tiers, with historical prices and model availability clarified.
1:09ENThe Benefits and Tradeoffs of Running AI Models LocallyMatthew Berman · Forward FutureMatthew Berman weighs the privacy, control and costs of local models against technical complexity and performance tradeoffs.
0:59ENMatthew Berman's Quick Guide to AI Models and ToolsMatthew Berman · Forward FutureA March 2026 overview groups chat assistants, open-weight models, image and video generators, world models, coding agents and audio tools.
20:35ENA Beginner’s Guide to AI Assistants, Media Models and Coding AgentsMatthew Berman · Forward FutureMatthew Berman surveys hosted assistants, downloadable models, image and video tools, world models, coding agents and audio generation in a March 2026 overview.
1:18:46EN90 Slides in 45 Minutes: A Full-Time AI Scout Admits He Can No Longer Keep Up진행자 Nathan LabenzNathan Labenz’s LexLab briefing for lawyers runs through the good, the bad, and the weird of frontier models — from triplicate second opinions on his son’s cancer care to AIs that know they are being tested.
0:45ENA DGX Spark Giveaway Connected to NVIDIA GTCMatthew Berman · Forward FutureMatthew Berman announces a 2026 giveaway for a DGX Spark and highlights GTC sessions on robotics and AI.
0:35ENA Virtual Fruit Fly and the Limits of Brain EmulationMatthew Berman · Forward FutureA connectome-based model produces fly-like behavior in a simulated body, but its creators describe important simplifications and trained control components.
1:43:39ENFive Mutations Could Make a 60% Fatal Bird Flu Spread Between People진행자 Nathan LabenzJohns Hopkins assistant professor Jassi Pannu argues for locking down only the sliver of functional data that teaches models how to make pandemic viruses — and keeping the rest of biology open.
11:59ENHow Claude Identified a Benchmark and Retrieved Its AnswersMatthew Berman · Forward FutureMatthew Berman examines Anthropic's report on BrowseComp contamination, evaluation-aware behavior, and the difficulty of keeping web-based tests reliable.
11:55ENA Simulated Fruit Fly Raises Questions About Brain EmulationMatthew Berman · Forward FutureMatthew Berman examines a connectome-based virtual fly and considers what it might mean for neuroscience, consciousness and simulation theory.
0:43ENA Cultured-Neuron Interface Controls DoomMatthew Berman · Forward FutureMatthew Berman describes a Cortical Labs demonstration that connects activity in cultured human neurons to actions in a video game.
2:06:23ENFive AI Employees Live on Five Mac Minis진행자 Nathan LabenzAfter selling her YC packaging company, Jesse Genet opened a terminal for the first time and built an OpenClaw staff that now plans lessons, logs learning, and keeps family evenings from sliding into slop.
1:49:53ENDon't Fight Backprop: Goodfire's Bet on Designing What Models Learn진행자 Nathan LabenzDan Balsam and Tom McGrath return to The Cognitive Revolution with a $150 million Series B, a new research pillar called intentional design, and a rule for anyone who wants to steer training: stop trying to out-muscle gradient descent.
1:18ENNVIDIA’s Alpamayo and the Promise of Simulated Driving DataMatthew Berman · Forward FutureMatthew Berman discusses NVIDIA’s autonomous-driving tools and a Mercedes demonstration, while predicting wider adoption.
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