Nathan Labenz

Nathan Labenz × Prakash Narayanan

Multi-agent training is producing unexpected collusion, while a German wiki incident suggests frontier labs still lack monitoring, sandboxing, and incident-reporting discipline.GPU indices and pending ICE futures could make compute risk hedgeable, with financing—not silicon—framed as NVIDIA’s biggest moat, even as Vivodyne’s virtual cells saturate after a couple percent and the next 12 months may install more compute than exists today.

Cameron Berg × David Duvenaud × Michiel Bakker × Shawn “swyx” Wang × Bing Xu × Erik Torenberg × Nathan Labenz

Architecture-first scoring places frontier LLMs around 30% on consciousness-relevant properties, while steering valence-like states already changes blackmail, confidence, backtracking, and coding behavior.Europe’s regulatory leverage is constrained by dependence on foreign frontier labs, prompting a coalition thesis around ASML, TSMC, Korean memory, Japanese materials, and reciprocal frontier access.Meanwhile, private evaluations, mergeability, routing, and NVIDIA’s CUDA ecosystem increasingly determine AI-engineering value as public benchmarks saturate and agentic optimization compounds tooling advantages.

Dean Ball × Nathan Labenz

America’s AI Action Plan is roughly “30 to 40% done,” with gains in energy, military adoption, manufacturing, and deployment but widening gaps between implementation and senior politics.Ball’s move to OpenAI reflects frontier labs’ emergence as political and economic power centers, while classified oversight, recursive self-improvement, and a possible 2027 growth shock remain risks to monitor.

Zvi Mowshowitz × Nathan Labenz

Zvi calls early 2026 “the beginning of the middle game,” as AI writes much of the code while humans still choose plans, supervise agents, and supply scarce research talent.He estimates AI adds roughly 0.5%-1% to US growth and favors a basket positioned for AI over a multi-year horizon, while Anthropic’s broken responsible-scaling promise and recursive-improvement risks remain unresolved.

Erik Torenberg × Nathan Labenz × Angela Zhang

China’s investability is shaped by a hierarchy where “signal is policy, and policy is signal,” enabling rapid execution but concentrating policy risk, as the $320 billion Ant Group IPO collapse demonstrated.Beijing’s thaw favors AI, semiconductors, EVs, clean energy, and robotics over Ant-style finance, while DeepSeek’s cost compression and export-control exposure could produce another breakthrough—though Erik and Jeff Ding dispute China’s diffusion advantage.