Jeremy Howard proposes that labs claiming to slow recursive AI self-improvement should ban themselves from using their top model for frontier research while letting others access it. He argues Anthropic does the opposite — using its best model internally while reportedly blocking others from doing the same — accelerating the frontier and worsening power imbalance. Howard personally favors democratization over slowdown, but his point is about consistency: if you preach restraint, constrain yourself first.
Import AI 460 covers SocioHack, a benchmark where RL-trained LLMs discover loopholes in institutional rule systems. It also discusses Anthropic evidence for a practical form of recursive self-improvement, reflected in sharply increased code merged during 2026. Other sections examine multi-agent RL drones outperforming a champion human pilot, plus research showing state-controlled media can shape LLM responses in local languages.
TechCrunch reports that recursive self-improvement, or RSI, is becoming a new AI industry fixation, much like AGI. Researchers and startups including Recursive Superintelligence, Auto-Research, AutoScientist, and Disarray are exploring ways for AI systems to automate parts of AI research. But experts caution that AI-assisted research is not the same as fully autonomous self-improvement, especially while models still struggle with long-term self-direction and verification.
This Import AI issue is a long essay and fiction piece about living through rapid AI progress. Clark uses personal experience and Anthropic’s internal use of Claude to show work shifting toward delegation, verification, observability, and agent management. He then offers speculative 2026-2028 predictions around biology, autonomous companies, robotics, recursive self-improvement, and a positive singularity story focused on healthcare.
In the latest issue of Import AI 455, Jack Clark guides readers through an exploration of a highly forward-looking and both exciting and concerning theme: AI…