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.
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…