🔗 AI Progress Could Compress Years

A Cambridge paper by 22 authors, including Geoffrey Hinton, Yoshua Bengio, OpenAI’s Jakub Pachocki, and Anthropic’s Jack Clark, examines compressing years of AI progress into months.

At Anthropic, model-written code rose from single digits to over 80% since early 2025. Autonomous R&D tasks rose from 1% to 26% in 6 months. Full automation could make progress 10x faster in about 1.5 years.

Compute or data could limit the scenario. Risks include lost control and a winner gaining too much advantage. The authors propose reporting R&D automation, external audits before deployment, and ways to pause specific data-center workloads.

📊@tech