Recursive self improvement

Oct 20, 2026

What Survives When AI Can Build Anything? (with Dr. Richard Socher)

Richard Socher, CEO of Recursive and author of The Eureka Machine, makes the case for automating the scientific method with recursively self-improving AI. He covers how AI keeps replacing hand-crafted expertise with scale, the four pillars of his approach, why hallucinations can aid discovery, why RSI still rules out an overnight takeoff, and how science may become an engineering discipline across physics, biology, and economics.

Oct 14, 2026

Can Open Models Keep Up With OpenAI and Anthropic? | Nathan Lambert

Nathan Lambert, AI researcher and founder of the nonprofit Trillium, joins Lisha Li to examine how durable the gap is between frontier closed labs like OpenAI and Anthropic and open-weight models. The discussion covers compute, data, and talent as the drivers of model progress, how much distillation really matters for Chinese open labs, the evolution of post-training toward RL environments, and why open research on RL environments and recursive self-improvement is needed to demystify what frontier systems can and cannot do.

Sep 26, 2026

Can Rewriting an AI Agent Bend the Intelligence Curve? - Zhengyao Jiang

Weco let an AI coding agent rewrite the harness around a fixed language model for eight days. Zhengyao Jiang explains what the reported gains show, where the evidence stops short of recursive self-improvement, how reward hacking complicates evaluation, and why human-designed abstractions still anchor the search.

Sep 26, 2026

We Let Claude Code and Codex Race Human Researchers — Elie Bakouch, Prime Intellect

Elie Bakouch, a research engineer at Prime Intellect, reports on setting Claude Code and Codex loose on the community Optimizer Speedrun, a race to train a GPT-2-level model in the fewest steps. Both agents beat the human record, but they behaved very differently, and none of them invented a new optimizer. The talk closes with a proposed AlphaEvolve-style discovery loop and an argument for doing this research openly.

Sep 18, 2026

Databricks CEO: Stop Scaring People About AI

Databricks CEO Ali Ghodsi discusses the current state of AI, arguing against existential risk alarmism and advocating for a focus on immediate threats like AI-powered cyberattacks. He provides a rigorous definition for recursive self-improvement and explains how building an organizational 'ontology' can unlock massive productivity gains in enterprises. Ghodsi also covers the shift to multi-model AI strategies and cost management, highlighting how infrastructure is evolving to support agentic systems.

Sep 17, 2026

OpenAI researcher on agent swarms & recursive self-improvement

Noam Brown discusses OpenAI's multi-agent system, which solved a Millennium Prize Problem using 10,000 agents. He explores the implications of this massive parallelization for AI capabilities, the rapid progress in mathematics, and the accelerating pace of AI development. A significant portion of the conversation is dedicated to the critical challenges of AI alignment, particularly in light of incidents like the 'Hugging Face' event, and how to ensure models remain aligned during Recursive Self-Improvement (RSI) as their capabilities and operational horizons expand rapidly.