recursive-self-improvement

This paper introduces the Red Queen Gödel Machine (RQGM), an evolutionary framework for recursive self-improvement under non-stationary utilities, where agents and evaluators co-evolve, improving performance on coding tasks, scientific writing, and Olympiad-level proof grading.

Vadim Fedenko shares a technical analysis of Recursive Self-Improvement (RSI), arguing that true RSI requires improving capability faster than complexity and expanding architectural space rather than just optimizing within fixed parameters. He doubts recent claims by xAI and Anthropic that RSI could arrive within a year, citing LLMs' poor subtractive engineering skills and current reward functions that ignore complexity.

Recursive releases early results from its automated AI research system, achieving state-of-the-art in fixed-budget language model training, small-model training speed, and GPU kernel optimization, and open-sources artifacts.

Jeremy Howard critiques Anthropic's approach to frontier AI safety, arguing that the lab with the top-ranked model should not use it for frontier research to slow self-improvement and prevent power imbalance.

Anthropic's Fable 5 model includes silent safeguards that degrade responses for requests related to competitive AI development, without user awareness, raising concerns about transparency and research impact.

OpenAI and Anthropic have both called for an international organization to oversee frontier AI development, citing risks of recursive self-improvement and an intelligence explosion. The joint plea highlights concerns that commercial incentives could outpace safety measures as AI capabilities advance rapidly.

Sakana AI launches RSI Lab in Tokyo, dedicated to recursive self-improvement (RSI) where AI builds AI, aiming to achieve self-improvement without unlimited computational resources.

Anthropic warns that AI systems may soon achieve recursive self-improvement without human oversight, urging the industry to develop safety brakes and cooperate on regulation.

Anthropic warns that AI is accelerating AI development (recursive self-improvement) and supports a coordinated pause, revealing that Claude now writes over 80% of their production code.

Anthropic internal data shows Claude is accelerating AI development, potentially leading to a path of recursive self-improvement. The process of AI autonomously building a more powerful successor is happening faster than anticipated.

Anthropic's research article details the accelerating trend of AI systems taking over more of their own development, pointing toward recursive self-improvement. The article presents evidence and implications of AI's growing autonomy in software engineering and model training.

Anthropic publishes in-depth article 'When AI builds itself', showing AI systems accelerating their own development, including code generation, benchmark saturation, and internal data indicating an 8x increase in engineer productivity. The article explores the trend and potential impact of recursive self-improvement.

Anthropic reports that over 80% of its new production code is now authored by Claude, leading to an 8x increase in code shipped per engineer. The article outlines a roadmap for enterprises to adopt similar AI-driven development workflows.

Anthropic's Mythos system achieved a 52x speedup in optimizing training code compared to a human's 4x speedup over 4-8 hours on the same task, with the caveat that absolute multiples depend heavily on starting code quality. The like-for-like comparison shows roughly 3x–52x improvement across models over the past year.

Anthropic reports internal data suggesting Claude is accelerating AI development, raising the possibility of recursive self-improvement or AI autonomously building more capable successors.

Anthropic's Institute publishes analysis on progress toward recursive self-improvement, showing AI is already accelerating AI development—engineers ship 8x more code per quarter—and projecting that AI systems capable of fully autonomous self-improvement could arrive sooner than most institutions are prepared for.

Anthropic discusses the plausibility of AI systems designing their own successors, noting Claude may approach research-level judgment, and announces the Anthropic Institute to study implications of increasingly powerful, potentially self-improving AI systems.

OpenAI reports early signs of recursive self-improvement in current AI systems, a potentially significant development in AI capabilities.

Skill RSI is a free tool that recursively evaluates and improves AI skills via procedural evaluations and a research agent, supporting standalone or Codex plugin usage.

OpenAI is hiring a safety researcher with a salary up to $445,000 to prepare for the risks of AI achieving recursive self-improvement, as coding tools advance rapidly and industry leaders warn about the approaching singularity.