{
  "id": 13820734,
  "title": "Recursive self-improvement through collective intelligence",
  "url": "https://urgent.news/2026/10/11/recursive-self-improvement-through-collective-intelligence",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-11T22:22:10.000Z",
  "source": {
    "name": "Hacker News",
    "slug": "hacker-news",
    "url": "https://pub.sakana.ai/mass/"
  },
  "original_language": "en",
  "account": null,
  "summary": "The article discusses the concept of recursive self-improvement (RSI) in AI models, where the model itself acts as its own optimizer and evaluator. The authors introduce Multi-Agent Self-Supervision (MASS), a learning loop that uses the same model for executor, optimizer, and evaluator roles. By distilling collective intelligence from multi-agent systems, MASS aims to improve the model's performance on non-verifiable research tasks, where automatic rule-based signals are not available. The process is evaluated using GPT-5.5 and Claude Opus 4.8, which provide an outside measure of improvement in a loop where supervision comes solely from the model.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}