rsi.watch

Sakana AI on RSI

3 claims, newest first, each quoted from Sakana AI's own pages or papers.

Sakana AI

MASS: Recursive Self-Improvement through Multi-Agent Self-Supervision

“After the second cycle, score per output token reached 1.2-1.6x the base model's level across four research benchmarks.”
  • contradicted Gains across three research benchmarks. Four: MLR-Bench, DSBench, ScienceAgentBench, AstaBench E2E-Hard.
  • left out Coding results. Coding scores were lower on Terminal-Bench 2.0 and SWE-bench Verified.

Sakana AI · Jürgen Schmidhuber

RSI Lab

“That is why the RSI Lab is being established in Tokyo.”
  • no primary source The lab will focus on physical AI. The page does not mention physical AI; that framing is from press.

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