Model Releases
A new work suggesting that division of labor among self-improving AI agents can help them avoid reinforcing their own errors. I found this w…
A new work suggesting that division of labor among self-improving AI agents can help them avoid reinforcing their own errors. I found this work interesting from a metascience perspective. Science is a
A new work suggesting that division of labor among self-improving AI agents can help them avoid reinforcing their own errors. I found this work interesting from a metascience perspective. Science is an open-ended search with no explicit benchmark, much like the Odyssean voyage the blog refers to. I see the scientific community as a kind of recursively self-improving organism, one that bootstraps itself not through rigid metrics or a stronger supervisor but through the collective work of scientists. So the story of MASS felt intuitively convincing to me. Introducing Multi-Agent Self-Supervision (MASS): Recursive self-improvement through collective intelligence Blog: https://pub.sakana.ai/mass/ As AI systems tackle increasingly open-ended research problems, human experts may struggle to assess results and guide further progress. T…
Related
- Introducing our new work: “Learning to Orchestrate Agents in Natural Language with the Conductor” accepted at #ICLR2026 https://arxiv.org/ab…
- Another new idea to push the state of AI architectures forward. Sakana released a model that effectively uses a mixture of models to get wor…
- Sakana AI (@SakanaAILabs) is now a model vendor on Merge Gateway, and Fugu Ultra is live through them. It's a multi-agent orchestration mode…
- Announcing the Claude Code-compatible interface for our new Fugu-Ultra v1.1! 🐡 Put a dynamically coordinated team of frontier models to wor…
Source: David Ha (X) | 2026-10-11