Sakana AI· Sakana models

Evolving New Foundation Models: Unleashing the Power of Automating Model Development

We’re pleased to announce that our paper, “Evolutionary Optimization of Model Merging Recipes,” has been accepted to Nature Machine Intelligence and published today! The latest version includes new experimental results that further validate our approach: Link to our Nature Machine Intelligence publication. Back in March 2024, Sakana AI released “Evolutionary Model Merge,” which generated some attention in the AI community. It has since been implemented in well-known open-source frameworks like mergekit and Optuna Hub, enabling diverse users to create and publish many unique models. Multiple internal and external teams have been pursuing follow-up research; one example is “CycleQD,” which was accepted to ICLR 2025. We are happy to incorporate all the feedback from the community and from our reviewers, and release additional results into our Nature Machine Intelligence publication. We view “Evolutionary Model Merge” as the first step in our long-term R&D efforts. Sakana AI will continue to learn from the principles of nature and forge new frontiers in foundational model development. Stay tuned! Summary …

Announced

20 Mar 2024 15:00 UTC

Detected

28 Aug 2026 21:48 UTC (+891d after)