Get the latest tech news
How Sakana AI’s new evolutionary algorithm builds powerful AI models without expensive retraining
M2N2 is a model merging technique that creates powerful multi-skilled agents without the high cost and data needs of retraining.
For enterprises looking to build custom AI solutions, the approach offers a powerful and efficient way to create specialized models by combining the strengths of existing open-source variants. In comments to VentureBeat, the paper’s authors said model merging is a gradient-free process that only requires forward passes, making it computationally cheaper than fine-tuning, which involves costly gradient updates. The results showed that its diversity-preservation mechanism was key, allowing it to maintain an archive of models with complementary strengths that facilitated effective merging while systematically discarding weaker solutions.
Or read this on Venture Beat
