Why Muon Outperforms Adam: A Curvature Perspective
A new research paper and accompanying analysis explore the performance advantages of the Muon optimizer over Adam, particularly in the training of large language models and vision classifiers. Studies indicate that Muon learns more robust and transferable features, showing better performance on corrupted data and improved transferability to downstream tasks. This superiority is attributed to Muon's ability to reduce curvature penalties by maintaining lower normalized directional sharpness, especially in later stages of training, an effect amplified by data imbalance. AI
IMPACT Muon's demonstrated ability to learn more robust and transferable features could lead to more efficient and effective training of future large language models and AI systems.
