Neural Thermodynamics: Entropic Forces in Deep and Universal Representation Learning

arXiv — cs.LG•Monday, October 27, 2025 at 4:00:00 AM

A new theory on entropic forces in neural networks sheds light on the learning dynamics of deep learning and large language models. This research is significant as it addresses the urgent need to understand the emergent phenomena in these technologies, particularly how representation learning plays a crucial role in their development. By exploring the entropic loss landscape and parameter symmetries, this study could pave the way for more effective training methods in AI, enhancing our ability to harness these powerful tools.

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