[r/ML] [P] Weber Electrodynamic Optimizer + SDR Hardware Entropy for Autonomous ML Research (fork of karpathy/autoresearch)

Summary

This project, a fork of karpathy/autoresearch, introduces the Weber Electrodynamic Optimizer, which applies 19th-century Weber's force law to gradient descent. This novel approach modifies the effective learning rate per-parameter based on its momentum and acceleration. Parameters that are accelerating receive larger steps, while decelerating ones are dampened, potentially enhancing optimization.

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