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Quantization and Optimization for In-Browser Machine Learning
Exploring quantization in machine learning for web browsers to compress network weights, reduce model size, and enhance performance, enabling significant memory cost reductions and speed optimization. Discussions on using varying numbers in JavaScript, tokenization importance, and the future integration of WebGPU for web machine learning applications.