Fast weights are a neural network technique enabling rapid, context-specific learning by temporarily adjusting parameters during inference. Used in memory-augmented models and transformers, they allow systems to adapt on-the-fly without retraining. Researchers, AI engineers, and developers building dynamic, few-shot learning applications benefit from faster adaptation and improved performance in evolving data environments.
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