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This article explores a technique called 'CPU-maxing tokenization' to reduce the 'time to first token' (TTFT) in natural language processing models. The approach focuses on optimizing the tokenization process, which can be a performance bottleneck, in order to improve the overall responsiveness and efficiency of these models.