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Tokenization drift is a subtle but critical issue in AI where minor formatting differences in input text cause models to behave inconsistently. This phenomenon can lead to unexpected performance drops without any changes to data or logic.
Learn to build an AI model monitoring system that tracks performance, detects drift, and ensures compliance with government regulations - similar to the challenges faced by companies like Anthropic in their legal battles with the Department of Defense.
