Token Optimization

Token optimization refers to the process of refining and improving the performance of machine learning models by optimizing the representation of input data as tokens, which are discrete units of text or other data. By fine-tuning tokenization strategies, developers can significantly enhance the accuracy, efficiency, and scalability of natural language processing (NLP) and other AI applications, making token optimization a crucial consideration for tech professionals working on AI and machine learning projects.