Quantization helps in converting complex data into simpler 'tokens' that are easier to work with. These tokens can be used in models just like words in language models.
There are different quantization approaches, like Vector Quantization and Group Vector Quantization, which can improve how data is represented and processed. Each method has its own way of managing and encoding the data.
Some new strategies, like Latent Free Quantization and Finite State Quantization, use fixed values or unique arrangements to make the quantization process more efficient and effective. They simplify how data is processed without losing important information.