Foundation Models

Action Tokenization

Action tokenization is the conversion of continuous robot actions into discrete tokens so that language-model architectures can predict them autoregressively. The simplest scheme bins each action dimension uniformly, as in RT-1 and RT-2, which mapped actions onto reserved text tokens. Later approaches compress action chunks more efficiently; the FAST tokenizer, for example, applies a discrete cosine transform followed by byte-pair encoding to represent high-frequency chunks with few tokens.

Why it matters for physical AI

Tokenization lets robot actions share the same interface as text, unlocking transfer from internet-pretrained vision-language models, but coarse binning limits precision, driving research into learned and compressed action codes.