REAL-TIME ACTION CHUNKING WITH LARGE MODELS

Summary from the TLDR AI newsletter

Unlike chatbots or image generators, robots must operate in real time - delays between inputs and outputs have a tangible effect on performance. While vision-language-action (VLA) models have achieved promising results in open-world generalization, they can be slow to run. This article presents an algorithm called real-time chunking that enables real-time execution without discontinuities. It works on any diffusion- or flow-based VLA with no training-time changes.