The claims of "embodiment" and "reasoning over images" made in this paper seem to really stretch the definitions of these words. IIUC, what is being fed into th

The claims of "embodiment" and "reasoning over images" made in this paper seem to really stretch the definitions of these words. IIUC, what is being fed into the model as input is essentially a text caption generated from the image, and the model does next-word prediction repeatedly in an effort to generate instructions for consumption by a robot. So the LLM model itself, as always, has no groundedness and is statistically converting text to text (or to be more precise, numeric vectors to numeric vectors), with the required intervention of humans to assign and extract meaning through robotic control development or image labeling. While it is an interesting technique for using LLMs to control robotic systems, it does not seem like a step towards any kind of AGI.