This is actually a pretty good point, but quite honestly isn't this just an implementation detail? We can wire up a squirrel robot, give it a wifi connection to a Cerebras inference engine with a big context window, then let it run about during the day collecting a video feed while directing it to do "squirrel stuff".

Then during the night, we make it go to sleep and use the data collected during the day to continue finetuning the actual model weights in some data center somewhere.

After 2 years, this model would have a ton of "direct experiences" about the world.

> then let it run about during the day collecting a video feed while directing it to do "squirrel stuff".

Your phrase "squirrel stuff" is doing a lot of work.

What are the robo-squirrels "goals" and how does it relate to the physical robot?

Is it going around trying to find spare electronic parts to repair itself and reproduce? How does the video feed data relate to its goals?

Where do these goals come from?

Despite all their expensive training, LLMs do not emerge goals. Why would they emerge for your robot squirrel, especially when the survival of its brain is not dependent on the survival of its mechanical body.