I don't think the issue with robotics is a data gap. maybe somewhat, but the real issues are that:

- RL is extraordinarily sample-inefficient.

- distribution shift/catastrophic forgetting aren't solved. only off-policy learning with giant decorrelated batches works.

- the breakout success of transformers as an architecture doesn't neatly translate to robot motion policy models.

the field is missing fundamental breakthroughs.

I also find it very interesting that conversational AI has taken this long. where are the models with good turn-taking? passive listening? the ability not to respond in paragraphs? has Anthropic simply not gotten around to it?