I have not overlooked anything. I had imagined that this "mapping", to have any power, would also need to be handled by an LLM (action expert). But here is the problem with that. That would not be as "intelligent" as an LLM....And you can't make it as smart as the LLM because there is not a similarly huge training data on which LLMs are trained on..

The backbone of the VLA there is literally a pre-trained Gemma model. And a small one at that.

You already downgraded your claims from "LLMs are irrelevant to robotics" to a measly "you can't train a useful robotics LLM because there's not enough data". And you say that while looking at an LLM that was pre-trained on all of internet scraped and only then reused for robotics.

Both the pool of robotics-relevant data and the performance of foundation model LLMs grow over time. All the companies that are serious about robotics are serious about scaling up data collection.

I'm not going to claim that this "LLM core" approach is the best approach to AI robotics possible - but if you're betting on it failing outright, you're going to be fighting uphill.

>to a measly "you can't train a useful robotics LLM because there's not enough data"..

This was the claim from the very beginning. You should have asked why I think what I think, instead of leading with "the entire premise is wrong!"...

No, you openly, plainly went and downgraded your claim to a somewhat defensible one. It's not subtle.

Your entire premise was wrong at every point, and now you're trying to wriggle your way out of admitting it.