The word on the street among the researchers I know from my grad school days is that this is basically a bunch of datasets that were created earlier on for specific papers, and the subset of researchers are repackaging them as a kind of weird academia twitter winnertakeall thing.
The author list also reminds me of the embarrassing practices of the physics community…
Nothing wrong with releasing a webpage with a list of datasets, but the press and need for a whole big announcement that claims it will change robotics makes them seem desperate.
Paper is pretty upfront about that, "we provide the Open X-Embodiment (OXE) Repository, which includes a dataset with 22 different robotic embodiments from 21 different institutions". Some of the data is new from Google's robots, but the rest is not.
The author list is long because Google is a big company with big teams.
Aside from this paper, I do think that generative modeling is going to change robotics. It seems likely that large transformer models could learn to do many simple tasks in response to natural-language instructions. This could be the burger-flipping robot.
The author list isn't long because everybody at Google got listed. There are a ton of full Professors in the author list. This is a cross-university effort.
They are attention-seeking, but they don't care about you, they want big grant money. Training is very expensive and it's a lot to ask for money for not just robotics hardware but now also big compute. Imagine trying to bid for a $100m H100 cluster like some sovereign nations.
I think one of the contributions is that the data are provided in the same format for all robot embodiments, i.e. action spaces, and observations. This way they can feed all the data to same model.
The author list also reminds me of the embarrassing practices of the physics community…
Nothing wrong with releasing a webpage with a list of datasets, but the press and need for a whole big announcement that claims it will change robotics makes them seem desperate.