Excellent (what's with the trans bluhair style?)
The researchers hope that this will eventually lead to progress in building robots that can cope with our volatile and mutable reality while helping humans with chores at home and at work.
It's a hand! Animated by a neural network, which is a thing that does processing at insect capabilities.
There is a whole (situated) robot to which it must be attached which doesn't exist. (cue Miles Bennett Dyson in the Cyberdyne vault)
There is much to do.
Consider AlphaGo, the program that beat 18 time world Go champion, Lee Sedol, in March of 2016. The program had no idea that it was playing a game, that people exist, or that there is two dimensional territory in the real world–it didn’t know that a real world exists. So AlphaGo was very different from Lee Sedol who is a living, breathing human who takes care of his existence in the world.
I remember seeing someone comment at the time that Lee Sedol was supported by a cup of coffee. And Alpha Go was supported by 200 human engineers. They got it processors in the cloud on which to run, managed software versions, fed AlphaGo the moves (Lee Sedol merely looked at the board with his own two eyes), played AlphaGo’s desired moves on the board, rebooted everything when necessary, and generally enabled AlphaGo to play at all. That is not a Super Intelligence, it is a super basket case.
We need more (unless you are doing task-oriented kill problems for the military for example):
Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution, Judea Pearl, 2018-01-15
Current machine learning systems operate, almost exclusively, in a statistical, or model-free mode,
which entails severe theoretical limits on their power and performance. Such systems cannot reason about interventions and retrospection and, therefore, cannot serve as the basis for strong AI. To achieve human level intelligence, learning machines need the guidance of a model of reality, similar to the ones used in causal inference tasks. To demonstrate the essential role of such models, I will present a summary of seven tasks which are beyond reach of current machine learning systems and which have been accomplished using the tools of causal modeling.
(Also get Judea Pearl's "The Book of Why", it's full of fun)