For your question, &quot;would a robot need to relearn a skill if a part like the arm changes shape&quot;, for the currently commonly used style of machine learning which is also implied by the article - deep convoluted neural networks - the situation is that it would need <i>some</i> relearning&#x2F;retraining but it would be much smaller than starting from scratch.<p>When you need to train a system for problem X that limited data available, a possible approach is to train a system on some related problem Y where the data is plentiful, and then use that network (with e.g. the final layer removed) as input for a smallish network that solves the problem you need, but piggybacks on all the patterns discovered by the original network.<p>In a similar manner, if you had a system that works on one style of arms, then it would be usable training a (much smaller) neural network that &quot;converts&quot; from that system to outputs of another style of arms.