They did not.
They showed that for certain problems one could not do more than figure out some invariant and scaling laws. Showing what is impossible is not failure.
For the rest: Modern gene networks and lots of biological modelling is based on their work as well as quite a few other things. That’s also not failure.
I agree that modern AI is alchemy.
When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong.
Also see Minsky's "Perceptrons"
The problem with almost all such proofs is that people (even those who know better) read them as "this can't be done" when in fact they tell you "it can't be done unless you break one of the following assumptions."
I agree that it's unfair to say they failed, but it's likewise unfair to say that their success was in telling us our limits rather than exploring what we need to do to get around the roadblocks.
No matter what you do you are bound by that. As soon as you uncertainties become of the order of the systems scale you cannot predict.
You might push from 1 lyapunov time to 3 or use ensemble methods to get probabilities, but the fundamental impossibility remains.
Age of the scientist does not matter.
Though I think it's fair to say that the torch was picked up and carried by others with a different set of strategies.