There's an entire genre of articles which argue that computers can never do X, because X is ill defined. Thing is, half of the time X is only ill defined because the writer neglects to define X well, and for the other half, that the writer can't define X well is no proof that it is impossible to define X well.

Here however, if the take the argument of representations in a technical sense, then since a neural network topology is just data we can fit along with the rest of the network, it's just wrong.

Or if we take a slightly more charitable interpretation, observing robots, from time to time they can get to really surprising solutions, so at least one would need to distinguish between a numerical algorithm finds a surprising solution and 'insight.'

Now, I actually don't want to be too hard on the article, I think it is genuinely interesting hodgepodge of facts about human cognition, I just think it should be rewritten without the computers will never do X thesis.