>you do realize that NN/AI is totally state of the art for many tasks?

Being state of the art doesn't imply that these things will solve these problems. In ML terms, how do you know that NN/AI isn't a local maxima that we need to jump out of? All NLP systems are joke. Sure replace Watson with DL, might perform better on Jeopardy. But in real conversations? Forget it.

I wouldn't bet on these things. NN will win, but not the back propagation, ReLu, sigmoid or whatever pseudo science that is the current buzzword. There is 50 years worth of understanding in actual neuroscience and cognitive modelling that no one has paid attention to, and new design principles are emerging that will influence mathematics.

Because DL isn't great at NLP (and may never solve "real conversations" aka AGI), it's worthless?

It's the best performing tool we have for NLP, image recognition, etc. Is it a local maxima? Probably. But it's out there solving real problems nonetheless. We'll capture all the gains we can and then move on after.

"Being state of the art doesn't imply that these things will solve these problems. "

I suggest you are misinformed about the state of AI.

AI is currently ahead of all other approaches in many fields.

It's lead to quite a number of practical advances and breakthroughs.

The 'best examples' are those that I described, but there are many more.

Your comments indicate I think some ignorance on the issue - I think I see the point you are trying to make but I also submit that you're not aware of what AI is doing today.

'Self driving cars' would be impossible without AI today, for example. The vision systems depend on AI it's a breakthrough without which we simply wouldn't have the tech.

What if I don't care about general intelligence? Honestly it sounds more like a burden than a benefit. A local maxima might actually be exactly the type of solution that I need, especially in cases where no satisfying solution currently exists.