Calling simple statistical clustering algorithms that are tweaked by lots of trial-and-error heuristics "AI" feels like calling those slow two-wheeled electric self-balancing skateboards "hoverboards". Sometimes marketing can be too dramatic.
Trial and error is a main way that people learn and it works.
What is it, then?
In the 60s people used backpropagation to train neural networks. NN + BP is a very simple statistical clustering algorithm. I know that when I worked on neural networks in the 90s we still used backpropagation. Are they using something different now?
Yes, why else do you think we've had such breakthroughs in the past six years?
The two (NN and SAT solvers) share little theoretical progress (and certainly no theoretical breakthrough) in the past several decades, but SAT solvers aren't marketed as "AI" in spite of their seemingly magical abilities. I know that ML researchers usually cringe at the name AI and often try to disassociate themselves from the sci-fi term, but still, the marketing is extremely aggressive and misleading.
I realize that in every generation, marketers like associating the name "AI" with some particular class of algorithms, but it's important to understand that currently, assigning that name to this class of statistical clustering algorithms (regardless of their remarkable effectiveness in some tasks) is a stretch, just as it was when the term was assigned to other algorithms.
[1]: https://en.wikipedia.org/wiki/Backpropagation
[2]: https://en.wikipedia.org/wiki/Davis%E2%80%93Putnam_algorithm
I don't deny that it works, but it isn't AI (not that statistical clustering isn't possibly a foundation for AI -- we have no idea -- but the current state-of-the-art is a far cry from the sci-fi meaning of the term).
It is true that some algorithm has been called AI for decades. It wasn't always this one or anything similar to it. Both Lisp and Prolog were thought to be AI languages at one point.
[1]: https://en.wikipedia.org/wiki/Technological_singularity
The word AGI is pretty established. There are AGI conferences. I've heard it used by a wide variety of people, not just singularitarians. "Strong AI" is another common term.
I don't think there is much doubt at this point that neural networks are on the right path for AI. They are extremely general, have made remarkable progress in widely different AI domains, and are the closest AI approach to the human brain.
Not only is there doubt, I don't think any NN researcher would even dare to suggest (based on scientific knowledge; not as a mere conjecture) that neural networks, and certainly current NN algorithms, have anything to do with AGI, which, at this point, is still a dream or a sci-fi concept.
> They are extremely general, have made remarkable progress in widely different AI domains
They work precisely where statistical clustering works, because that's what they are. Statistical clustering is extremely effective.
> and are the closest AI approach to the human brain.
We don't know that. It is possible, even likely, that statistical learning plays some low-level role in the brain. We know little beyond that, but it is pretty certain that neurons in the brain work very differently from neural networks. I don't think anyone imagines that backpropagation is used by the brain.