There is acknowledgement that early AI was overly ambitious, which is why AI has focused more on applications than trying to figure out how to write programs that were "really" intelligent since the AI winter. People like Ray Kurtzweil may still be flying the flag, but that's not what most people in AI are actually working on, and you don't see many working scientists making predictions about when or if it's going to happen. The problem is you hear a lot from the cheerleaders and very little from the experts, because "we found a slightly different way to recognize text in photographs, which works really well for extracting street addresses" doesn't make for sexy press releases.

The distinction between weak and strong AI is really about what you're trying to achieve. With weak AI we want programs that act like they're intelligent; we want to be able to make them smart enough for whatever application we have in mind. Strong AI wants to give you a holographic Lexa Doig. I am sure a large chunk of the AI community would not say no to a holographic Lexa Doig, but the problems you have some clue how to solve are much more attractive than the problems you don't. Skim the table of contents of some recent issues of AI magazine and see which you see more of.

For what it's worth, I'm in the "you might as well be arguing about whether is all, like, a simulation, like the matrix, man" camp.