For all the points I raised, I still think that truely intelligent machines are possible. I just don't think I'll see them in my lifetime or that the current computer architectures/programming paradigms can support them. That doesn't mean there shouldn't be research. A lot of people in the field focus on hardware and reasoning algorithms--not as many focus on how to represent, organize, and associate information (the CYC program is one notable exception)--which is key. I also think there is much promise in using the WWW as a starting point for AI research.
Developing AI is (perhaps) the hardest research problem ever--by several orders of magnitude. When you think about it, it all about people figuring out how they are wired and how to replicate their own archaic programming.
Because of the above, progress will be very slow and lots of $$ will be wasted on dead ends--but that is the nature of research. Unfortunately, you don't know what will work apriori. Also, unfortunately, the field attract a lot of charatans, probably because no one expects really a lot of success.
"Developing AI is (perhaps) the hardest research problem ever--by several orders of magnitude. When you think about it, it all about people figuring out how they are wired and how to replicate their own archaic programming."
It took approx. 50 years to solve the chess problem. Others will be harder.
The problem is that computers have no sensory context with which to understand the symbols being fed in. CYC is no exception. All they and the rest are doing is taking meaningless abstract symbols and munging them into other meaningless abstract symbols. The sensory context to gain meaning from the gibberish must come from the machine interacting with the world, not a machine being spoon-fed symbols.