After many many years, I'm still (slowly) reading GEB. That's because I'm wasting to much time reading the (whole) Internet to bother with printed books! Yet, I like to finish what I start (eventually) and yesterday I found a really interesting quote in that book. Mind you, it has been written thirty one years ago, at a time when personal computers were a novelty that only a few lucky ones could afford. Most computer usage (Punched Cards!) was being done in Universities laboratories and these machines weren't fast enough to do most of what we take for granted today.
Dogs, Garbage and Light Bulbs...
The world have changed a lot since then and computers are incredibly more useful now a day's. While discussing the Church-Turing thesis in chapter seventeen, Mr. Hofstadter goes on the representation of knowledge about the real world and say:
Because of the complexity of the world , it is hard to imagine a little pocket calculator that can answer questions put to it when you press a few buttons bearing labels such as "dog", "garbage", "light bulb", and so forth. In fact, so far it has proven to be extremely complicated to have a full-size high-speed computer answer questions about what appear to be rather simple subdomains of the real world.
Hard to imagine back then, but today it's quite commonplace to see people asking such questions to their smartphones. Which bring me to the point of this post, is the Web can be considered a form of artificial intelligence? I'd say no, it's just a hack, yet a pretty useful one. The raw data that can be found here isn't that different than the information that could be gathered in any other format. It is the search capabilities offered by various engines that truly makes the greatness of the World Wide Web. Still, these facilities aren't quite smart enough, we still have to choose carefully the wording of our queries and click around.
The Semantic Web
This is the next step, and a big one also. A lot of have been written on the subject, a lot of code too and thus far that concept hasn't yielded (easily) usable tools. I think that most problems concerning semantical representation of data are intrinsic to the nature of information. As Oleg once said: "Without a reader, a book has no meaning." It's all about asking the right question. And here is the missing link, does natural languages are good enough? Where's the real burden located, in formulating a query or in understanding it?