Way to go wired, an article with a bunch of references to things that are definitely not AI, would not have been considered AI (even in the dark gray past) and that are not considered AI today even by those that would like to believe that an 'AI revolution' is on.
According to this article AI is just another way of saying 'the leading edge in real world interaction', from inventory control to (apparently) crappy search results that still need further interpretation. (google 'what is the color of grass' for a nice example of AI in action, any three year old would tell you 'green' is the answer, not a bunch of links).
The 'AI winter' was not brought on by a lack of progress or interesting results, it was mostly brought on by it being used as buzz word hyping the notion of AI long before even baby steps had been made in the field, and this article fits right in with the over-selling of AI. An ABS system is AI? Please.
As of now we do not know if there will ever be something that we would call an AI but just like with pornography, I'll know it when I see it, and an inventory control system, no matter how clever it appears is not it, especially not if it took a bunch of programmers to write.
I think the one thing that will set a true AI off against the background of wanna-be AI systems is that a true AI can be taught by non programmers to reason about the world around it and draw meaningful conclusions without external input. We are still - in my opinion at least - very far away from anything that comes close to that.
Maybe their example sucked but Search engines fall into AI in my book.
I think the author is emphasizing the complexity behind very simple things. Obviously, it's not intelligent but it's doing way more than expected.
To me "intelligence" in software is about hiding complexity, making decisions and deducing things based on data, predicting and adapting based on input to deliver unforeseen results using a simple UI (where UI could be keywords in a search engine or a warehouse reorganizing itself to deliver and locate stuff faster based on new input/output).
The next generation of software is not about building actual intelligent systems. It's about accomplishing specific tasks and delivering more than expected.
Think of your IDE fixing your most common typos because it's constantly analyzing your input, or a file selection program that saves patterns/dependencies between your opened files and tries to guess which file you mean when you hit `gt` etc.
To me, this is smart behavior or _artificial_ intelligence. This is as far as software will ever get unless you start mixing it with biological stuff.
Diapers.com: Then, to fill an order, the first available robot simply finds the closest requested item. < That's AI.
Google: "what is the color of grass" is equated to "define:color of grass"
Web definitions for color of grass
a primary color between yellow and blue in the spectrum, like the color of grass
encarta.msn.com/dictionary_/green.html - Definition in context
So yea it's stupid AI, but they are both still AI.
PS: Decoding a natural language queries structure is considered AI. "1600 Pennsylvania Avenue" to a map location is more than just a search for web pages.
There is a joke that goes more or less that any sufficiently advanced AI is indistinguishable from 'just' statistics. But statistics (the unreasonable effectiveness of data) and the philosophy of probability are very profound topics that delve into the very fabric and nature of the universe. The same things keep appearing everywhere too. Bayesian networks and quantum mechanics. Entropy. Monte Carlo. So many.
I have a personal theory that we learn physical actions from statistical models more than modelling physical variables. Otherwise training how to do something as easy as a back flip (from a physics perspective) or flare would not be so hard.
Another problem is that nobody knows what the I part of AI is. So from the get go saying what AI is and isn't, is a failed experiment. I don't know what I is but i bet there are times you will know it when you see it and i won't. and vice versa. I also contend that modern systems do learn in a very basic sense. But I suspect we will also disagree on what learning is.
Yeah, I think this has to do more with systems and who controls them, than with AI per se. As far as classic writing on human/machine interaction goes, it's less about the stuff that AI pioneers like John McCarthy and Alan Newell were writing, and more about the stuff that Ted Nelson was writing in Computer Lib, about the dangers of people's lives being significantly structured by computers they didn't understand and didn't know how to control.
According to this article AI is just another way of saying 'the leading edge in real world interaction', from inventory control to (apparently) crappy search results that still need further interpretation. (google 'what is the color of grass' for a nice example of AI in action, any three year old would tell you 'green' is the answer, not a bunch of links).
The 'AI winter' was not brought on by a lack of progress or interesting results, it was mostly brought on by it being used as buzz word hyping the notion of AI long before even baby steps had been made in the field, and this article fits right in with the over-selling of AI. An ABS system is AI? Please.
As of now we do not know if there will ever be something that we would call an AI but just like with pornography, I'll know it when I see it, and an inventory control system, no matter how clever it appears is not it, especially not if it took a bunch of programmers to write.
I think the one thing that will set a true AI off against the background of wanna-be AI systems is that a true AI can be taught by non programmers to reason about the world around it and draw meaningful conclusions without external input. We are still - in my opinion at least - very far away from anything that comes close to that.
Learning is the key to AI, not programming.