Whatever Happened To AI? 472
stinkymountain writes to tell us NetworkWorld's James Gaskin has an interesting take on Artificial Intelligence research and how the term AI is diverging from the actual implementation. "If you define artificial intelligence as self-aware, self-learning, mobile systems, then artificial intelligence has been a huge disappointment. On the other hand, every time you search the Web, get a movie recommendation from NetFlix, or speak to a telephone voice recognition system, tools developed chasing the great promise of intelligent machines do the work."
a good quote (Score:5, Informative)
The question of whether a computer can think is no more interesting than the question of whether a submarine can swim. ~Edsger Dijkstra
Also, for understanding recommendation systems and pattern recognition in volumes of data, I found Collective Intelligence [oreilly.com] to be a great resource.
Difference: Machine Learning vs. AI (Score:5, Informative)
As a Machine Learning Scientist, I see a distinct difference between the two fields, although they overlap significantly. They have similar roots, techniques and approaches.
I usually describe Machine Learning as a branch of computer science that is similar to AI, but less ambitious. True AI is concerned with getting computers to become sentient and self-aware. Machine Learning however, seeks to simply mimic human behavior, just to recognize patterns and make decisions, but not become sentient.
Additionally, Machine Learning often concentrates on one problem (OCR, internet search, etc.) rather than a truly self-aware entity that has to deal with a variety of tasks.
At least that's how I describe my field to people not familiar with it. They've usually heard of AI, so it's a good stepping stone to helping them understand what I do.
A lot of the tasks mentioned in the summary fall into the niche Machine Learning, and it's sibling Data Mining are currently addressing.
Anyway, just my $0.02.
Few are working on the grand integration (Score:3, Informative)
What strikes me is that no researchers are really putting together a multiplicity of AI techniques to produce a generally intelligent "human analogue" or "smart and lippy assistant".
Instead, the researchers are going to the nth degree of detail on a very specialized aspect, like some variant of bayesian inference that is optimal under these very particular circumstances,
etc.
I don't know of any AI research other than Marvin Minsky who is even interested in or advocating a grand synthesis of current techniques to produce a first cut of general intelligence.
That being said, probably there are two (related) exceptions:
1. I think some fascinating AI stuff must be going on at Google. They have the motherlode of associative data to work with. They are sifting all of human knowledge, news, interest, and opinion that anyone bothers to put on the net.
They must be trying to figure out how to make algorithms take advantage of the general patterns in this data to start giving people info-concierge
type of functionality. Pro-active information gethering, organization, prioritization in support of the users' activities, which have been inferred by google-spying on their pattern of computer use and other peoples' average patterns.
2. I think there is some pretty squirrelly stuff
happening on behalf of the department of homeland security, though. Stuff that probably combs all signals intelligence including the whole Internet, and tries to impute motives and then detect very weak correlations that might be consistent with those motives.
Um.... no? (Score:3, Informative)
It's not that AI has been abandoned, it's just that the definition is a bit of a moving goalpost. We're still learning on how exactly intelligence and consciousness work. Every once and awhile you hear about parts of the human brain being simulated in supercomputers.
Not even that. (Score:5, Informative)
Amazon SUCKS at recommending anything for me.
You have recently purchased a just released DVD. Here are other just released DVD's that you might be interested in. Based only upon the facts that they are:
#1. DVD's
#2. New releases
Or, you have recently purchased two items by Terry Pratchett. Here are other items you might be interested in based upon the facts:
#1. They are items
#2. The word "Pratchett" appears somewhere in the description.
You would THINK that they'd be "intelligent" enough to factor in your REJECTIONS as well as your purchases (and what you've identified as items you already own).
Figure it out! I do NOT buy derivative works. No books about writers who wrote biographies about Pratchett.
AI bots becoming more prevalent (Score:4, Informative)
Re:Few are working on the grand integration (Score:2, Informative)
Re:I thought sigularity was right around the corne (Score:3, Informative)
Who says the Singularity is reliant on ARTIFICIAL Intelligence?
AUGMENTED Intelligence [wikipedia.org] is actually within our grasp: for example, look at the number of people who know how to Google / Wiki [xkcd.com] any information they don't know to get caught up with whatever subject is at hand? "Well, Damn, don't know much about RAID, better Wiki it... oh, I get it!"
How long until we figure out how to make pills to make people think faster, or remember better? [newscientist.com]
How long until we get PDAs in the form of sunglasses [igargoyle.com] that will allow you to automatically get the definition of words as you hear / read them?
Or Contact Lense-displays [eurekalert.org] that connect to a PDA that you control using your brain? [contractoruk.com]
The Singularity is not going to be an all at once WHAMMO thing, we're not going to wake up with benevolent robotic overlords announcing that the Rapture of the Geeks is at hand. It will be gradual, and those of us on the techy side will likely not even notice it.
Computers will get faster, and as we learn how to augment ourselves, we will to. Eventually we'll be able to communicate with a PC/PDA directly. Meanwhile, things like RepRap [reprap.org] will change our world in ways we're not quite ready for. (For example, I have no dobut that a functional RepRap would be a beautiful, amazing thing in the hands of Slashdot or the OSS Community. At the same time, the idea of 4Chan getting ahold of one fills me with Dread.)
Re:They keep changing the definition (Score:2, Informative)
Strong AI is alive and well (Score:1, Informative)
Strong AI, aka Neural Networks are alive and well. It's what's powering all OCR(Object Character Recognition), Voice Recognition, Hand-writing recognition, Facial Recognition, etc. The problem as you mentioned is one of scale. We can simulate dozens, even hundreds of nodes in a neural network, but this hardly compares to the billions of brain cells we have working in parallel. Human intelligence fundamentally involves human senses (input) processed through billions of neurons (nodes in your network) to produce action and thought. We won't see anything approaching human intelligence until we can achieve similar scale which I actually don't see as being that far away. As for the so called billions of years of built in programming you mention, that's just crazy talk. We have flexible neural mechanisms for assimilating and organizing information at birth, but without input we would remain deaf dumb and blind. They've done plenty of experiments on sensory deprivation and it's effect on brain developement in rats and we've seen smooth brain phenomena in humans as well to illustrate this.
Re:Strong AI is alive and well (Score:3, Informative)
Strong AI isn't aka Neural Networks. Strong AI is AI that matches or exceeds human intelligence [wikipedia.org]. I probably could have worded my statement better, as strong AI research is not really dead, but the overwhelming majority of AI research is focused on specific weak AI problems. These solutions may very well create strong AI when combined, but that isn't the focus of the serious research, and even neural networks are just one more solution to the many weak AI problems out there.
Regardless, my point is that it took billions of years not to condition responses to inputs, but to build a biological machine that is capable of receiving inputs, processing those inputs, and outputting a response, then recursively evaluating and processing the results. It also needs to self replicate.
My main point though is in agreement with yours- the problem isn't one of technology or advancing algorithms, it's one of scale.