The A.I. Revolution Is On

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.

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.

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.

And learning how to program will be the ultimate in AI.

For now, at least, computers can't do anything at all interesting or remarkable. They can, however, do boring things really really fast. And lots of boring things, done really really fast, can yield some pretty impressive results.

But it doesn't change the fact that what computers actually do is utterly trivial. Anything interesting they achieve is the result of algorithms programmed by very intelligent and sophisticated human beings.

That's a clear, qualitative difference from any real AI. When computers are creative, when they start doing things that haven't been done before, without the direct programming of any human, then a computer can truly be said to be "in control."

It's basically a philosophical question what you want to call that, but I'm okay with at least metaphorically calling that a situation where "the machine is in control", because in a sense it "knows" what it's doing and carries it out, whereas the human operators have only a vague sense of what it's doing, and sometimes have to engage in software archaeology to figure it out and change anything.

(But yes, I wouldn't say that an "AI" is in charge of anything.)

I expect we'll find one about the same time we find a true scotsman.

There is no way we can spit out cobolt programmers fast enough to handle the millions if not billions of machines handling critical tasks.

So in the sense that we can't just turn them off, computer are in control. But yes it is also out of control.

I found this article interesting and actually very well informed as such things go. It does not focus on Human like AI but practical approaches currently being used that are able to do the most basic type of learning at a complex level - ability to infer albeit on restricted spaces. For example, its 9 AM someone is at the door, given my past experience on situations like this (data) who is it most likely to be? I have a best guess based on what I have learned about who tends to come knocking when.

They can also pick out basic patterns whose details are very intricate, sometimes nuanced. What is interesting is that in these small spaces they can account for and infer on and recommend basic actions on vast number of parameters so accurately that they blow away any human attempt to match them to smitherings. This is why they are used as they are. Creativity, abstraction, self aware introspection,emotions, exploration for exploration's sake etc. are nice to think of as AI but that would be a waste of the type of niche intelligence computers are particularly well suited to based on their architecture. They do need to handle nuanced ambiguity better though. As well as transfering learning and dealing with situations far outside their training. The logic overflow of the 1960s movies is quite apt sometimes.

I do believe though that when (if) AI arrives it will be sudden as a unifying framework, a Standard Model of ML if you will is created. But in the mean time there is a lot of very interesting things going on and the combined explotion of introspection in the field (of Statistical Inference/Learning), data and processing power means very interesting times are ahead.

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  whatever