You don't know how many times I have heard a student claim that they have made some type of major advance. But on inspection it usually comes down to something that requires exhaustive search.
I think that there is definitely a place for new ideas in the field, but I don't think they will come from complete novices. I think they will come from those who have CRITICALLY read the basic literature. And probably from those who have read more than just the basics too.
My own pet peeve on the field now is the over emphasis on asymptotic complexity. Sure its important, but its not exactly an AI result. The scruffies need to make a come back and start coding! See my own meager efforts (http://www.anaphoric.com)
Intelligence is about finding algorithms for successful survival within a given environment. It's some sort of a meta-algorithm, although I have no idea if it's simple or not, but we can be sure it does exist.
Sorry for repeating myself (comment lost in this huge thread), but I think it's the definition of intelligence we should look for first. Once we have a clear and unambiguous definition of intelligence, only and only after that we may be able to think about implementation. And I'm sure implementation would be straightforward once we know what we are trying to achieve.
It's actually amazing if not ridiculous that researchers always start from the other end of a cigar: they raise ideas, one after another, but they don't even try to explain what problem exactly they are solving.
If we all took that attitude, we'd never get anything done.
The process of discovery is hands-on, learning by doing. You don't know all the rules at the outset, or all the definitions, or even know what you don't know. You find out as you go along. Thus it has been for every great invention from sex to agriculture to post-it notes to landing a man on the Moon and back to on-demand porn.
The real requirement is that we have some way to test it; that we can do, e.g. by conversation. To cop an example from quantum mechanics (which I know nothing about), we don't have to understand why it is like that in order to make predictions with it.
We don't need a clear and unambiguous definition of intelligence in order to tell that other human beings are intelligent. Likewise, we don't need one in order to start trying to create an artifice that impresses us into thinking it also is intelligent.
We don't need a clear and unambiguous definition of intelligence in order to tell that other human beings are intelligent.
The problem here is that not every human being is intelligent and yes, we are actually trying to define intelligence through IQ tests, for example.
Likewise, we don't need one in order to start trying to create an artifice that impresses us into thinking it also is intelligent.
So when you need accounting software you say: "write me something that will be as clever as my accountant". Is that the way you formulate tasks for software engineers?
> we are actually trying to define intelligence through IQ tests, for example
Fail. IQ tests only measure how well you do on IQ tests.
> The problem here is that not every human being is intelligent
Unless they're in a vegetative state, they are more intelligent than any artificial system, so far.
> Is that the way you formulate tasks for software engineers?
The only way to make a specification so precise that it does exactly what you want is to implement it, and then the code itself becomes the specification.
So, what you mean by saying something is more intelligent than something else? What criteria are you using to evaluate that?
And yes, it's the way programming works - when you know what you are trying to achieve. Software is about input and output and unless they are deterministic, you can't write code.
It simply does not exist yet. There were no good airplanes before Orville and Wilbur showed up on the scene. I hope there will be some breakthroughs soon, but scientific discoveries can't be planned/scheduled, so who knows how long it'll be...
SHRDLU is nothing more than a really well-done ELIZA for a really small domain.
It's one thing to notice that beginners can sometimes make contributions by luck, just by not knowing how hard something is supposed to be. It's another to use this reasoning to glorify lack of knowledge.
Whenever I see someone succeed rapidly I assume it isn't a newcomer, that there are depths of effort I cannot yet see.
Many, many people have gone into the field to study the traditional techniques, and glorifying this knowledge has not led to AI.
I don't think a beginner is going to create AI by "luck". But a beginner's mind is not cluttered in the same way as an expert's. This may be what it takes to get working AI.
Expert knowledge is appropriate when discussing proven solutions. AI is speculative at this point.
