A significant part of artificial intelligence deals with autonomous planning or deliberation for systems which can perform mechanical actions such as moving a robot through some environment. This type of processing typically needs input data provided by a computer vision system, acting as a vision sensor and providing high-level information about the environment and the robot. Other parts which sometimes are described as belonging to artificial intelligence and which are used in relation to computer vision is pattern recognition and learning techniques. As a consequence, computer vision is sometimes seen as a part of the artificial intelligence field or the computer science field in general.
It's the capacity to self program if you like - a human can learn anything, just tell him about the subject. A program can not.
So, if an artificial information-sensing/learning program is not as strong at sensing information as the strongest information-sensing/learning machine that has ever existed - the human brain - then it cannot sense and learn information at any level? Wouldn't that be a strawman argument?
You seem to be claiming that if artificial intelligence does not exist at a human level, that it therefore does not exist at any level. Why are you arbitrarily selecting human-level general intelligence as the only intelligence that could possibly exist? Your line of reasoning seems to imply that human olfactory nodes (sub-processors which help humans sense, and learn, smells) do not represent any level of intelligence at all, since they are not at the level of current human general-intelligence.
Is a single-celled protozoan (e.g. ameba) intelligent? An invertebrate? A vertibrate? A lower-mammal? A non-human primate? Do you deny the possibility of biological evolution by natural-selection?
You seem to be claiming that if artificial intelligence does not exist at a human level, that it therefore does not exist at any level.
Right now it doesn't - not at any level. There are no AI's that can self-program. So it's hardly a strawman argument. There are some that can learn the specifics of pre-programed concepts, but none that can self learn a new concept. That is something that most animals can do, but computers are not even close.
Yes, human olfactory nodes do not have any intelligence at all - but not because "they are not at the level of current human general-intelligence", but because they can only do the single function they were created to do, and can not learn anything else.
There are lines in intelligence - it's not a continuum. The first line, to use your example, is being able to recognize any human face after being programmed with a sample of human faces. The second line is to be able to recognize the concept of face of a different species, i.e. the concept of the "front" of a creature.
AI has not even reached the second line.
A next major line (I'm sure there are others before that) is being able to learn to self-program. This means: use only the IO of the program, and using that teach it something new, without sending any commands that change it's programming. I don't think AI will ever reach this, even though animals can do it to some degree.
A further line is being able to create something new, not simply respond to requests. This does not mean a refinement of an existing technique, but something totally new. Not even all humans actually do this, it's in the realm of genius.
I skipped the line separating animals from humans. But it is a line, it's not a matter of degree - there is a jump from non-sapient to sapient.
Even the most retarded human is noticeably different from the smartest animal.
If you program it to recognize faces, it will not, on it's own, learn to recognize cows.
So, if you walked into a VC's office to pitch a startup, you might say with a straight face that you believe the market for cow recognition exceeds the market for human facial recognition? Do you realize that to serve the cow recognition market, we simply clip RFID tags to their ears? http://images.google.com/images?q=cow+ear+rfid+tag
The artificial-machine face-recognition market is fueling the development of special intelligence in that area. There is relatively quick-return money in that area, so that is an area where intelligence is being developed first. Smell-recognition is another area where development of special intelligence can pay off relatively quickly, and therefore is providing impetus for development. So far, there are at least these relatively-fast-payoff markets for which special intelligences are being developed:
The imaging studies revealed significant face-selective activity in brain regions known to make up the distributed cortical face-processing network in humans. Further study showed distinct patches of activity in a region known as the fusiform gyrus - the primary site of face-selective activity in humans - when chimps observed faces.
Do you deny that the modern human brain probably resulted from evolution by natural-selection, rather than from Intelligent Design?
This post totally confuses me. What does the market for VC funding have to do with AI?
Are we even talking about the same things? Are you an AI? You are sort of acting like one (in this post), not responding to the points, but picking nouns from my post and finding info about them. (I'm joking - sort of.)
"....for which special intelligences" - is your definition of intelligence different from mine? Because none of the items on your list are forms of intelligence.
Yes, I am aware of the "special sub-processor" for recognizing faces.
What does the market for VC funding have to do with AI?
Technologies develop where they can earn a reasonable return on investment. If AI is developing first as facial recognition, instead of cow or everything recognition, it's because that is where the money is, relative to the amount of investment required. The return on an everything recognition AI investment might be higher, but the investment required would be higher still, implying a poor ROI.
a human can learn anything, just tell him about the subject.
There has never been any evidence of any human not being able to learn a given subject or concept or rule, given ample time and resources to learn it? Have you heard of Piaget? http://en.wikipedia.org/wiki/Conservation_(psychology)
Preoperational children have an inability to conserve liquid volume. If you give a preoperational child a glass of milk in a tall, thin glass, they will think they have more milk than if it were in a short, fat glass. The child will focus only on the dimensions of the glass, not on the volume of the liquid inside. [...] this confusion [is] born from a pre-operational child’s inability to understand the notion of reversibility; the ability to see the reversal of a physical transformation as well as the transformation itself.
Then how do they learn, and recognize, faces? http://en.wikipedia.org/wiki/Computer_vision#Related_fields
A significant part of artificial intelligence deals with autonomous planning or deliberation for systems which can perform mechanical actions such as moving a robot through some environment. This type of processing typically needs input data provided by a computer vision system, acting as a vision sensor and providing high-level information about the environment and the robot. Other parts which sometimes are described as belonging to artificial intelligence and which are used in relation to computer vision is pattern recognition and learning techniques. As a consequence, computer vision is sometimes seen as a part of the artificial intelligence field or the computer science field in general.