Artificial Palms

A preface to the understanding of Artificial Intelligence

I
f we compare our lifestyle and needs of the day with no more than 50 years ago, then one conclusion is obvious that we evolved not only in terms of knowledge, but also in the position requirements, needs and dependence on external entities.
In summary it can be said that as the domain of our knowledge extended also changed the scale of our dependence on the external entities, and the COP with this dynamic world of knowledge of the tools to help came to be called "computers."
There is something very interesting related to computers.
Before the 1920s, computers were human workers who perform calculations. They were usually under the direction of a physicist. Many thousands of computers were employed in commerce, government and research center. Most of these computers were women and that a title is known that in the calculation. Some performed astronomical calculations for calendars [1].
It gives us an idea of Artificial Intelligence. Key is, most of the jobs man was associated with, now the machines are given the responsibility to perform, because the machines can work on those things without effort. And he said that if knowledge is power after autopilot is an amplifier of this power. But now we see that this domain of knowledge is changing and to know the definition of knowledge about computer is spent to perform some actions without thinking for reasoning and thinking and in this sense, I am afraid I am not computer is an amplifier very good, yet.
If our wider domain of a computer system to the machines around us then again that is not natural or unusual man Nature has always manipulated to suit your needs and the development of these all mechanics around us is a good piece of confirmation. The man maneuver nature simply the power of curiosity that is inherited by a child. When he opens his eyes, begins to hear voices, etc. You should have seen this phenomenon.
Computers can do many amazing things that are in the domain of computing, but now the man has his limits again pushed and challenged in their efforts to nature exploration.
For Aristotle, the most fascinating aspect of nature was change. In his Physics, defined his "philosophy of nature" as the study of changing things. "[2]
Although there is no standard definition of artificial intelligence and many experts have suggested different definitions connected with their work on it.
We can say that artificial intelligence is the study of intelligence that can be generated in the entities that do not inherit. Although a defined by a student as not only the answer.
Intelligence is something like fire, is thought of a divine gift randomly delivered in the form of rays, forest fires burning lava. European peasants would insert a wooden wheel in the round hole and turn it tightly between your palms to produce fire, Ancient Greeks used lenses or concave mirrors to concentrate the sun's rays and burning glasses have been used by the Aztecs of Mexico and China. Same is the case with intelligence, playing chess and theorem-proof was thought to be subject to intelligence, but intelligent computers can now beat their teachers to play chess, and may even have tremendous achievements in the championships of chess master level. However, man's quest is to put intelligence cage iron machines and steel.

A formal definition of AI given by Elaine:
"Artificial Intelligence is the study of how to make computers do things in which, for the moment, people are better. "[3]

So it is now clear that artificial intelligence is not the study to make efficient computers that can perform, but it is a study of how to empower computers to do things that at this point computer class people.
Computers are better than people in the numerical computation, information storage, repetitive operation which is now the core area of Artificial Intelligence is, intelligent behavior, even an ordinary person can perform better than a super computer. Dr. Seuss in his book writes that even the most super supercomputer lacks the reasoning capacity of a child absorbed. [4]
We do much more than just process information we understand. We make sense of what we see and hear, use common sense to make our way through a world that sometimes seems very logical. [5]
So now our search more effective, but there is still a long way to go to reach our destination. Before you know what intelligence is? As most of us do not or probably almost all us.
But for the sake of the abstract idea about the intelligence of any list I have feature for an intelligence system, these features are suggested by Douglas Hofstadter in a list of "essential skills for intelligence. He said that for an intelligent system you need:
· "To answer to very flexible. "
· "To make sense of ambiguous or contradictory messages"
· "To recognize the relative importance of different elements of a situation. "
· "To find similarities between situations despite differences that may separate them."
· "To make distinctions between situations despite similarities that may link them." [6]

Math can describe in great detail technique for multiplying two numbers, since you can describe in intricate detail, team carries out easily. On the other hand, if an activity is so naturally to you that you do not have to think about it at all, you can have great difficulty describing exactly how. What do you have for dinner last night?
Now, can you list the mental steps that happened to remember what you ate? [7]
And learning is definitely needed to be intelligent. But when our computers are used to predefined instructions, when the team already gave what to do, how and when to do it, then it is learning. I do not think so. Learning is basically the reasoning and analysis and new short chain of processed information to our database of knowledge and concluded. Although it is a great concern how this knowledge they need to be represented in the computer system so that it can be retrieved for intelligent actions. A of proposed actions taken by the researchers are using Artificial Neural Networks. They are very similar to the human brain and the activities taking place in it. And very interesting new thing that is good but his team "know" a lot of things but that's what we know. What team knows what he knows?
Another concern why could imitate human intelligence, when we all know that people do things exactly or optimal. Well, the main reason for this is what we want our teams to carry out activities acceptable enough to not require them to be intelligent and excellent at the same time although it is desirable, but only to start is not necessary. And to serve our energies to make optimal and intelligent computers, scientists are working on how to avoid stupidities artificial. "
The following are the fields of research, some of Artificial Intelligence by John McCarthy [8]:

Logical AI
What knows a program on the wider world the facts of the specific situation in which to act, and its objectives are represented all sentences of a logical-mathematical language.

Search
IA programs are examined often a large number of possibilities, for example, moves in a chess game or inferences by a demonstration program theorem. The discoveries are continually made about how to do this more efficient in several areas.

Pattern recognition
When a program makes observations of some kind, it is often programmed to compare what he sees with a pattern. For example, a vision program may try to match a pattern the eyes and nose in a scene to find a face. More complex patterns, for example, in a natural language text in a chess position, or history an event has been studied. These more complex patterns require very different methods than simple patterns have been studied more

Representation
Data on the world should be represented in some way. Usually languages of mathematical logic are used.

Inference
Some facts, others can be inferred. mathematical logical deduction is adequate for some purposes, but new methods of non-monotonic inference have been added to the logic from the 1970s.

common sense knowledge and reasoning
This is the area in which AI is farthest from the human level, at Despite the fact that it has been an area of active research since the 1950s. While considerable progress has been made, for example, in the development of reasoning systems non-monotonic and theories of action, more new ideas are needed.

Learning from experience
Programs to do that. AI approaches based on connectionism and neural networks specialize in that. There is also learning the laws expressed in logic.

Planning
Planning programs start with general data about the world (especially data on the effects of actions), data on the particular situation and a statement of a goal. From of these, create a strategy for achieving the objective. In the most common, strategy is just a sequence of actions.

Epistemology
This is A study of the types of knowledge that are needed to solve world problems.

Ontology
Ontology is the study of the types of things exist. In IA, programs and phrases dealing with different types of objects, and study what these are and what their basic properties are. The emphasis on ontology began in the 1990s.

Heuristics
A heuristic is a way of trying to discover something or an idea embedded in a program. The term is used variously in AI. heuristic approaches are used in some of the search to measure how far a node in a search tree seems to be a target.

Genetic Programming
Genetic programming is a technique for programs to solve a task by mating random Lisp programs and select the fittest in millions of generations.

At this point we can say that this area is evolving and is still much more to do there. Currently, we have many questions, but only some of them are answered. But being a scientist not afraid to ask because the question is the key to unlock the secrets of nature.
I hope this preliminary introduction will give you a better understanding about this field and its interests.

"When the only tool you have is a hammer, every problem they encounter trends to look like a nail ";
(Source - Unknown)

References:
1. wikipedia / History of computing.
2. Artificial Intelligence, 3rd edition. By George F. William A. Luger and Stubblefield, page No. 65.
3. Understanding Intelligence Henery C Mishkoff artificial ..
4. Herald Net. Published: Sunday, January 30, 2005. The equation of avian influenza.
5. Understanding Artificial Intelligence by Henery C Mishkoff.
6. An Eternal Golden Braid by Douglas Hofstadter. New York, vintage 1980, Page N º 6.
7. Understanding Artificial Intelligence by Henery C Mishkoff.
8. www-formal.stanford.edu/jmc/whatisai/whatisai.html

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