What is Artificial Intelligence?

The left brain indicates a normal state while the right brain indicates general intelligence correlated to IQ scores.

Recently, a study about mapping the human brain has been published in the the early edition of the Proceedings of the National Academy of Sciences.

A team of neuro-scientists from the California Institute of Technology (Caltech), the University of Iowa, the University of Southern California (USC), and the Autonomous University of Madrid collaborate to have successfully mapped the brain to measure general intelligence.

According to Ralph Adolphs, one of the authors, "general intelligence is also referred to as the Spearman's g-factor" but the underlying concepts are quite vague.

Using brain imaging techniques, the team examined a uniquely wide range of data set of 241 brain-lesion patients who all took the IQ tests.

Then, the scientists mapped the area of each patient's lesion in their brains, and correlated them with the patient's IQ score to produce a map of the brain regions that affect general intelligence.

During the examinations, the researchers were amazed to find out that, instead of living in a single structure, general intelligence is distinguished by a network of regions across both sides of the brain.

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Scientists from the Max Planck Institute for Biological Cybernetics discovered that we are able to classify an expression much better when it moves naturally.

Scientists from the Max Planck Institute for Biological Cybernetics in Tübingen, Germany learned that we can recognize facial expressions better when it is moving naturally rather than when it is in a static photograph.

There are many explanations for each facial expression. A frown may say: “Please explain that again!". A nod may signify that you understand.

We must see the expression moving for at least 100 milliseconds in order for us to gain the advantage of dynamic information. Our brain is less capable of decoding the facial motion if the video sequence is shorter.

There are series of experiments that these scientists do in order for them to prove their theories. The result of the experiment shows that either pictures or motion alone are what is needed, but it’s the combination of the temporal sequence and the right facial motion to consistently interpret facial expressions.

Dr. Christian Wallraven, co-author of the study said, "Our results also have implications for the area of computer animation, since its goal is to create artificial avatars and facial animations that are able to communicate realistically and believably."

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An example of a process in artificial intelligent system

An Artificial Intelligent System was first known as an expert system some 3000 years ago. It evolved into sophistication and the use of complicated algorithms in order to ultimately respond and learn from their masters.

A concept of machine communication was introduced by Alan Turing, known as the universal Turing machine that mimics other computing machine. The concept was largely accepted and became the basis for the development of an artificial intelligent system that we now see and use these days.

So how does an artificial intelligent system works?

Let us take for example an artificial intelligent robot.

The artificial intelligent system embedded in the robot's brain takes advantage of sensors integrated in cameras or laser devices. The sensors feed information to the robot's brain. Then, the brain checks for any historical data. If there's none, it creates a composite concept to form part of its memory.

Then the brain builds up the present situation from these concepts. Again, the brain checks for any existing response rule in the memory that is appropriate for this situation. It the picks up one of the matched response rules and sends the action part, to the limbs.

At the start, the robots memory is empty of concepts and response rules. But every time the robot "learns" a new set of response rule containing the present situation, the specific action performed and if it was useful for the objectives set for its actions.

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WeCU

WeCU Technologies is creating a system that would essentially turn the public spaces in airports into vast screening grounds a mind-reading scanner that can tell if a given traveler is a potential danger.

The system projects image onto airport screens or some other image such as symbols associated with a certain terrorist group to familiar images that suddenly appear in unfamiliar places. If you strolled through an airport and saw a picture of your mother, the logic is that people can't help reacting, even if only subtly.

“And a circular screen which ought to have been a calm turquoise blue on the wall behind him. But which was flickering from dark blue through violet to mauve. That was simple nervous tension and guilt and anger at the humiliation of being subjected to "veridicator" interrogation.

There was a bright conical helmet on his head, and electrodes had been clamped to various portions of his anatomy which was designed to extract information more efficiently than conventional interrogation methods. "The chair" is employed throughout the Peacekeeper military is believed one of the most effective means of gaining information from unwilling subjects.

It is designed to sort through and uncover the mind's "layers".

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A hypothetical question was raised during a forum on robot morality "can a machine be programmed to act or decide morally, as much as humans?"

In a recent paper published in the International Journal of Reasoning-based Intelligent Systems, the authors Luís Moniz Pereira of the Universidade Nova de Lisboa, in Portugal and Ari Saptawijaya of the Universitas Indonesia, described a method for computers to calculate the future consequences of hypothetical moral judgments.

The paper, Modelling Morality with Prospective Logic, made particular mention "that morality is no longer the exclusive realm of human philosophers".

They've proven their findings by creating models of moral dilemmas inherent in a specific problem called "the trolley problem" and in creating a computer system that delivers moral judgments that conform to human results.

They have cited scenarios that build their theories around the "trolley problem".

And based of these typical scenarios where moral judgments are drawn, the authors claimed that they have been successful in modeling these difficult moral problems in computer logic by resolving the "hidden rules" that people use in making moral judgments and then modeling them for the computer using prospective logic programs.

Click here to read more about Robots Make Moral Judgments, "The Trolley Problem"