What is Artificial Intelligence?

Left brain after the first trial; Right brain after 10 minutes of practice controlling movement of cursor through imagination

The human brain signals has been a subject of curiosity and exploration. And in a recent study, it showed that by just thinking about controlling the movement of a computer cursor, brain neurons populate to make it happen in real life.

As published in Proceedings of the National Academy of Sciences, scientists from the University of Washington observed the brain signals in its surface while using imagination to control the movements of computer cursor. The activity was proven with the brain-computer interface connecting the brain through tiny electrodes.

The team of experts studied eight patients awaiting surgery for epilepsy at two hospitals in Seattle. They were placed with electrodes connected to their brains' surface during the week of observation prior to the scheduled surgery.

They asked these patients to imagine moving their arms while brain activities were recorded. Then, they asked the patients to imagine moving a computer cursor towards a target object in the computer screen. And after just 10 minutes of doing so, they actually enjoyed controlling the movement of the computer cursor like it was something they do physically.

Now, this findings also provide marks on which brain signals to tap to aid in the treatment of brain-related diseases like epilepsy.

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Flame, the first ever walking robot to imitate humans

A new robot named Flame was developed by Daan Hobbelen, a PhD student at TU Delft in the Netherlands.

This robot is based on the principles of human walking and this is considered to be most advance robot in its kind. Flame can cope to achieve great stability while remaining energy efficient.

In the two groups of walking robot, Flame is categorized in the second group which is designed to imitate human walking in the sense that the robot is executing a controlled fall forward. This type of robot is not very energy consuming and is not that costly.

Flame is 1.3 m in height and is about 15 kg. It has seven motors. It does not fall and can manage to stay stable because of “organ balance” and a sequence of algorithms which calculate where and how far apart the robot’s ‘feet’ should be placed.

The upper body of Flame has PC104 computer which has a real-time Linux kernel (RTAI) running a control loop and can implement torque and/or position control on all actuated joints.

According to Hobbelen, Flame is the first walking robot with electric actuation. This research might further the development of treatment and diagnosis for people who have difficulty in walking.

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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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Matt Bunting, student with his very own Hexapod

"One of the things I wanted to explore was the idea of reinforcement learning using an artificial intelligence... I wanted it to figure out how to walk straight forward on its (hexapod) own”, said Matt Bunting, a senior at the University of Arizona in electrical engineering.

Hexapod was Bunting's final class project on cognitive robotics. Built from spare parts, and to let the robot adaptively learn how to move he used an Intel Atom processor powering an Ubuntu OS computer. With Logitech Quick Cam to watches what happens when movements are initiated, and a changing scene to determine what effect the movements are having.

Intel ordered themselves two copies to take on an international publicity tour for the Atom processor. A couple days after Matt posted a video of his bot on YouTube, Then, the company who provided Matt with the servos, Crust Crawler Robotics, asked Matt to help develop a software for some of their hexapod kits.

Matt's hexapod Artificial intelligence learning can be applied to tasks other than wait, it can relearn how to walk. The robot even has foot contact sensors that can be used for terrain adaptation.

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Stanford computer scientists say that, with the diverse rules of every game in computers, they are the ideal tools for exploring ideas in artificial intelligence and fresh approaches to programming.

As Michael Genesereth, computer science professor with the Stanford Logic Group, and Nathaniel Love, a computer science doctoral student, in an article on general game playing (GGP), wrote that: "Programs that think better should be able to win more games.”

He added that, the theorem of general game playing is “drastically different” from the past creation of computer programming.

He said that, “the computer just follows a recipe that has been given to it.” AI’s application is limited to this situation because computer never needs to think for itself. According to him, program like IBM’s Deep Blue shows the smarts of the programmer rather than the smarts of the program. Writing program for GGP is similar as trying to educate a child the way how to play a game.

Genesereth said that competitions between GGP programs are an "evaluation technique for intelligent systems.” And, it is feasible to compare the relative intelligence of its system by playing the programs against one another.

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