What is Artificial Intelligence?

brain waves and heart rythyms are now used in biometrics to identify a person

Since the 9/11 incident, most American and European establishments have doubled their efforts in securing their establishments from identity thefts, which could be terrorists. This is very hard to accomplish, as most of these suspected "terrorists" use more sophisticated disguise technologies than the commercial biometrics technology presently used. The most common biometrics currently integrated in the security systems of most establishments nowadays are finger print analysis, face and voice and Iris scan analysis.

Although, it is sad to note, face, voice and finger biometrics can be faked. That is why scientists are continually seeking for ways to improve on the currently used biometrics. In Europe, researchers at HUMABIO, an EU-funded project, have combined biometrics' methodologies and the latest sensor technologies to capture brain patterns and use them to identify a person. Accordingly, brain patterns are unique for every person which make them impossible to be fraud.

typical EEG readings

In its early stage, the project had already developed the prototype headgear with two electrodes to read brain patterns. Using EEG and ECG technologies, HUMABIO will be able to extract the biometric profile of individuals, based on physiology and behavior characteristics. This information will be stored in a database and then compared to profiles created in real time, when individuals enter the secured area.

Click here to read more about Brain Waves Biometrics, HUMABIO, New Biometrics Systems.

This graphical figure shows the optimal solution by the VACCINE-AIS algorithm (PhysOrg.com)

One of the most difficult and challenging aspect of the human's physiology is the immune system. It is very complicated because it involves millions of cells and antibodies fighting against foreign microorganisms that evade the immune system every single second.

At Oklahoma State University, two researchers have worked together to build an artificial immune system that mimics the way the human body acquires immunity against diseases through vaccination. The AIS makes use of an algorithm VACCINE-AIS that identifies the best optimal solution from a given number of anti-bodies and antigens (weak or malfunctioning cells).

The core concept of AIS is boosting the immune system by injecting a vaccine that will stimulate the antibodies to quickly learn and locate weak or malfunctioning cells called the antigens. This process of location is called the optimization problem, the antibodies are the decision points in the immune system and the antigens are the solutions that the immune system are looking for.

An AIS application - AIS create or exhange antibodies to detect spam emails

Originally the AIS project was designed for data mining, anomaly detection and the like, however other research fields have shown interest in the AIS to use it for medical imaging (fMRI), power stabilizer and fault estimation, routing misbehavior detection and email spam filtering applications.

Click here to read more about Artificial Immune System and VACCINE-AIS algorithm.

This is Gordon, the robot operated exclusively by living rat brain neurons

It is somewhat very unlikely to see a robot operate autonomously without any artificial intelligent systems integrated in its circuitry. However, in the edge of our imagination, two researchers, Kevin Warwick and Ben Whalley from the University of Reading in UK, actually made a wheeled robot move using a rat's brain, nothing artificial.

About 300,000 neurons from a rat fetus' brain were extracted and cultured in a nutrient broth. Similarly, the neurons produced electrical impulses, and these electrical activity were then connected to an output device of the robot's sensor. During the actual experiment, it was proven that the neurons really made the robot move around an enclosed area. (see video)

The main purpose of this research is to understand how the brain functions given a specific stimulus and how the behavior of robots can differ using either a rat or a human brain . "By observing how the cultured neurons respond to stimulation could improve our understanding of neurological conditions such as epilepsy", Warwick said.

Upon completion of this experiment, the researchers will make a model out of human brain neurons to get a better understanding on the human brain-related diseases like alzheimer's.

Click here to read the full "Biological Brain (of a Rat) Controls a Wheeled Robot: A Breakthrough to Alzheimer's and Partkinson" story.

The two orange circles are exactly the same size; however, the one on the left seems smaller.

Optical or visual illusions have various effects of perception on the brain. A Scottish psychologist, Marty Doherty, suggests "that the brain’s capacity to consider the context of visual scenes, and not just focus on parts of scenes, develops slowly" that's why most kids have largely different perception over a visual illusion context.

In this particular study, Marty Doherty applied the famous Ebbinghaus illusion (sometimes called the "Titchener illusion"). Named for its discoverer, German psychologist Hermann Ebbinghaus (1850-1909) Ebbinghaus illusion consists of a circle surrounded in one image by smaller circles, and in another by larger circles. The viewer tends to perceive the circle surrounded by smaller circles as being larger than the circle in the other image, even though both are exactly the same size. The difference in size perception is due to the surrounding visual cues (larger or smaller surrounding circles), and the way the brain processes these visual cues.

Using the Ebbinghaus illusion, Doherty conducted various tests to 151 children, ages 4 to 10, recruited from a Scottish primary school and nursery school. Another 24 volunteers, ages 18 to 25, were college students. The participants were all provided with 1) Control Images, 2) Misleading Images and 3) Helpful Images.

Control images showed only two orange circles. Click here to see the image.

Misleading images showed the smaller orange circle surrounded by even smaller gray circles to boost its apparent size. Large gray circles surrounding the larger orange circle were intended to shrink its apparent size.

In helpful images, large gray circles surrounded the smaller orange circle to make it appear smaller than it actually was. Small circles surrounded the larger orange circle to magnify its apparent size.

Test results showed that for 4- to 6-year-olds, accuracy of size perception for misleading images remained at about what it was for control images. Misleading images increasingly elicited errors from older children and tricked adults most of the time. Adults made almost no errors on helpful images. Kids from age 7 to 10 erred on a minority of helpful images, while 4- to 6-year-olds performed no better than chance.

Neurogrid, a neuron-like computer chip consisting of millions of silicon neurons

The human brain is a powerful information processing system. It is composed of about 10 billion nerve cells, or neurons and each neuron is connected to other neurons through about 10,000 synapses. The brain's complex network of neurons forms a massively parallel information processing system as contrasted to conventional computers, in which a single processor executes a single series of instructions.

The brain's neural network is seemingly described as a 'chaos' because the communication patterns among neurons vary much according to specific situation. This 'chaos' creates electrical impulses which when simulated by a robot will require at least 10 megawatts to operate, the same amount of energy produced by a small hydroelectric plant.

However, a computer scientist from Stanford University, Kwabena Boahen, developed a neuron-like computer chips which will require only at least 20 watts, close to the actual human brain's energy consumption. This microchip which initially consisted one million silicon neurons is called Neurogrid, but can accommodate more of up to 64 million to simulate the brain of a mouse.

Boahen and the team of scientists developed neurogrid primarily to provide a solution in brain simulation with an efficient energy usage.

Click here to read the full story.