What is Artificial Intelligence?

Simon

"We're interested in machine learning algorithms where you don't need to necessarily be an expert in machine learning to interact," said Andrea Thomaz. She, together with her team of researchers, are working on robots that could be installed in our homes and don't need to be preprogrammed with a set of tasks.

Simon only has a "body" from the waist up and can pivot on the platform he rests on. Behind him is a bank of four computer monitors displaying various information about the robot's status. And in case something goes wrong with Simon, there's a large red button next to him to turn him off.

Thomaz said one of the biggest challenges in developing Simon was system integration. "We have Linux boxes, Macs, Windows PCs and basically any kind of machine, we're using it," she said. "We use OpenCV [Open Source Computer Vision] and lots of off-the-shelf things for speech recognition." She said that Simon does "blob detection," facial recognition and sound localization.

Click here to read more about Simon.

MERTZ

MERTZ is an active vision head robot, designed for exploring scalable learning in a social context. Inspired by how human infants learn by observing and imitating other people, the robot may learn to correlate objects and people with frequently uttered phoneme sequences, differentiate among people and their interaction habits, learn to dislike some people who tend to annoy the robot, etc.

Mertz is about 25cm tall and weighs around 2kg. It has a total of 13 degrees of freedom, including individually actuated eyebrows and lips, and has two cameras for vision and a microphone. One of the main issues involved concerning the learning capabilities of the robot is how to interact with while simultaneously learning from a person. Another problem was the ambient noise level of the robot’s surroundings.

Click here to read more about MERTZ.

Geminoid TMF Robot

Japanese researchers have developed a humanoid robot that can laugh and smile as it mimics a person's facial expressions. Geminoid TMF, smiled and furrowed its brow in almost concurrent mimicry of the woman, whose face was filmed with a video camera which then provided information on her expressions to the robot through electric signals.

The developers are hoping to have these in hospitals and the like in the not-too-distant future so they could be used in real-life situations. "We've already got some data showing that the robot gave patients psychological security by nodding and smiling at them, when patients were checked on by doctors," said Satoko Inoue, spokeswoman for Kokoro, one of the two companies involved in the development.

Copies of the robot are expected to be sold for about 10 million yen (110,000 dollars).

Click here to read more about Geminoid TMF.

Imperial student shows how neurotechnology works. (Credit: Image courtesy of Imperial College London)

Another novel and breakthrough device has been developed to help the physically disabled people play "pong" for the first time, without having to use the arms or the legs.

Pong is one game that really pushes a player to move in sync with the ball's movement. Although playing Pong as a video game won't need your body to move vigorously, but you still need to use your arms. But how about our physically disabled friends who cannot use both?

Well, that was the challenge taken by the students, from Imperial College London. The student researchers have used an open source game called 'Pong', where a player moves a virtual bat to strike a ball as it bounces around the screen using his own eye.

The game is played by wearing a special pair of glasses having an infrared light and a tiny webcam mounted on the glasses to record the movement of one eye.

The webcam is connected to a mobile device or laptop where a computer program synchronizes the player's eye movements to the game.

Click here to read more about Playing "Pong" using eye movements, Neurotechnology

Chris Harrison tried Skinput on his own palm.

A new technology revolutionizes the way we perceive and use input devices.

Skinput is the latest breakthrough in human-computer interaction. This technology was developed by Chris Harrison, a junior Ph.D. student in Carnegie Mellon University's Human-Computer Interaction Institute (HCII), in collaboration with Desney Tan and Dan Morris of Microsoft Research.

Chris Harrison, used the human skin as the primary input surface or touchpad for mobile devices such as your smart phone. Skinput is a combination of simple bio-acoustic sensors attached to the upper arm and some sophisticated machine learning through capturing sound generated by such actions as flicking or tapping fingers together, or tapping the forearm.

The armband design includes both the collection of sensors and a tiny projector that can superimpose multi-colored navigation buttons onto the bearer's forearm.

Moreover, a keypad can show on the palm of the hand. Simple mobile devices, like an MP3 player, might be controlled merely by tapping of fingertips, without need of superimposed buttons.

Also, Skinput can use "proprioception", a person's sense of body configuration - for eyes-free interaction.

Click here to read more about Skinput, Chris Harrison Skinput Device