Two researchers
from the Norwegian University of Science and Technology (NTNU) have made a
robot that learns like a young child. At least, that's the idea. The machine
starts with nothing -- it has to learn everything from scratch. The machine is
called ‘self’. It analyses sound through a system based on the human ear, and
learns to recognize images using a digital model of how nerve cells in the
brain handle sensory impressions. It is designed to learn entirely from sensory
input with no pre-defined knowledge database, so that its learning process will
resemble that of a human child in early life. In the beginning, the robot knew
nothing. It 'hears' sounds from a person speaking, and can connect these to a
simultaneous video feed of the speaker. The robot picks a sound that the person
appears to be emphasizing, and responds by playing other sounds that it
associates with this, while projecting a neural representation of its
association between the sound and pictures.
It doesn't show
a video, but rather how its 'brain' connects sounds and images. The robot
gradually absorbed more and more impressions of different people. Certain
people, like guides, affected it more, because it 'saw' them often. The robot
also learned to filter input. If a word is said in a certain way five times,
and then in a different way once, it learned to filter away the standout and
concentrate on the most common way, which is presumably correct. This
processing happens during the robot's downtime. After a while, the robot was
able to connect words and pictures together in a more complex manner, you could
say that it associates sounds with images and connects them by itself. The
robot is constantly under development, and the result is a robot that shows how
it makes associations in a very pedagogical manner. It doesn't resemble any
living organisms on purpose -- you're supposed to concentrate on its learning
and the process behind it.
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