Friday, August 21, 2009

This dinner

This dinner-napkin sketch of neural nets may sound relatively simple, but in practice, these artificial brains can perform some astoundingly complex logic. In fact, Ayanna calls neural nets a "black-box technology" -- in other words, what happens between the input layer and the output layer is often so difficult to decipher that scientists just treat it as a "black box" that somehow converts inputs into outputs.
By combining these two technologies, Ayanna and her colleagues at JPL hope to create a robot "brain" that can learn on its own how to expertly traverse the alien terrains of other planets.
Such a brainy 'bot might sound more like the science fiction fantasies of children's comics than a real NASA project, but Ayanna thinks the sci-fi flavour of the project contributes to its importance for space exploration.
Ayanna -- who wanted to be television's "Bionic Woman" when she was young, and later decided she wanted to try to build her instead -- says she believes that the flights of imagination common in childhood translate into adult scientific achievement.


To do this, Ayanna and her colleagues rely on two concepts in the field of artificial intelligence: "fuzzy logic" and "neural networks."
Fuzzy logic allows computers to operate not only in terms of black and white -- true or false -- but also in shades of gray. For example, a traditional computer would take the height measurement of a tree and assign that tree to some category -- say, "tall." But a fuzzy logic computer would say the tree has a 78 percent chance (for example) of belonging to the category "tall" and a 22 percent chance of belonging to some other category. The sharp distinction between "tall" and "short" becomes fuzzy.
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This probabilistic approach to categorisation allows the computer to learn from its experiences, since the assigning of probabilities can be adjusted the next time a similar object is encountered. Fuzzy logic is already in use today in software such as computer speech and handwriting recognition programs, which learn to perform better through "training."

Brainy Robots

Ayanna Howard may never set foot on Mars or lead a mission to Jupiter, but the work she's doing on "smart" robots will help to revolutionise planetary exploration nonetheless.
As a project scientist specialising in artificial intelligence at NASA's Jet Propulsion Laboratory (JPL), Ayanna is part of a team that applies creative energy to a new generation of space missions -- planetary and moon surface explorations led by autonomous robots capable of "thinking" for themselves.
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Nearly all of today's robotic space probes are inflexible in how they respond to the challenges they encounter (one notable exception is Deep Space 1, which employs artificial intelligence technologies). They can only perform actions that are explicitly written into their software or radioed from a human controller on Earth.
When exploring unfamiliar planets millions of miles from Earth, this "obedient dog" variety of robot requires constant attention from humans. In contrast, the ultimate goal for Ayanna and her colleagues is "putting a robot on Mars and walking away, leaving it to work without direct human interaction."