Google has a small fleet of robotic cars that since autumn have driven themselves for thousands of miles on the streets of northern California without once striking a pedestrian, running a stoplight or having to ask directions. The cars’ ability to analyze enormous quantities of data--from cameras, radar sensors, laser-range finders--lies in the 18th-century math theorem known as Bayes’ rule. The formula has survived decades of controversy and marginalization to emerge as the cornerstone of some of the most sophisticated robotics projects now under way around the world.
Discovered by English clergyman Thomas Bayes, the formula is a simple one-liner: Initial Beliefs + Recent Objective Data = A New and Improved Belief. A modern form comes from French mathematician Pierre-Simon Laplace, who, by recalculating the equation each time he got new data, could distinguish highly probable hypotheses from less valid ones. One of his applications involved explaining why slightly more boys than girls were born in Paris in the late 1700s. After collecting demographic data from around the world for 30 years, he concluded that the boy-girl ratio is universal to humankind and determined by biology.
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