Hold on tight.
. These networks are made up of nodes that connect like neurons, and they even"learn" in the same manner that organic brains do by being trained on sets of data, such as object recognition in photos or speech recognition. In other words, they get a lot better at these things over time.
In experiments, the scientists created a chip with a surface area of 0.01 square inches and used it to classify a sequence of handwritten characters that looked like letters. The chip was able to classify photos with 93.8 percent accuracy for sets having two types of characters, and 89.8 percent accuracy for sets containing four types after being trained on relevant data sets.
“Our chip processes information through what we call ‘computation-by-propagation,’ meaning that, unlike clock-based systems, computations occur as light propagates through the chip,” said Firooz Aflatouni, lead author of the study. “We are also skipping the step of converting optical signals to electrical signals because our chip can read and process optical signals directly, and both of these changes make our chip a significantly faster technology.