“One of the biggest problems in science today is moving forward and finding the underlying principles in areas where there is lots and lots of data, but there’s a theoretical gap. We don’t know how things work,” said Hod Lipson, the Cornell University computational researcher who co-wrote the program. “I think this is going to be an important tool.”
Condensing rules from raw data has long been considered the province of human intuition, not machine intelligence. It could foreshadow an age in which scientists and programs work as equals to decipher datasets too complex for human analysis.
