Scientists using advanced "neural network" machine-learning software to sift through thousands of weak, previously unstudied signals from NASA's planet-hunting Kepler spacecraft have identified two new worlds orbiting distant suns, researches announced Thursday.
One of them is the eighth planet now known to be orbiting the star Kepler-90, the first solar system other than Earth's to host at least that many worlds.
"What's different about this discovery is that we used machine learning to help identify planets that were missed by previous searches of the Kepler data," said Christopher Shallue, a senior software engineer at Google AI in Mountain View, Calif.
"The key contribution of machine learning here is it was able to search a much larger number of signals than humans would have been able to do in a reasonable amount of time."
The Kepler satellite, launched in 2009, has discovered 2,525 confirmed "exoplanets" orbiting other stars, using a 95-megapixel camera to measure the very slight dimming of a target star's light as a planet moves across its face as viewed from the spacecraft.
Up to this point, planet detections required astronomers to focus on the stronger signals to find planet candidates that then were confirmed or rejected based on additional observations and analysis to root out "false positives" and make sure the data reflected the transit of an actual planet.