A research team trained the algorithm by having it go through data collected by NASA’s now-retired Kepler Space Telescope, which spent nine years in deep space on a world-hunting mission. Once the algorithm learned to accurately separate real planets from false positives, it was used to analyze old data sets that had not yet been confirmed — which is where it found the 50 exoplanets.

These 50 exoplanets, which orbit around other stars, range in size from as large as Neptune to smaller than Earth, the university said in a news release. Some of their orbits are as long as 200 days, and some as short as a single day. And now that astronomers know the planets are real, they can prioritize them for further observation.

The algorithm could “validate thousands of unseen candidates in seconds,” the study indicated. And because it’s based on machine learning, it can still be improved upon, and can continue to become more effective with each new discovery.