Google open sources machine learning tech it used to find new planets

Google will open source the machine learning technology that allowed it to discover new exoplanets, the tech giant announced in a Thursday blog post. In December, Google announced that it had found two exoplanets by training a neural network to analyze data from NASA's Kepler space telescope and identify signals that could be coming from planets, our sister site ZDNet reported at the time. This success suggests that machine learning could be used both for discovering exoplanets, as well as a number of other scientific disciplines, including healthcare and quantum chemistry, Chris Shallue, a senior software engineer on the Google Brain Team, wrote in the blog post. SEE: IT pro's guide to working smarter with Linux (Tech Pro Research) This code may be useful for those developing similar models for other NASA missions, including Kepler's second mission K2, and the upcoming Transiting Exoplanet Survey Satellite mission, the post noted. In the post, Google also explained the basics of how the model works. When searching for planets in Kepler data, scientists use automated software to first detect signals that could potentially be caused by planets.