The research by Google and the University of Texas at Austin that used data from NASA raised the prospects of new insights into the universe by feeding data into computer programs that can churn through information faster and more in-depth than humanly possibly, a technique known as machine learning.
The rocky planet orbits its star once every 14.4 days and was discovered using a machine learning from Google.
Scientists found it by using machine learning from Google.
"In this way, a computer can "learn" how to identify a dog from a cat, or an exoplanet from something else in the readings measured by space telescopes like Kepler".
The planet Kepler-90i, described at a briefing Thursday and detailed in a paper accepted for publication in the Astronomical Journal, demonstrates that other stars can indeed host planetary systems as populous as our own solar system.
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The four-year dataset from Kepler contains more than 35,000 strong signals of possible planets circling distant stars, data that researchers have already sifted through and classified as either "planet" or "not planet".
"The Kepler-90 star system is like a mini version of our solar system. You have small planets inside and big planets outside, but everything is scrunched in much closer", said Andrew Vanderburg, astronomer and NASA Sagan Postdoctoral Fellow at The University of Texas, Austin.
This is the only eight-planet solar system found like ours - so far.
With the discovery of the eight planet Kepler-90i, the planetary system Kepler 90 has matched our solar system.
Google in recent years has been investing heavily on AI and machine learning across its products and services.
The team used the neural network to look at 15,000 signals that had been previously confirmed as either a planet or a false positive, and the network learned how to distinguish real planets from false signals.
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Google's AI has analysed only 10% of the 150,000 stars NASA's Kepler Mission has been eyeing off across the Milky Way galaxy.
The researchers also found a sixth planet in the Kepler-80 system. The A.I. found a weak transit signal from a planet known as Kepler-90i that had been previously missed.
Google is also continuing to push machine learning in its more regular product set, with its Sheets app now able to suggest pivot tables from a simple natural language query.
NASA project scientist for the Kepler space telescope, Jessie Dotson said, "who knows what might be discovered, As the application of neutral networks to Kepler data matures", he further added, "I'm on the edge of my seat".
There's potential then for sifting through Kepler's entire catalogue and finding other exoplanetary worlds that have either been skimmed by scientist or haven't been checked yet, due to Kepler's rich data set. The computer creates a neural network like the human brain. That's the downside of the transiting method; even if multiple planets are orbiting a star that the telescope is pointed at, it will only see them if the the planets pass directly in front of the star - it's all about line-of-sight. The process of finding the planets is very tough.
But earlier this year, a pair of researchers chose to take a closer look at the massive store of data collected by the Kepler space telescope.
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