Yet another solar system with 8 planets discovered by NASA’s AI
The National Aeronautics and Space Administration (NASA) on Thursday, December 14, announced that “our solar system now is tied for most number of planets around a single star.
The eight-planet system — the largest known outside of ours — orbits a star called Kepler 90 some 2,545 light-years away.
“The Kepler-90 star system is like a mini version of our solar system.
How was these planets found?
- The planet was found using a machine-learning system from Google, which was put to work sifting through data from NASA’s Kepler spacecraft.
- Kepler, a space telescope that trails Earth in orbit around the sun, has stared down 145,000 sun-like stars over the years to look for signs of distant planets.
- To detect these two new worlds, Google’s machine learning learned how to identify signals from exoplanets recorded in the Kepler data.
- It processed 14 billion data points from four years’ worth of Kepler images, using what’s known as a convolutional neural network, which sort of mimics the way the human brain processes information.
NASA and Google say this new technology will help scientists find many more such exoplanets in the future. In fact, Vanderburg believes the Kepler-90 solar system likely has more planets that we haven’t yet detected.
Prior to this analysis, NASA’s last examination of Kepler data confirmed 219 new worlds in the more than 4,000 candidates that Kepler had turned up.
The space agency’s current total of confirmed exoplanets is now 2,525 – and 10 of those may be rocky, Earth-size, and possibly habitable to alien life.
For those wondering whether Google’s AI system could make astronomers obsolete, NASA says not to worry.
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.