![]() ![]() Follow-up observations have so far failed to detect the radio signals again.Īstronomers are keen to study them more closely and try to determine if they actually are from deep space or just terrestrial interference, but they need to detect them again to do this. 'We believe that work like this will help accelerate the rate we're able to make discoveries in our grand effort to answer the question "are we alone in the universe?"' 'We're scaling this search effort to one million stars today with the MeerKAT telescope and beyond. Ma said: 'In total, we had searched through 150 TB of data of 820 nearby stars, on a dataset that had previously been searched through in 2017 by classical techniques but labeled as devoid of interesting signals. While not proven to be extraterrestrial, they are never-the-less interesting. The eight signals appear to originate from the direction of five of the collection of 820 stars, which range from 30 to 90 light-years away. 'Peter's algorithm gives us a more effective way to filter the haystack and find signals that have the characteristics we expect from technosignatures.' 'The vast majority of the signals detected by our telescopes originate from our own technology: GPS satellites, mobile phones and the like. Steve Croft, a project scientist for Breakthrough Listen on the Green Bank Telescope, added: 'The key issue with any technosignature search is looking through this huge haystack of signals to find the needle that might be a transmission from an alien world. However, rather than there being nothing of interest in that area of space, Ma and his colleagues have now discovered as many as eight different radio signals coming from it. Byrd Green Bank Telescope in West Virginia. The existing algorithm had previously found nothing when it searched radio data from a selection of stars collected by the Robert C. In this case, the researchers essentially took a classic algorithm from a more basic computer and used machine learning to teach it to differentiate between potential alien signals and human-caused ones. It involved using deep learning - a type of machine learning and artificial intelligence that imitates the way humans gain certain types of knowledge and is a key technology in driverless cars. ![]() Along with astronomers from the SETI Institute, Breakthrough Listen and scientific research institutions around the world, Ma developed a new machine learning algorithm that can better pick out potential alien signals from all the background noise on our planet. ![]()
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