Keith Cooper is a freelance science journalist and editor in the United Kingdom, and has a degree in physics and astrophysics from the University of Manchester. He's the author of 'The Contact Paradox: Challenging Our Assumptions in the Search for Extraterrestrial Intelligence' (Bloomsbury Sigma, 2020) and has written articles on astronomy, space, physics and astrobiology for a multitude of magazines and websites.
World Space Week 2023 is here and Space.com is looking at the current state of artificial intelligence and its impact on astronomy and space exploration as the space age celebrates its 66th anniversary. Here, Keith Cooper discusses how AI might help humans detect alien life.to radio galaxies, and ionospheric disturbances in the atmosphere to radio-frequency interference from our own technology, the sky is a cacophony of radio noise.
That other stuff is usually RFI, but the machine-learning algorithm is trained to recognize all the types of RFI we already know about. Those signals — the familiar patterns of mobile phones, local radio transmitters, electronics and so on — are the hay. These eight signals seem to come from five different star systems, although they might be misleading. They haven't been detected since — to see a signal repeat is the most basic requirement for a signal to be considered interesting in SETI — and they will probably turn out to be more RFI. However, even that's useful, because they can be used to train the next generation of machine-learning AI so similar RFI can be avoided in the future.
Certainly, in the age of 'Big Data', machine-learning AI is the way forward and is now being used extensively inWith machine learning algorithms, humans are still intimately involved. A signal might get flagged up by the AI as being intriguing, but it is still humans who have to follow up and investigate. The algorithms aren't that smart.
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