A.I. takes the search for ET to a new level: deep learning uncovers 8 mysterious signals (science news).

In the quest to discover extraterrestrial life, scientists have always faced a major challenge: how to sort through the massive amount of data collected by their telescopes and distinguish between real signals and interference.

But now, a team of researchers led by an undergraduate student at the University of Toronto has found a solution by using a new machine learning algorithm to categorize the data. And the results are staggering: they’ve uncovered eight previously unidentified signals that could be evidence of extraterrestrial intelligence.

The team was able to quickly sort through the information and find patterns by using artificial intelligence, a process known as machine learning. They re-examined data taken with the Green Bank Telescope in West Virginia and applied a deep learning technique to a previously studied dataset of nearby stars.

The newly detected signals have several key characteristics that could indicate extraterrestrial life. They are narrow band, have non-zero drift rates, and appear in on-source observations but not in off-source observations.

The scientists are optimistic about the future of the search for extraterrestrial life, saying that this new machine learning approach could be “transformational” for the field. And with more advances in technology, the search for ET is sure to continue, bringing us one step closer to answering the age-old question: “are we alone in the universe?”

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