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Welcome to Bw Reads, our weekend newsletter featuring one great magazine story from Bloomberg Businessweek. Today Jordan Robertson and Drake
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Welcome to Bw Reads, our weekend newsletter featuring one great magazine story from Bloomberg Businessweek. Today Jordan Robertson and Drake Bennett write about Harvard University’s Galileo Project, which has brought high-end academic research to a once-fringe pursuit of intelligent extraterrestrial life with the help of artificial intelligence. You can find the whole story online here.

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When Laura Dominé was getting her Ph.D. in physics at Stanford University, her research was on neutrinos: elementary particles, minuscule even to physicists, that to laypeople sound made-up. Neutrinos are almost massless and electrically neutral, and therefore they pass through matter as if it were air. Trillions of the so-called ghost particles are zipping through you right now unnoticed, continuing journeys that began, for many of them, a single second after the Big Bang.

The detectors built to find evidence of neutrinos are themselves fantastical things. These cavernous chambers, deep in the Earth, are filled with heavy water or liquid argon and lined with exquisitely sensitive photosensors or grids of delicate wiring. Every once in a while, thanks to something called the weak force, a neutrino will react with a subatomic particle inside the vat and be rendered detectable by human instruments. Dominé worked on a machine learning algorithm that could spot these reactions, helping physicists continue to piece together their portrait of the neutrino and, through it, the workings of our strange universe.

After earning her doctorate in 2023, Dominé didn’t join classmates who were going on to traditional astrophysics research programs or tech companies or algorithmic finance firms. Instead she took a postdoctoral fellowship in Cambridge, Massachusetts, at the Harvard & Smithsonian Center for Astrophysics and its Galileo Project, which is building a different kind of detector.

Dominé checking the Dalek’s wiring. Photographer: Cassandra Klos for Bloomberg Businessweek

On a patch of blacktop in the woods a half-hour outside of Boston, the Galileo Project’s array of equipment includes acoustic sensors, a radio-frequency spectrum analyzer, a charged-particle counter, a weather station with a magnetometer, plus several cameras, including eight infrared ones housed in a 20-inch-wide dome reminiscent of R2-D2’s head. This unprepossessing thicket of instruments is pointed at the sky, looking for what are known, in the small research community dedicated to studying them, as unidentified anomalous phenomena, or UAP. (The rest of us call them UFOs.)

Dominé and her fellow researchers are willing to consider all explanations for the anomalies they might uncover. And to them that means being open to the possibility that what they’ll find are signs of intelligent extraterrestrial life—not in some distant galaxy but in our own terrestrial airspace. Determined to apply mainstream scientific rigor to their unorthodox quest, the Galileo team has committed to sifting an entire sky’s worth of data, 24 hours a day. It’s something they’re only able to do because of recent advances in artificial intelligence. “This is the only way to solve this,” Dominé says.

The availability of such tools has coincided with a cultural shift, one fed by a cascade of US Department of Defense disclosures about its own research into ufology. Although the community of respectable alien-hunting academics like Dominé is still small, it’s no longer confined to the fringes. Research programs similar to Harvard’s have sprouted at Wellesley College, Germany’s University of Würzburg and the Nordic Institute for Theoretical Physics, along with the Pentagon. These programs are often run and staffed by people with blue-chip résumés such as Dominé’s, but algorithms are proving to be powerful partners. Rapid improvements in AI software, and the computer servers and other hardware needed to run it, have made it possible to process huge amounts of data in real time from multiple sources, including cameras and other instruments deployed in the field. These systems are advancing beyond their human training, teaching themselves to spot entirely new kinds of objects in the sky.

Keep reading: America’s Leading Alien Hunters Depend on AI to Speed Their Search

Watch a new short from Bloomberg Originals on the Galileo Project

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