What would Gailleo do? A group of scientists and astronomers have successfully used artificial intelligence and machine learning to identify and classify a supernova as it happened. It was a test of the Bright Transient Survey (BTS) bot project, part of a broader program that observes and classifies supernovae exceeding a specific brightness level. The team behind BTSbot said it could cut the human middleman out of confirming whether a detected event was an exploding star, giving researchers more time to analyze the heavenly event. The bot launched last week and was helmed by students and faculty at the private research Northwestern University. “This represents an important step forward as further refinement of models will allow the robots to isolate specific subtypes of stellar explosions,” Northwestern University assistant professor Adam Miller said. “Ultimately, removing humans from the loop provides more time for the research team to analyze their observations and develop new hypotheses to explain the origin of the cosmic explosions that we observe.” Some people have voiced concerns about being replaced by AI and resisted the idea of removing the “human middleman,” but Miller said the goal is efficiency. “We’ve been doing this since about 2018 when this program first started,” project co-lead and astronomy graduate student Nabeel Rehemtulla told Decrypt. “So we now have tens of thousands of supernovae, which we can train and build the model on and automate this process.”
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