🔬 Astronomers have been using machine learning since the late 1980s, decades before ChatGPT existed. The earliest neural networks in astronomy classified stars vs galaxies on photographic plates.

Here's what's interesting about how AI actually works in astronomy:

The AI used in astronomy is almost never a chatbot. It's specialized ML models trained for narrow tasks like classifying galaxies by shape or estimating parameters of gravitational wave signals. These models train on hundreds of thousands of already-classified galaxies, learn which features cluster together, then categorize new ones with a confidence score.

A huge application is outlier detection. The Vera C. Rubin Observatory will generate about 7 million alerts per night (tens of billions over its 10-year survey). Most are ordinary or noise. ML systems rank alerts so astronomers can focus on the genuinely unusual ones.

And no, AI isn't replacing astronomers. There are roughly 10,000 professional astronomers worldwide. The volume of data already far exceeds what humans could ever manually inspect.

Read more:
https://rubinobservatory.org/explore/how-rubin-works/alerts
https://pmc.ncbi.nlm.nih.gov/articles/PMC10230190/
https://ar5iv.labs.arxiv.org/html/1912.02934

#astronomy #MachineLearning #science