Teaching Gemini to spot exploding stars with just a few examples
Google Research, in collaboration with the University of Oxford, published a paper in Nature Astronomy demonstrating that Google's Gemini model, using few-shot learning with only 15 annotated examples per survey, can classify cosmic transients (e.g., supernovae) with 93% accuracy across three datasets (Pan-STARRS, MeerLICHT, ATLAS), while also providing textual explanations and interest scores. The model matches specialized CNNs but offers transparency, and a panel of astronomers confirmed the coherence of its outputs.
