This article offers a concise, one‑page overview of more than 100 pivotal AI‑for‑Science papers published in 2025, spanning biomedicine, materials chemistry, climate modeling, astronomy and other fields, and includes key findings, citations, and links for each breakthrough.
A multinational team of researchers from Stanford, Peking University, UCL and UC Berkeley built a data‑driven pipeline using convolutional neural networks to scan DESI DR1 spectra, expanding the known quasar‑lens sample from a handful to seven high‑quality candidates and demonstrating the power of AI for rare‑object astronomy.
AION-1, developed by a consortium including UC Berkeley, Cambridge and Oxford, is the first large‑scale multimodal foundation model for astronomy that unifies images, spectra and catalog data via an early‑fusion backbone, achieving zero‑shot and linear‑probe performance that rivals or surpasses task‑specific models across diverse scientific tasks.
This article explores ten mind‑blowing facts about the cosmos—from vast cosmic voids and magnetars to the perfect Sun‑Moon size ratio, Andromeda's true scale, perpetual universal motion, Venus's long day, sound in space, pulsar navigation, dark matter dominance, and how space exploration fuels everyday technology.
