AI for Science
What large models actually change once they enter physics, weather, biology and materials labs, and which results hold up under experimental replication rather than stopping at the demo stage, for research and industry readers.
AI for science treats large models as research collaborators: reading literature, proposing hypotheses, running simulations and screening experiments. After AlphaFold rewrote protein structure prediction, the same approach has spread to particle physics, weather forecasting and new materials, and the bar has risen with it: findings must survive experimental replication, not just a launch presentation.
