MIT affiliates win AI for Math grants to accelerate mathematical discovery
Department of Mathematics researchers David Roe and Andrew Sutherland seek to advance automated theorem proving; four additional MIT alumni also awarded.
School of Science
What does the future hold for generative AI?
At the inaugural MIT Generative AI Impact Consortium Symposium, researchers and business leaders discussed potential advancements centered on this powerful technology.
DoE selects MIT to establish a Center for the Exascale Simulation of Coupled High-Enthalpy Fluid–Solid Interactions
The research center, sponsored by the DoE’s National Nuclear Security Administration, will advance the simulation of extreme environments, such as those in hypersonic flight and atmospheric reentry.
Simpler models can outperform deep learning at climate prediction
New research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.
Researchers glimpse the inner workings of protein language models
A new approach can reveal the features AI models use to predict proteins that might make good drug or vaccine targets.
MIT tool visualizes and edits “physically impossible” objects
By visualizing Escher-like optical illusions in 2.5 dimensions, the “Meschers” tool could help scientists understand physics-defying shapes and spark new designs.
New machine-learning application to help researchers predict chemical properties
ChemXploreML makes advanced chemical predictions easier and faster — without requiring deep programming skills.
New AI system uncovers hidden cell subtypes, boosts precision medicine
CellLENS reveals hidden patterns in cell behavior within tissues, offering deeper insights into cell heterogeneity — vital for advancing cancer immunotherapy.
Accelerating scientific discovery with AI
FutureHouse, co-founded by Sam Rodriques PhD ’19, has developed AI agents to automate key steps on the path toward scientific progress.
Using generative AI to help robots jump higher and land safely
MIT CSAIL researchers combined GenAI and a physics simulation engine to refine robot designs. The result: a machine that out-jumped a robot designed by humans.