Lincoln Lab unveils the most powerful AI supercomputer at any US university
Optimized for generative AI, TX-GAIN is driving innovation in biodefense, materials discovery, cybersecurity, and other areas of research and development.
Responding to the climate impact of generative AI
Explosive growth of AI data centers is expected to increase greenhouse gas emissions. Researchers are now seeking solutions to reduce these environmental harms.
AI system learns from many types of scientific information and runs experiments to discover new materials
The new “CRESt” platform could help find solutions to real-world energy problems that have plagued the materials science and engineering community for decades.
New AI system could accelerate clinical research
By enabling rapid annotation of areas of interest in medical images, the tool can help scientists study new treatments or map disease progression.
Improving the workplace of the future
Economics doctoral student Whitney Zhang investigates how technologies and organizational decisions shape labor markets.
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.
New tool makes generative AI models more likely to create breakthrough materials
With SCIGEN, researchers can steer AI models to create materials with exotic properties for applications like quantum computing.
How are MIT entrepreneurs using AI?
This year’s delta v summer accelerator offered an up-close look at how AI is changing the process of building a startup.
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.
How to build AI scaling laws for efficient LLM training and budget maximization
MIT-IBM Watson AI Lab researchers have developed a universal guide for estimating how large language models will perform based on smaller models in the same family.
Machine-learning tool gives doctors a more detailed 3D picture of fetal health
MIT CSAIL researchers developed a tool that can model the shape and movements of fetuses in 3D, potentially assisting doctors in finding abnormalities and making diagnoses.
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.
AI and machine learning for engineering design
Popular mechanical engineering course applies machine learning and AI theory to real-world engineering design.
A greener way to 3D print stronger stuff
MIT CSAIL researchers developed SustainaPrint, a system that reinforces only the weakest zones of eco-friendly 3D prints, achieving strong results with less plastic.
A new generative AI approach to predicting chemical reactions
System developed at MIT could provide realistic predictions for a wide variety of reactions, while maintaining real-world physical constraints.