Research
Research

Research

Artificial Intelligence Department of Energy (DoE) Energy machine learning Materials science and engineering National Science Foundation (NSF) Nuclear science and engineering Quantum mechanics Research School of Engineering Superconductivity

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.

Artificial Intelligence Collaboration Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Industry machine learning MIT Schwarzman College of Computing MIT Sloan School of Management President Sally Kornbluth Provost Research Robotics School of Architecture and Planning School of Engineering School of Humanities Arts and Social Sciences School of Science Special events and guest speakers Technology and society

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.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering

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.

3-D Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Development Electrical engineering and computer science (EECS) Health Care Health sciences and technology Imaging machine learning MIT Schwarzman College of Computing National Institutes of Health (NIH) Research School of Engineering

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.

Aeronautical and astronautical engineering Artificial Intelligence Computer modeling Computer science and technology Department of Energy (DoE) DMSE Electrical engineering and computer science (EECS) machine learning Mathematics Mechanical engineering MIT Schwarzman College of Computing Research School of Engineering School of Science Security studies and military Space Supercomputing

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.

3-D printing Artificial Intelligence Cleaner industry Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Design Electrical engineering and computer science (EECS) Invention machine learning MIT Schwarzman College of Computing Recycling Research School of Engineering Sustainability

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.

Algorithms Artificial Intelligence Chemical engineering Computer science and technology Electrical engineering and computer science (EECS) Invention MIT Schwarzman College of Computing National Science Foundation (NSF) open source Research School of Engineering

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.

Algorithms Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Interview Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research School of Engineering

3 Questions: The pros and cons of synthetic data in AI

Artificially created data offer benefits from cost savings to privacy preservation, but their limitations require careful planning and evaluation, Kalyan Veeramachaneni says.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Covid-19 Data Disease Drug development Electrical engineering and computer science (EECS) Health Care Health sciences and technology Influenza Jameel Clinic machine learning Medicine MIT Schwarzman College of Computing Research School of Engineering Vaccines Viruses

MIT researchers develop AI tool to improve flu vaccine strain selection

VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.

Algorithms Artificial Intelligence Climate change Computer modeling Data EAPS Earth and atmospheric sciences Emissions IDSS machine learning MIT Schwarzman College of Computing Pollution Public health Research School of Science Sustainability

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.