School of Engineering
School of Engineering

School of Engineering

3-D printing Artificial Intelligence machine learning Materials science and engineering Mechanical engineering Research School of Engineering

Printable aluminum alloy sets strength records, may enable lighter aircraft parts

Incorporating machine learning, MIT engineers developed a way to 3D print alloys that are much stronger than conventionally manufactured versions.

Aeronautical and astronautical engineering Artificial Intelligence Computer modeling Energy Fluid dynamics Fusion Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Nuclear power and reactors Plasma Science and Fusion Center Renewable energy Research School of Engineering Sustainability

New prediction model could improve the reliability of fusion power plants

The approach combines physics and machine learning to avoid damaging disruptions when powering down tokamak fusion machines.

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

AI maps how a new antibiotic targets gut bacteria

MIT CSAIL and McMaster researchers used a generative AI model to reveal how a narrow-spectrum antibiotic attacks disease-causing bacteria, speeding up a process that normally takes years.

Algorithms Artificial Intelligence Climate change Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Emissions Energy Energy storage Infrastructure Lincoln Laboratory machine learning MIT Energy Initiative MIT Schwarzman College of Computing MIT Sloan School of Management Research School of Engineering Supercomputing Sustainable computing

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.

Artificial Intelligence DMSE Energy machine learning Materials science and engineering MIT.nano Nanoscience and nanotechnology Nuclear science and engineering Research School of Engineering

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.

Artificial Intelligence Broad Institute Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) health Health Care Imaging machine learning Medicine MIT Schwarzman College of Computing National Institutes of Health (NIH) Research School of Engineering

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.

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.