National Science Foundation (NSF)
National Science Foundation (NSF)

National Science Foundation (NSF)

Artificial Intelligence Batteries Computer modeling Department of Energy (DoE) DMSE Electrical engineering and computer science (EECS) machine learning Manufacturing Materials science and engineering Nanoscience and nanotechnology National Science Foundation (NSF) Nuclear science and engineering Research School of Engineering Semiconductors Solar

MIT researchers use AI to uncover atomic defects in materials

A new model measures defects that can be leveraged to improve materials’ mechanical strength, heat transfer, and energy-conversion efficiency.

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) Animals Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Ecology Electrical engineering and computer science (EECS) Environment machine learning Mechanical engineering MIT Schwarzman College of Computing MIT Sea Grant National Science Foundation (NSF) Oceanography and ocean engineering Research School of Engineering Undergraduate Research Opportunities Program (UROP) Video Volunteering, outreach, public service Water

Augmenting citizen science with computer vision for fish monitoring

MIT Sea Grant works with the Woodwell Climate Research Center and other collaborators to demonstrate a deep learning-based system for fish monitoring.

Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Electronics Imaging machine learning Media Lab MIT Schwarzman College of Computing National Science Foundation (NSF) Research Robotics School of Architecture and Planning School of Engineering sensors Wireless

Generative AI improves a wireless vision system that sees through obstructions

With this new technique, a robot could more accurately detect hidden objects or understand an indoor scene using reflected Wi-Fi signals.

Algorithms Artificial Intelligence Astronomy and astrophysics chemistry Computer science and technology Data Faculty IDSS Interview Laboratory for Nuclear Science machine learning Materials science and engineering Mathematics MIT Schwarzman College of Computing National Science Foundation (NSF) Physics Research School of Science

3 Questions: On the future of AI and the mathematical and physical sciences

Professor Jesse Thaler describes a vision for a two-way bridge between artificial intelligence and the mathematical and physical sciences — one that promises to advance both.

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

New method could increase LLM training efficiency

By leveraging idle computing time, researchers can double the speed of model training while preserving accuracy.

Algorithms Artificial Intelligence Cities Civil and environmental engineering Climate change Computer modeling Computer science and technology Electrical engineering and computer science (EECS) Emissions IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Energy Initiative MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering Sustainability Transportation

Parking-aware navigation system could prevent frustration and emissions

By minimizing the need to drive around looking for a parking spot, this technique can save drivers up to 35 minutes — and give them a realistic estimate of total travel time.

Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) IDSS Laboratory for Information and Decision Systems (LIDS) machine learning Mathematics MIT Schwarzman College of Computing MIT-IBM Watson AI Lab National Science Foundation (NSF) Research School of Engineering

Study: Platforms that rank the latest LLMs can be unreliable

Removing just a tiny fraction of the crowdsourced data that informs online ranking platforms can significantly change the results.

Artificial Intelligence Chemical engineering Computer science and technology DMSE machine learning Materials science and engineering National Science Foundation (NSF) Research School of Engineering

How generative AI can help scientists synthesize complex materials

MIT researchers’ DiffSyn model offers recipes for synthesizing new materials, enabling faster experimentation and a shorter journey from hypothesis to use.

Artificial Intelligence Broad Institute Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology cybersecurity Electrical engineering and computer science (EECS) Ethics Health Care Health sciences and technology Human-computer interaction Institute for Medical Engineering and Science (IMES) Jameel Clinic Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Privacy Public health Research School of Engineering Technology and society

MIT scientists investigate memorization risk in the age of clinical AI

New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.

Algorithms Artificial Intelligence Center for Brains Minds and Machines Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Defense Advanced Research Projects Agency (DARPA) Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab National Science Foundation (NSF) Networks Neuroscience Research School of Engineering

Guided learning lets “untrainable” neural networks realize their potential

CSAIL researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method.