Machine Learning

Auto Added by WPeMatico

How artificial intelligence can help achieve a clean energy future

Artificial Intelligence, Chemical engineering, Cleaner industry, Climate, Electric grid, Electric vehicles, Energy, Energy efficiency, Energy storage, infrastructure, Investments, Machine Learning, Mechanical engineering, MIT Energy Initiative, Renewable energy, Research, School of Engineering, Sustainability, Sustainable computing, Weather modeling

There is growing attention on the links between artificial intelligence and increased energy demands. But while the power-hungry data centers being built to support AI could potentially stress electricity grids, increase customer prices and service interruptions, and generally slow the transition to clean energy, the use of artificial intelligence can also help the energy transition.For […]

How artificial intelligence can help achieve a clean energy future Read More »

A faster problem-solving tool that guarantees feasibility

Algorithms, Alternative energy, Artificial Intelligence, Computer science and technology, Electrical engineering and computer science (EECS), Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, Research, School of Engineering

Managing a power grid is like trying to solve an enormous puzzle.Grid operators must ensure the proper amount of power is flowing to the right areas at the exact time when it is needed, and they must do this in a way that minimizes costs without overloading physical infrastructure. Even more, they must solve this

A faster problem-solving tool that guarantees feasibility Read More »

3 Questions: How AI is helping us monitor and support vulnerable ecosystems

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS), Algorithms, 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, Graduate, postdoctoral, Interview, Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Pollution, Research, School of Engineering, Students, Sustainability

A recent study from Oregon State University estimated that more than 3,500 animal species are at risk of extinction because of factors including habitat alterations, natural resources being overexploited, and climate change.To better understand these changes and protect vulnerable wildlife, conservationists like MIT PhD student and Computer Science and Artificial Intelligence Laboratory (CSAIL) researcher Justin Kay

3 Questions: How AI is helping us monitor and support vulnerable ecosystems Read More »

Teaching robots to map large environments

Aeronautical and astronautical engineering, Algorithms, Artificial Intelligence, Autonomous vehicles, Computer science and technology, Computer vision, Disaster response, Electrical engineering and computer science (EECS), Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, Robotics, School of Engineering

A robot searching for workers trapped in a partially collapsed mine shaft must rapidly generate a map of the scene and identify its location within that scene as it navigates the treacherous terrain.Researchers have recently started building powerful machine-learning models to perform this complex task using only images from the robot’s onboard cameras, but even

Teaching robots to map large environments Read More »

MIT researchers propose a new model for legible, modular software

Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Human-computer interaction, Machine Learning, MIT Schwarzman College of Computing, Programming, Programming languages, Research, School of Engineering, Software

Coding with large language models (LLMs) holds huge promise, but it also exposes some long-standing flaws in software: code that’s messy, hard to change safely, and often opaque about what’s really happening under the hood. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are charting a more “modular” path ahead. Their new approach breaks

MIT researchers propose a new model for legible, modular software Read More »

Charting the future of AI, from safer answers to faster thinking

Algorithms, Artificial Intelligence, Classes and programs, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, data, Electrical engineering and computer science (EECS), Graduate, postdoctoral, Institute for Medical Engineering and Science (IMES), Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering, Students

Adoption of new tools and technologies occurs when users largely perceive them as reliable, accessible, and an improvement over the available methods and workflows for the cost. Five PhD students from the inaugural class of the MIT-IBM Watson AI Lab Summer Program are utilizing state-of-the-art resources, alleviating AI pain points, and creating new features and

Charting the future of AI, from safer answers to faster thinking Read More »

AI maps how a new antibiotic targets gut bacteria

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

For patients with inflammatory bowel disease, antibiotics can be a double-edged sword. The broad-spectrum drugs often prescribed for gut flare-ups can kill helpful microbes alongside harmful ones, sometimes worsening symptoms over time. When fighting gut inflammation, you don’t always want to bring a sledgehammer to a knife fight.Researchers at MIT’s Computer Science and Artificial Intelligence

AI maps how a new antibiotic targets gut bacteria Read More »

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

3-D printing, Artificial Intelligence, DMSE, Machine Learning, Materials science and engineering, Mechanical engineering, MIT.nano, Research, School of Engineering

MIT engineers have developed a printable aluminum alloy that can withstand high temperatures and is five times stronger than traditionally manufactured aluminum.The new printable metal is made from a mix of aluminum and other elements that the team identified using a combination of simulations and machine learning, which significantly pruned the number of possible combinations

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

New prediction model could improve the reliability of fusion power plants

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

Tokamaks are machines that are meant to hold and harness the power of the sun. These fusion machines use powerful magnets to contain a plasma hotter than the sun’s core and push the plasma’s atoms to fuse and release energy. If tokamaks can operate safely and efficiently, the machines could one day provide clean and

New prediction model could improve the reliability of fusion power plants Read More »

Fighting for the health of the planet with AI

Algorithms, Artificial Intelligence, Climate change, Computer science and technology, Electric grid, Electrical engineering and computer science (EECS), Energy, Faculty, Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, Profile, Renewable energy, School of Engineering, Sustainability, Technology and policy

For Priya Donti, childhood trips to India were more than an opportunity to visit extended family. The biennial journeys activated in her a motivation that continues to shape her research and her teaching.Contrasting her family home in Massachusetts, Donti — now the Silverman Family Career Development Professor in the MIT Department of Electrical Engineering and

Fighting for the health of the planet with AI Read More »