Electrical engineering and computer science (EECS)

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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 […]

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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

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Using generative AI to diversify virtual training grounds for robots

Artificial Intelligence, Computer modeling, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, data, Electrical engineering and computer science (EECS), Internet, Machine Learning, MIT Schwarzman College of Computing, Research, Robotics, School of Engineering, Simulation

Chatbots like ChatGPT and Claude have experienced a meteoric rise in usage over the past three years because they can help you with a wide range of tasks. Whether you’re writing Shakespearean sonnets, debugging code, or need an answer to an obscure trivia question, artificial intelligence systems seem to have you covered. The source of

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MIT Schwarzman College of Computing and MBZUAI launch international collaboration to shape the future of AI

Artificial Intelligence, Collaboration, Computer science and technology, Electrical engineering and computer science (EECS), Funding, International initiatives, MIT Schwarzman College of Computing, Research, School of Engineering, Technology and society

The MIT Schwarzman College of Computing and the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) recently celebrated the launch of the MIT–MBZUAI Collaborative Research Program, a new effort to strengthen the building blocks of artificial intelligence and accelerate its use in pressing scientific and societal challenges.Under the five-year agreement, faculty, students, and research staff

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Helping scientists run complex data analyses without writing code

Algorithms, Alumni/ae, Artificial Intelligence, Disease, Electrical engineering and computer science (EECS), Health, Innovation and Entrepreneurship (I&E), Machine Learning, Medicine, School of Engineering, Startups

As costs for diagnostic and sequencing technologies have plummeted in recent years, researchers have collected an unprecedented amount of data around disease and biology. Unfortunately, scientists hoping to go from data to new cures often require help from someone with experience in software engineering.Now, Watershed Bio is helping scientists and bioinformaticians run experiments and get

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Method teaches generative AI models to locate personalized objects

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, Video

Say a person takes their French Bulldog, Bowser, to the dog park. Identifying Bowser as he plays among the other canines is easy for the dog-owner to do while onsite.But if someone wants to use a generative AI model like GPT-5 to monitor their pet while they are at work, the model could fail at

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New software designs eco-friendly clothing that can reassemble into new items

Artificial Intelligence, Cleaner industry, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Design, Electrical engineering and computer science (EECS), Human-computer interaction, Invention, Machine Learning, Media Lab, MIT Morningside Academy for Design, MIT Schwarzman College of Computing, Research, School of Engineering, Sustainability

It’s hard to keep up with the ever-changing trends of the fashion world. What’s “in” one minute is often out of style the next season, potentially causing you to re-evaluate your wardrobe.Staying current with the latest fashion styles can be wasteful and expensive, though. Roughly 92 million tons of textile waste are produced annually, including the

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Creating AI that matters

Algorithms, Artificial Intelligence, Business and management, Collaboration, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, data, Electrical engineering and computer science (EECS), IDSS, Industry, Machine Learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering, Technology and society

When it comes to artificial intelligence, MIT and IBM were there at the beginning: laying foundational work and creating some of the first programs — AI predecessors — and theorizing how machine “intelligence” might come to be.Today, collaborations like the MIT-IBM Watson AI Lab, which launched eight years ago, are continuing to deliver expertise for

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DOE selects MIT to establish a Center for the Exascale Simulation of Coupled High-Enthalpy Fluid–Solid Interactions

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

The U.S. Department of Energy’s National Nuclear Security Administration (DOE/NNSA) recently announced that it has selected MIT to establish a new research center dedicated to advancing the predictive simulation of extreme environments, such as those encountered in hypersonic flight and atmospheric re-entry. The center will be part of the fourth phase of NNSA’s Predictive Science Academic Alliance

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How to build AI scaling laws for efficient LLM training and budget maximization

When researchers are building large language models (LLMs), they aim to maximize performance under a particular computational and financial budget. Since training a model can amount to millions of dollars, developers need to be judicious with cost-impacting decisions about, for instance, the model architecture, optimizers, and training datasets before committing to a model. To anticipate

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