The brain power behind sustainable AI
PhD student Miranda Schwacke explores how computing inspired by the human brain can fuel energy-efficient artificial intelligence.
Computer science and technology
Creating AI that matters
How the MIT-IBM Watson AI Lab is shaping AI-sociotechnical systems for the future.
Read MoreNew software designs eco-friendly clothing that can reassemble into new items
To reduce waste, the Refashion program helps users create outlines for adaptable clothing, such as pants that can be reconfigured into a dress. Each component of these pieces can be replaced, rearranged, or restyled.
Read MoreMethod teaches generative AI models to locate personalized objects
After being trained with this technique, vision-language models can better identify a unique item in a new scene.
Read MoreMIT Schwarzman College of Computing and MBZUAI launch international collaboration to shape the future of AI
The MIT–MBZUAI Collaborative Research Program will unite faculty and students from both institutions to advance AI and accelerate its use in pressing scientific and societal challenges.
Read MoreUsing generative AI to diversify virtual training grounds for robots
New tool from MIT CSAIL creates realistic virtual kitchens and living rooms where simulated robots can interact with models of real-world objects, scaling up training data for robot foundation models.
Read MoreFighting for the health of the planet with AI
Assistant Professor Priya Donti’s research applies machine learning to optimize renewable energy.
Read MoreAI 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.
Read MoreResponding 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.
Read MoreNew 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.
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