Machine learning speeds up vehicle routing
Strategy accelerates the best algorithmic solvers for large sets of cities.
Strategy accelerates the best algorithmic solvers for large sets of cities.
Summit features the latest research of women and other underrepresented genders in MIT EECS, along with an opportunity to network, share experiences, and learn.
New technique applied to small computer chips enables efficient vision and detection algorithms without internet connectivity.
A new “common-sense” approach to computer vision enables artificial intelligence that interprets scenes more accurately than other systems do.
MIT-IBM Watson AI Lab researchers aim to design concrete mixtures that use AI to shrink environmental footprint and cost, while recycling byproducts and increasing performance.
Chandrakasan honored for his “contributions to ultralow-power circuits and systems, and leadership in academia and advancing diversity in the profession.”
A new AI-powered, virtual platform uses real-world physics to simulate a rich and interactive audio-visual environment, enabling human and robotic learning, training, and experimental studies.
Reducing the complexity of a powerful machine-learning model may help level the playing field for automatic speech-recognition around the world.
Scientists employ an underused resource — radiology reports that accompany medical images — to improve the interpretive abilities of machine learning algorithms.
MIT professor is designing the next generation of smart wireless devices that will sit in the background, gathering and interpreting data, rather than being worn on the body.
Nearly 300 government and military members participated in a new course designed to explore the next generation of artificial intelligence and related technologies.
A virtual environment embedded with knowledge of the physical world speeds up problem-solving.
Professor Markus Buehler composed it, and a South Korean orchestra performed it; it’s the latest in a series of artistic collaborations sparked by Buehler’s exploration of the structure of SARS-CoV-2.
SuperUROP scholars apply deep learning to improve accuracy of climate models, profitably match computers in the cloud with customers, and more.
Her research focuses on more-efficient deep neural networks to process video, and more-efficient hardware to run applications.