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New hardware offers faster computation for artificial intelligence, with much less energy

August 1, 2022

Engineers working on “analog deep learning” have found a way to propel protons through solids at unprecedented speeds.

Artificial intelligence model finds potential drug molecules a thousand times faster

July 15, 2022

A geometric deep-learning model is faster and more accurate than state-of-the-art computational models, reducing the chances and costs of drug trial failures.

Costis Daskalakis appointed inaugural Avanessians Professor in the MIT Schwarzman College of Computing

July 15, 2022

The MIT Stephen A. Schwarzman College of Computing has named Costis Daskalakis as the inaugural holder of the Avanessians Professorship. His chair began on July 1. Daskalakis is

The Thriving Stars of AI

July 11, 2022

Four early-career researchers shared their work on improving the social outcomes of artificial intelligence and machine learning at a research summit hosted by EECS Thriving Stars.

Taking the guesswork out of dental care with artificial intelligence

June 24, 2022

MIT alumni-founded Overjet analyzes and annotates dental X-rays to help dentists offer more comprehensive care.

Student-powered machine learning

June 10, 2022

Recent MEng graduates reflect on their application-focused research as affiliates of the MIT-IBM Watson AI Lab.

Artificial intelligence predicts patients’ race from their medical images

May 23, 2022

Study shows AI can identify self-reported race from medical images that contain no indications of race detectable by human experts.

On the road to cleaner, greener, and faster driving

May 17, 2022

Researchers use artificial intelligence to help autonomous vehicles avoid idling at red lights.

School of Engineering welcomes new faculty

March 8, 2022

Sixteen new professors join the MIT community, with research areas ranging from robotics and machine learning to health care and agriculture.

Injecting fairness into machine-learning models

March 3, 2022

A new technique boosts models’ ability to reduce bias, even if the dataset used to train the model is unbalanced.