MIT Schwarzman College of Computing
MIT Schwarzman College of Computing

Using AI, scientists find a drug that could combat drug-resistant infections

The machine-learning algorithm identified a compound that kills Acinetobacter baumannii, a bacterium that lurks in many hospital settings.

Probabilistic AI that knows how well it’s working

It’s more important than ever for artificial intelligence to estimate how accurately it is explaining data.

Researchers use AI to identify similar materials in images

This machine-learning method could assist with robotic scene understanding, image editing, or online recommendation systems.

Using data to write songs for progress

Senior Ananya Gurumurthy adds her musical talents to her math and computer science studies to advocate using data for social change.

Is medicine ready for AI? Doctors, computer scientists, and policymakers are cautiously optimistic

With the artificial intelligence conversation now mainstream, the 2023 MIT-MGB AI Cures conference saw attendance double from previous years.

A better way to study ocean currents

A new machine-learning model makes more accurate predictions about ocean currents, which could help with tracking plastic pollution and oil spills, and aid in search and rescue.

3 Questions: Jacob Andreas on large language models

The CSAIL scientist describes natural language processing research through state-of-the-art machine-learning models and investigation of how language can enhance other types of artificial intelligence.

Study: AI models fail to reproduce human judgements about rule violations

Models trained using common data-collection techniques judge rule violations more harshly than humans would, researchers report.

Success at the intersection of technology and finance

Citadel founder and CEO Ken Griffin visits MIT, discusses how technology will continue to transform trading and investing.

Training machines to learn more like humans do

Researchers identify a property that helps computer vision models learn to represent the visual world in a more stable, predictable way.