MIT system “learns” how to optimally allocate workloads across thousands of servers to cut costs, save energy.

“Risk-aware” traffic engineering could help service providers such as Microsoft, Amazon, and Google better utilize network infrastructure.

In “semiautonomous” cars, older drivers may need more time to take the wheel when responding to the unexpected.

New research from the Computer Science and Artificial Intelligence Laboratory uses machine learning to customize clothing designs.

Model replaces the laborious process of annotating massive patient datasets by hand.

When designing actuators involves too many variables for humans to test by hand, this system can step in.

System lets nonspecialists use machine-learning models to make predictions for medical research, sales, and more.

General-purpose language works for computer vision, robotics, statistics, and more.

System helps machine-learning models glean training information for diagnosing and treating brain conditions.

System automatically writes optimized algorithms to encrypt data in Google Chrome browsers and web applications.