Researchers train a machine-learning model to monitor and adjust the 3D printing process to correct errors in real-time.

Using a randomized field experiment, researchers discover that Wikipedia articles affect judges’ legal reasoning.

Neuroscience professor and Science Hub investigator Ted Adelson explains how simulating the sense of touch with a camera can make robots smarter.

“Interpretability methods” seek to shed light on how machine-learning models make predictions, but researchers say to proceed with caution.

Researchers have made strides toward machine-learning models that can help doctors more efficiently find information in a patient’s health record.

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.

Researchers created Exo for writing high-performance code on hardware accelerators.

A new system lets robots manipulate soft, deformable material into various shapes from visual inputs, which could one day enable better home assistants.

MIT scientists unveil the first open-source simulation engine capable of constructing realistic environments for deployable training and testing of autonomous vehicles.

The system rapidly scans the genome of cancer cells, could help researchers find targets for new drugs.