By blending 2D images with foundation models to build 3D feature fields, a new MIT method helps robots understand and manipulate nearby objects with open-ended language prompts.

The scientists used a natural language-based logical inference dataset to create smaller language models that outperformed much larger counterparts.

MIT researchers uncover the structural properties and dynamics of deep classifiers, offering novel explanations for optimization, generalization, and approximation in deep networks.

MIT researchers trained logic-aware language models to reduce harmful stereotypes like gender and racial biases.

Built on recent advances in machine learning, the model predicts how well individuals will produce and comprehend sentences.

MIT researchers are discovering which parts of the brain are engaged when a person evaluates a computer program.

Researchers used a powerful deep-learning model to extract important data from electronic health records that could assist with personalized medicine.

Dan Huttenlocher is a professor of electrical engineering and computer science and the inaugural dean at MIT Schwarzman College of Computing.

MIT engineers are controlling pore openings for maximum molecule capture.

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