Researchers coaxed a family of generative AI models to work together to solve multistep robot manipulation problems.

Training artificial neural networks with data from real brains can make computer vision more robust.

A new tool brings the benefits of AI programming to a much broader class of problems.

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

The MIT senior will pursue postgraduate studies in computer science in Ireland.

A new computational model could explain differences in recognizing facial emotions.

Researchers propose a method for finding and fixing weaknesses in automated programming tools.

Researchers show that deep reinforcement learning can be used to design more efficient nuclear reactors.

Adding a module that mimics part of the brain can prevent common errors made by computer vision models.

Recent advances give theoretical insight into why deep learning networks are successful.