Robots that have been programmed to see or feel can’t use these signals quite as interchangeably. To better bridge this sensory gap, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have come up with a predictive artificial intelligence (AI) that can learn to see by touching, and learn to feel by seeing.

Wearing a sensor-packed glove while handling a variety of objects, MIT CSAIL researchers have compiled a massive dataset that enables an AI system to recognize objects through touch alone. The information could be leveraged to help robots identify and manipulate objects, and may aid in prosthetics design.

If you’ve ever wondered what a loaf of bread would look like as a cat, edges2cats is for you. The program that turns sketches into images of cats is one of many whimsical creations inspired by Phillip Isola’s image-to-image translation software released in the early days of generative adversarial networks, or GANs.

A team of roboticists at MIT CSAIL and Harvard has developed a new way to design pistons that replaces their conventional rigid elements with a mechanism using compressible structures inside a membrane made of soft materials.

With aims of bringing more human-like reasoning to autonomous vehicles, a team led by researchers at MIT CSAIL have created a system that uses only simple maps and visual data to enable driverless cars to navigate routes in new, complex environments.

MIT CSAIL unsealed a special time capsule from 1999 after a self-taught programmer Belgium solved a puzzle devised by MIT professor and famed cryptographer Ron Rivest.

A team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Massachusetts General Hospital (MGH) has created a new deep learning model that can predict from a mammogram if a patient is likely to develop breast cancer in the future. They trained their model on mammograms and known outcomes from over 60,000 patients treated at MGH, and their model learned the subtle patterns in breast tissue that are precursors to malignancy.

Constantinos (“Costis”) Daskalakis, an MIT professor and CSAIL principal investigator, has won the 2018 ACM Grace Murray Hopper Award. Daskalakis was honored for “proving that the computational complexity of finding Nash equilibria is the same as that of finding Brouwer fixed points, a proof since extended to several other equilibrium notions.”

MIT placed first among all North American teams - and second globally - at the World Finals of the Association for Computing Machinery's 43rd annual International College Programming Contest (ICPC) in Porto, Portugal.

The world's most prestigious programming contest, ICPC involves 300,000 students from two thousand universities and nearly 100 countries, with only the top 128 teams earning a spot in the finals.

A novel technique developed by MIT researchers rethinks hardware data compression to free up more memory used by computers and mobile devices, allowing them to run faster and perform more tasks simultaneously.