Neural Networks can learn to solve all sorts of problems, from identifying cats in photographs to steering a self-driving car. But whether these powerful, pattern-recognizing algorithms actually understand the tasks they are performing remains an open question.

MIT professor is designing the next generation of smart wireless devices that will sit in the background, gathering and interpreting data, rather than being worn on the body.

ARROW, a reconfigurable fiber optics network developed at MIT, aims to take on the end of Moore’s law.

“SensiCut,” a smart material-sensing platform for laser cutters, can differentiate between 30 materials commonly found in makerspaces and workshops.

PhD student Martin Nisser wants to democratize hardware by making it easier to build and customize.

MIT researchers employ machine learning to find powerful peptides that could improve a gene therapy drug for Duchenne muscular dystrophy.

Two research projects on the design of state-of-the-art hardware could one day power next-generation 5G and 6G mobile networks.

A human-aware motion planning algorithm addresses the safety gap in collaboration between robots and humans.

CSAIL created a new method to computationally optimize the shape and control of a robotic manipulator for a specific task.