New CSAIL work shows that traffic would flow faster if drivers kept an equal distance between cars

Today four MIT faculty were named among the Association for Computer Machinery's 2017 Fellows for making “landmark contributions to computing.”

Artificial intelligence (AI) in the form of “neural networks” are increasingly used in technologies like self-driving cars to be able to see and recognize objects. Such systems could even help with tasks like identifying explosives in airport security lines.

Light lets us see the things that surround us, but what if we could also use it to see things hidden around corners? It sounds like science fiction, but that’s the idea behind a new algorithm out of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) — and its discovery has implications for everything from emergency response to self-driving cars.

While 3-D movies continue to be popular in theaters, they haven’t made the leap to our homes just yet — and the reason rests largely on the ridge of your nose.

In recent years, a host of Hollywood blockbusters — including “The Fast and the Furious 7,” “Jurassic World,” and “The Wolf of Wall Street” — have included aerial tracking shots provided by drone helicopters outfitted with cameras. Those shots required separate operators for the drones and the cameras, and careful planning to avoid collisions. But a team of researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and ETH Zurich hope to make drone cinematography more accessible, simple, and reliable.