Imagine yourself glancing at a busy street for a few moments, then trying to sketch the scene you saw from memory. Most people could draw the rough positions of the major objects like cars, people, and crosswalks, but almost no one can draw every detail with pixel-perfect accuracy. The same is true for most modern computer vision algorithms: They are fantastic at capturing high-level details of a scene, but they lose fine-grained details as they process information.

If a robot traveling to a destination has just two possible paths, it needs only to compare the routes’ travel time and probability of success. But if the robot is traversing a complex environment with many possible paths, choosing the best route amid so much uncertainty can quickly become an intractable problem.

Autonomous helicopters made by Rotor Technologies, a startup led by MIT alumni, take the human out of risky commercial missions.

An interdisciplinary team of researchers thinks health AI could benefit from some of the aviation industry’s long history of hard-won lessons that have created one of the safest activities today.

The system could improve image quality in video streaming or help autonomous vehicles identify road hazards in real-time.

In a first, researchers have observed how lithium ions flow through a battery interface, which could help engineers optimize the material’s design.

A new AI-based approach for controlling autonomous robots satisfies the often-conflicting goals of safety and stability.