In the Iron Man movies, Tony Stark uses a holographic computer to project 3D data into thin air, manipulate them with his hands, and find fixes to his superhero troubles. In the same vein, researchers from MIT and Brown University have now developed a system for interactive data analytics that runs on touchscreens and lets everyone — not just billionaire tech geniuses — tackle real-world issues.

Prime Minister Mark Rutte of the Netherlands recently visited MIT, taking an innovation-oriented campus tour with a focus on computing and robotics.

A team from MIT and IBM has now done exactly that with “GANpaint Studio,” a system that can automatically generate realistic photographic images and edit objects inside them. In addition to helping artists and designers make quick adjustments to visuals, the researchers say the work may help computer scientists identify “fake” images.

A team of researchers from MIT CSAIL and QCRI have developed a neural network that can look at an image of a pizza, determine the type and distribution of ingredients, and figure out the correct order to layer the pizza before cooking.

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.

MIT and the US Air Force have signed an agreement to launch a new program designed to make fundamental advances in artificial intelligence that could improve Air Force operations while also addressing broader societal needs.

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.