Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have introduced a computer vision system that combines image recognition and image generation technology into one training model instead of two. The result, MAGE (short for MAsked Generative Encoder) holds promise for a wide variety of use cases and is expected to reduce costs through unified training, according to the team. “To the best of our knowledge, this is the first model that achieves close to state-of-the-art results for both tasks using the same data and training paradigm,” the researchers said. Continue reading MAGE AI Unifies Generative and Recognition Image Training

Waiting for a video to buffer may become an annoyance of the past. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are working on streaming algorithms that use AI to improve load rates and, thus, reduce buffering. Dubbed Pensieve, the new technology relies on machine learning to navigate the often-chaotic and ever-changing conditions of networks in real-time, based on a system of rewards (when the video loads smoothly) and penalties (when it’s interrupted). Meanwhile, Netflix is working on its own AI solution to address buffering. Continue reading MIT and Netflix Testing AI-Based Algorithms to Curb Buffering

MIT’s Computer Science and Artificial Intelligence Lab (CSAIL), with Israel’s Weizmann Institute of Science, released the prototype of a 3D display technology, for use in movie theaters, that doesn’t require glasses. Other glasses-free 3D displays have been available, most notably with the Nintendo 3DS, but they are designed for use by a single user and only work when the content is viewed at a specific angle. A research paper on the technology, dubbed “Cinema 3D,” will be given at the SIGGRAPH conference this week. Continue reading MIT Prototypes Glasses-Free 3D for Motion Picture Theaters