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