MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has developed a single system called Masked Generative Encoder (MAGE) that can handle both image recognition and generation tasks with high accuracy. Previously, building an image recognition or generation system required two separate processes, state-of-the-art generative modelling and self-supervised representation learning. However, MAGE does both by using a pre-training approach called masked token modelling. Researchers from MIT plan to perfect the technology further and expand its capabilities. It currently supports conditional image generation that allows users to specify criteria for the images they require. MAGE could have applications in industries like photo editing, visual effects and post-production.
MAGE: MIT’s Advanced System for Generating and Recognizing Images
Date:
Frequently Asked Questions (FAQs) Related to the Above News
Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.
More like thisRelated
Samsung Unpacked Event Teases Exciting AI Features for Galaxy Z Fold 6 and More
Discover the latest AI features for Galaxy Z Fold 6 and more at Samsung's Unpacked event on July 10. Stay tuned for exciting updates!
Revolutionizing Ophthalmology: Quantum Computing’s Impact on Eye Health
Explore how quantum computing is changing ophthalmology with faster information processing and better treatment options.
Are You Missing Out on Nvidia? You May Already Be a Millionaire!
Don't miss out on Nvidia's AI stock potential - could turn $25,000 into $1 million! Dive into tech investments for huge returns!
Revolutionizing Business Growth Through AI & Machine Learning
Revolutionize your business growth with AI & Machine Learning. Learn six ways to use ML in your startup and drive success.