Meta has released a new artificial intelligence model that can pick out individual objects in images, presenting a big step forward in image recognition.
The Segment Anything Model (SAM) can “cut out” objects in an image, Meta claimed on its website for the model.
Users may initially think the model aims to help edit photos, but the purpose is to try to improve image analysis and segmentation, to isolate parts of the image, which can be “cut” and put in a side tray for copying and pasting into other programs.
The program can even work on videos and even works on media that it has not encountered during training.
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SAM is a computer vision AI program, meaning it focuses on enabling computers and systems to pick out information from visual data — pictures, videos and other media — and then act on it. The field is working on refining the ability to identify and pick out objects within this media, which SAM allows.
Meta CEO Mark Zuckerberg has said that incorporating such generative AI “creative aids” into Meta’s apps is a priority this year.
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Visitors walk in front of the Meta sign at its headquarters in Menlo Park, Calif., Dec. 29, 2022. (Tayfun Coskun/Anadolu Agency via Getty Images)
Meta does already use technology similar to SAM internally for activities like tagging photos, moderating prohibited content and determining which posts to recommend to users of Facebook and Instagram.
The company said SAM’s release would broaden access to that type of technology as the company plans to make the model and dataset available for download under a noncommercial license.
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Mark Zuckerberg, CEO and founder of Facebook Inc., speaks during the Silicon Slopes Tech Summit in Salt Lake City Jan. 31, 2020. (George Frey/Bloomberg via Getty Images)
Tech blog Encord noted that the program provides a number of enhancements, which it labeled as “groundbreaking” for image work, mainly the ability to more quickly and accurately label, annotate and identify objects in an image. That can help distinguish parts of single objects in images as well. Examples include distinguishing different parts of the brain within a single image of an X-ray.
The blog claimed the improved computer vision capabilities will eventually yield significant applications within agriculture, such as remotely guiding large harvester vehicles by linking them with AI-guided drones that follow from the air and medical imagery and geospatial imagery.
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Even more exciting may be the application for sports analytics, which will help better understand player movements in games and training, providing coaches, trainers and scouts better insights into a wider range of aspects of the game they might not have had the same focus on.