Meta, led by Mark Zuckerberg, Meta Introduces a new artificial intelligence (AI) model that can recognize specific items in photos. In addition to the model, Meta has published a dataset of image annotations that they claim is the largest of its kind to date.
The Segment Anything Model (SAM), according to a recent blog post by Meta’s research division, is a sophisticated object detection model built by the business. SAM is designed to detect items within photos and videos, even if they were not encountered during training. This state-of-the-art object identification system can help users recognize things in photos and videos despite never having seen them before during the training phase.
The user can choose an item either by clicking on it or by typing in its name, such as “cat” or “chair,” etc. In response to the textual request, SAM was able to appropriately draw boxes around various cats in a photograph during a demonstration.
Meta has utilized SAM-like technologies internally for activities such as tagging photographs, censoring restricted content, and recommending posts to Facebook and Instagram users. The corporation has indicated that the distribution of SAM will increase access to this type of cutting-edge technology outside its own operations.
The organization has made the SAM model and dataset downloadable under a non-commercial license. Anyone who adds their own photographs to the prototype must nonetheless agree to use the tool solely for research reasons.
Meta has provided a non-commercial license for the SAM model and dataset. Those who contribute photographs to the prototype, however, must consent to their usage solely for scientific investigation.
In a blog post, Meta argued that SAM might be put to use in any number of fields where locating and segmenting objects in images is a common need. SAM has the potential to be integrated into bigger AI systems for general multimodal knowledge of the world, such as interpreting the visual and textual content of a webpage.
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Also, SAM could be used in the augmented reality/virtual reality space, allowing users to “raise” an object into 3D based on where they are looking.
According to the business, SAM has many potential uses for content makers, such as the ability to extract image sections for use in collages and video editing.
The business claims that in the future, SAM could be utilized to assist applications in a variety of fields that involve locating and segmenting any object in any image. For the AI research community and others, SAM could become a component of larger AI systems for more general multimodal awareness of the world, such as comprehending the visual and textual content of a webpage.
In addition, the model may prove valuable for scientific study, enabling scientists to detect and monitor animals or other things of interest inside video recordings of natural phenomena on Earth or in space.