Episode description

Across all industries, businesses actively adopt computer vision to improve operations, elevate user experiences, and optimize overall efficiency. Image segmentation stands out as a key approach, enabling various applications such as recognition, localization, semantic understanding, augmented reality, and medical imaging. To make it easier to develop these types of applications, Meta AI released the Segment Anything Model (SAM)—an algorithm for identifying and segmenting any objects in an image without prior training.

In this podcast, we look at the evolution of image segmentation, what the launch of Meta AI’s Segment Anything model means to the computer vision community, and how developers can leverage OpenVINO™ to optimize for performance.

Join us as we explore these ideas with:
Paula Ramos, AI Evangelist, Intel
Christina Cardoza, Editorial Director, insight.tech

Paula answers our questions about

• The importance of image segmentation to computer vision
• Traditional challenges building image segmentation solutions
• What value the Segment Anything Model (SAM) brings
• Business opportunities for image segmentation and SAMs
• The power of OpenVINO to image segmentation
• The future of OpenVINO and Segment Anything

Related Content

To learn more about image segmentation, read Segment Anything Model — Versatile by Itself and Faster by OpenVINO. For the latest innovations from Intel, follow them on X at @IntelAI and on LinkedIn.