{"id":6506,"date":"2022-12-31T01:41:57","date_gmt":"2022-12-31T01:41:57","guid":{"rendered":"https:\/\/cms.idc-custom.com\/?post_type=idcproduct&p=6506"},"modified":"2023-01-18T15:28:25","modified_gmt":"2023-01-18T15:28:25","slug":"microsoft-general-purpose-computer-vision-ai-software-platforms-2022-vendor-assessment","status":"publish","type":"idcproduct","link":"https:\/\/cms.idc-custom.com\/idcproduct\/microsoft-general-purpose-computer-vision-ai-software-platforms-2022-vendor-assessment\/","title":{"rendered":"Microsoft – General-Purpose Computer Vision AI Software Platforms 2022 Vendor Assessment"},"content":{"rendered":"\r\n<\/a>\n\n\n
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\r\n\t\tIDC MarketScape: Worldwide General-Purpose Computer Vision AI Software Platforms 2022 Vendor Assessment\t<\/h3>\r\n\r\n
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IDC Opinion<\/h2>\n\n\n\n

The human vision system, which gathers and interprets information through sight, remains a critical aspect as part of one’s life as both a consumer and an employee (i.e., working as part of a private business or government entity). Vision is critical to performing routine tasks like navigating roadways and sidewalks; identifying, classifying, and interacting with objects and environments; and engaging with computers and digital devices. Human vision continues to develop and be fine-tuned by technology to support an ever-increasing range of dynamic events and human experiences. Yet, as our society continues to invest in R&D to advance and deploy new technology and automation techniques, there are increasing opportunities for businesses and consumers to leverage or pair (i.e., in a cooperative or human-in-the-loop manner) human sight with computer-driven sight (referred to as computer vision [CV] or computer vision artificial intelligence [CV AI]) to take the next step in delivering improved productivity, efficiency, safety, sustainability, and inclusivity.<\/p>\n\n\n\n

CV has been a strong beneficiary of academic and commercialization investments to advance the fields of deep learning\u2013 and machine learning (ML)\u2013based approaches to AI. These advancements, which have largely occurred over the past five years, look to abstract the human intelligence schema and system to interpret unstructured data in the forms of images, videos, and sensor data (e.g., radar, lidar) through complex neural networks. To develop this neural network architecture, CV technology user organizations require massive amounts of use case\u2013specific or even generalizable training data, as well as extensive computational resources (including GPUs, TPUs, and hardware- and software- based accelerators) to train, build, and validate models that can “learn” details and characteristics from new, unstructured visual-based inputs. This approach to solving CV AI has led to breakthroughs where computers are now able to surpass the quality and efficiency of humans for multiple discrete use cases, along with delivering differentiated benefits versus humans in the areas of scale, repeatability, longevity, attentiveness, and subjectivity (to name a few).<\/p>\n\n\n\n

Although deep learning\u2013based CV is a very new technology area, IDC has seen tremendous progress in its use by organizations of all sizes and across all verticals. This includes support for (or even potentially enabling new) business and consumer use cases that can deliver insights in the areas of:<\/p>\n\n\n\n