OpenVINO™ Toolkit Accelerates CV Development across Intel® Platforms

The Internet of Things (IoT) is a growth business that is creating data-driven innovation opportunities for companies and developers worldwide. One of the driving factors behind the rapid growth in the global IoT market is the adoption of artificial intelligence (AI) technology by businesses seeking greater insight, as demonstrated by a dramatic increase in computer vision solutions at the edge.

According to recent industry reports:
• The overall computer vision market is expected to reach USD $17.38 billion by 20231 ,
• The video analytics market is estimated to reach USD $11.17 billion by 2022 , and
• Deep learning revenue is expected to grow from USD $655 million in 2016 to USD $35 billion by 2025 .

Introducing the OpenVINO™ Toolkit
To help developers take advantage of these trends, Intel is introducing the OpenVINO™ (Open Visual Inference & Neural network Optimization) toolkit, the latest offering in the comprehensive lineup of Intel® Vision Products that accelerate deep learning and transform vision data into business insights. The OpenVINO™ toolkit, in combination with Intel’s diverse portfolio of hardware and software, drives deep learning at the edge and positions Intel as the clear industry leader in enabling IoT solutions from the edge to the cloud.

The OpenVINO™ toolkit is designed to enable users to fast-track development of high-performance computer vision applications, unleash deep learning inference capabilities across the entire Intel silicon portfolio, and provide an unparalleled solution to meet their AI needs. The new toolkit also includes three major APIs: The Deep Learning Deployment toolkit, a common deep learning inference toolkit that scales across Intel® Vision Products, and optimized functions for OpenCV* and OpenVX*. With the addition of the OpenVINO™ toolkit to the Intel® Vision Product portfolio, Intel provides the only vision solution currently available with the capability to distribute AI solutions from the edge to the network to the cloud across a diverse set of products. Because OpenVINO is compatible with widely adopted AI frameworks, developers can seamlessly and effortlessly deploy their applications at the edge.

Computer Vision: Challenges and Opportunities
Developers who want to capitalize on computer vision and the opportunities it presents typically face several fundamental challenges. First, computer vision solutions often experience bandwidth, storage, and latency limitations. Second, it can be difficult to optimize computer vision applications to improve performance and efficiently

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