Edge Computing
How Edge Computing is Transforming Enterprises
April 13, 2023
Computer Vision works best when it is focused on a specific task and optimized for a specific
context. Cameras that look out your front door (at your porch and driveway) are doing a different
job to the camera looking down on your backyard from the roofline. Both watch for people to keep
you safe, but in the world of AI these are very different tasks.
CVOps is the enterprise software process for delivering the right Computer Vision to the right
camera at the right time. A reliable, accurate CV system needs to collect data over time (to deal
with factors like “Data Drift” and “Model Drift”), and to deliver software updates that adapt to the
changing realities of our physical world.
CVOps is best enabled by specialty software that securely and reliably manages the “learning loop”
of data collection, AI updates, deployment, and monitoring.
CVOps is a new category and Orchestrait (the AI management platform within this category) is a new way of doing things.
Orchestrait gives you the ability to create and manage your own IP instead of getting someone to do it for you. This is a groundbreaking option that, until now, hasn’t even existed.
With Orchestrait, you can create custom AI and take control of your own AI destiny
Early solutions in AI based Computer Vision required massive compute infrastructure and had to be executed in the cloud. These systems required exponentially more data and computing power to accurately address the diversity of the real world.
Technology trends of Edge Deployment and Ensemble AI emerged to address the problems of AI bloat – but created a new challenge in the logistics of matching data and AI to the cameras and use cases.
CVOps is an enterprise function incorporating the best practices of data collection, AI updates, release management, and performance monitoring to ensure high quality service and excellent customer experience.
CVOps describes the enterprise business process, job role, and enabling tools for delivering Computer Vision in production.
A reliable, accurate CV system needs to collect data to deal with factors like “Data Drift” and “Model Drift,” and to deliver software updates that adapt to the changing physical world. CVOps delivers the correct Computer Vision to the correct camera at the correct time.
Past solutions in AI based Computer Vision needed immense compute infrastructure and had to execute in the cloud. These systems required exponentially more data and computing power to accurately address the diversity of the real world.
Technology trends of Edge Deployment and Ensemble AI were created to address the issue of AI bloat - but they also created new challenges in the logistics of matching data and AI to the cameras and use cases.
CVOps is best enabled by specialty software that securely and reliably manages the “learning loop” of data collection, AI updates, deployment, and monitoring.
December 28, 2022
Introducing Orchestrait: Face recognition at the edge for smart home devices SAN FRANCISCO, December 28, 2022 /PRNewswire/ — Orchestrait is the world’s first privacy-safe face recognition solution that uses state-of-the-art artificial intelligence (AI) at the edge to ensure full compliance with biometric data and privacy laws across the world. By processing data on edge – […]
March 14, 2022
Xailient specializes in extremely efficient low-power computer vision. Intel's OpenVINO specializes in maximizing the performance and speed of computer vision AI workloads. OpenVINO improved Xailient FPS 9.5x on Intel hardware to 448 FPS. Together, Xailient-Intel outperforms the comparable MobileNet_SSD by 80x. Even after Intel worked the OpenVINO magic on MobileNet_SSD, Xailient-OpenVINO is 14x faster.
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Edge Computing
Edge Computing
We empower companies to bring computer vision AI products to market
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