At GSX, Camio Unveils A Way To Run Sophisticated Vision AI Applications At ¼ The Cost Of Cloud
IP video manufacturers and solution providers can now orchestrate AI tasks using Kubernetes on edge chipsets for lower latency and reduced costs.
Camio announced at GSX a way to run sophisticated Computer Vision and AI workloads at the edge as Kubernetes clusters, reducing the costs of deploying security and business intelligence AI applications by 73%.
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“Even their DIY Detectors that exclude uniformed deliveries and staff run at the edge using industry standard IP cameras.”
Camio Flex, the new Cloud Native Kubernetes Video Management System alternative, runs AI anywhere along its video processing pipeline—from edge to cloud—to reduce hardware and automate critical storage, scale, and lifecycle management functions. General-purpose computing tasks—once reserved for sophisticated data centers—can be orchestrated at the edge, even across IP cameras on a 5G/CBRS network. Camio brings the billions of dollars invested by big tech cloud providers to existing IP cameras in the security industry.
Camio Flex also utilizes the latest advances in edge AI processors. For example, with the edge processing power of Qualcomm Technologies, Inc.’s system on a chip easily accessible from containers, Camio enables a cluster of IP cameras to work together to run AI tasks and data pipelines that exceed the real-time computational power of any single Node in the cluster. The resulting combination delivers one of the most cost-effective ways to run visual intelligence applications across security, retail, biotech, manufacturing, healthcare, and financial services.
The approach also supports Camio “Do-It-Yourself Detectors,” which are custom AI models created and deployed to the edge by end users themselves. “A large telecommunications customer is now able to get detailed in-store traffic analyses every 15 minutes from the IP cameras in each of their 1,500 stores at a fraction of the bandwidth and cost of running in the cloud,” said Carter Maslan, Camio CEO. “Even their DIY Detectors that exclude uniformed deliveries and staff run at the edge using industry standard IP cameras.”
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Camio, with support from Qualcomm Technologies, has prepared reference designs for camera and gateway manufacturers to run edge Nodes in Kubernetes clusters in order to move compute power to the edge for cost savings and lower latency. Camio Flex edge workload orchestration ensures devices never run into hard limits that could block the most demanding applications. Containers using the latest edge AI advances, like the Qualcomm® AI Stack, can be delivered instantly and frequently.
“Global Security Operations Centers are focused on their cost per monitored hour,” added Maslan. “With AI applications run at the edge as containers, GSOCs can run automated tailgating detection and alarm verification without worrying about high cloud costs or exceeding the peak compute capacity of single devices.” There are additional cost savings from the freedom to use off-the-shelf cameras, access control systems, storage providers, and computers.
Edge AI deployments powered by Camio Flex enable device manufacturers and solution providers to run sophisticated computer vision applications at ¼ the cost of running on cloud
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