AI Is Pushing the Limits
Computing is moving from the data center to the edge at a record-breaking rate due to the expansion of connected devices and the necessity for real-time data processing. Edge AI is already participating, revolutionizing company operations and enabling decision-making that is swift and effective.
Advancements in edge intelligence
Edge AI lessens dependency on connection, decreases latency, frees up bandwidth constraints, and solves security as processing power comes closer to the data source. This offers up a wide range of opportunities, including predictive maintenance in manufacturing, AI-powered medical equipment, and energy forecasting.
How does it function?
Like anything else, it begins with the need for the appropriate tools. Preferably, these tools should be turnkey, able to integrate into your current processes with ease, and be tailored to your specific requirements. You won’t be shocked to learn that we have a fantastic answer.
IoT gateways, production lines, information/sale points, and vehicle systems are examples of edge devices that must function with constrained processing capacity, power, cooling, and connection. Additionally, they sometimes have little or no on-site technological competence and are difficult to reach. To fulfill these needs, you’ll need a versatile platform that can reliably serve various workloads across devices and places.
OpenVINO with Core Computing
The processors that are pushing the limits of Edge AI include Intel Core and Intel Xeon Scalable processors with integrated AI accelerators (AMX). The free, open-source toolkit known as OpenVINO was created to assist you in developing and deploying a deep learning model from a framework. With the help of oneAPI-powered open-source software libraries and APIs, Intel enables its partners to develop more quickly while advancing the capabilities of edge AI applications.
Guise AI
Manufacturing, energy, and logistics are among of the most important sectors in the world, and Guise AI is a software business on the leading “edge” of artificial intelligence (AI).
Guise AI created a “automated visual inspection” presentation for Red Hat Summit 2023. In comparison to TFLite, they were able to process 62% more frames per second utilizing OpenVINO to suit their real-time inference requirements.
Guise AI solutions take use of the device edge’s benefits. Their in-house, edge AI-enabled solutions provide low latency, quick reaction times, high privacy and security, affordable data transport, and effective use of network capacity where data is created.
A complete edge management platform is needed for edge scaling. A no-code platform called Guise EdgeOps is designed to deploy, coordinate, and manage AI workloads at the edge in a totally safe setting. AI is also about iteration, and Guise EdgeOps gathers inference and drift data from edge devices in a safe manner to create a unified data store that makes it possible to retrain models at the edge and to use a rich hybrid cloud. The Unified Data Store delivers increased “speed to ROI” with quicker POCs and steadily more accurate models in production, and it lets a company pick their data gravity.
Red Hat
Red Hat Device Edge provides an edge-optimized operating system built from Red Hat Enterprise Linux, a lightweight Kubernetes orchestration solution built from the edge capabilities of Red Hat OpenShift, and an enterprise-ready and supported distribution of the Red Hat-led open-source community project MicroShift. Regardless of where devices are placed, customers using Red Hat Device Edge may ensure operational and development consistency across edge and hybrid cloud environments.
OnLogic
Whereas conventional server hardware is too large or too hot, OnLogic hardware is suitable. OnLogic’s industrial computers can help with it. Global computer maker OnLogic creates highly customizable, solution-focused solutions that are built for dependability at the edge. They enable companies to overcome difficult implementation issues for complicated AI across all industries while operating in the hardest settings on earth.
Putting everything together
Here’s how businesses may choose their own ideal configuration:
Utilize the OpenVINO toolbox to optimize the unique edge workloads of Guise AI;
Utilizing the Guise EdgeOps platform, deploy and manage edge use cases;
Profit from Red Hat Device Edge’s strength and usability; then, run everything on Intel processors in OnLogic industrial computers.
The Outcome Establish a reliable supply chain while lowering risk and using cutting-edge technology to meet the current business realities.
AI is now attainable, not aspirational. A customizable Edge AI solution has been developed by Intel, Red Hat, OnLogic, and Guise AI to address your edge demands in any sector.
