Artificial Intelligence

Top 10 Edge AI Hardware Makers to Lookout For in 2022

Sayantani Sanyal

Edge AI is currently one of the most trending technologies that business enterprises are using

Enterprise leaders are now carefully deploying cloud technologies as it promises the chance of getting a highly scalable centralized compute power. Edge AI seems like one of the major technologies that is making huge strides in the tech sector. The growth of the global edge AI hardware market is anticipated to be driven by factors that include the emergence of artificial intelligence coprocessors for edge computing and the rise in IoT applications by distinct industries such as automotive, consumer electronics, and others. Edge AI products are some of the most widely used technologies that are used by enterprise leaders. The technology is integrated into devices like smartphones, robots, wearables, smart speakers, and others. Edge AI companies are delivering advanced processors and hardware that would make the enterprise leaders more efficient and productive. In this article, we have listed the most popular edge AI makers that you can follow in 2022.

AWS provides cloud-edge hybrid hardware solutions that enable consistent, immersive consumer experience on both the cloud and the edge. AWS includes services and solutions that include IoT, AI, ML, robotics, and analytics to make sure that all business enterprises are achieving their business objectives effective.

Dell has extensively invested in edge computing and provides sophisticated edge AI hardware solutions. The Dell EMC offers edge-computing management and orchestration capabilities.

Only a few companies possess the amount of expertise and technical infrastructure that Google's edge computing sphere contains. Google has several consumers all over the world and provides cloud computing services for distinct industries. Google uses Edge TPU hardware to run analytics and AI at the edge.

ClearBlade provides ClearBlade Edge and ClearBlade platforms, enabling enterprises to deliver long-lasting edge computing locations to end-users as they seek to cut cloud transport costs, latency, or both. Its solutions are used by various industries like smart rail, smart monitoring, real-time location, and asset tracking.

IBM provides advanced solutions to businesses. Its range of IoT solutions for enterprise asset management facilitates the management and system engineering. The company boasts of providing the advantage of edge AI and classic computing solutions to distinct industries like telecommunications, retail, and automobile industries.

EdgeConneX focuses on enabling efficient placement of data crunching facilities for better network and IT connectivity. The idea behind EdgeConneX's solutions is to put edge AI at the forefront of all technologies. The company's EdgeOS technology is a self-service management application that is geared for high observability, with a single universal dashboard to manage it efficiently.

 With the help of 5G and edge computing technologies, the company serves thousands of cloud facilities and application instances. Aarna Networks solves several enterprise complications by providing an open-source orchestration, lifecycle management, and control loop automation solution.

ADVA holds a strong position in the edge ecosystem. The company aims to build and enhance its platform for edge computing applications. This includes adding features including broader support for COTS servers and NICS, dynamic orchestration, and improving secure networking.

Section is an edge computing platform focused on DevOps. The company's patent-pending Adaptive Edge Engine technology paves the way for complete edge computing. Section's edge computing platform empowers the next-generation smart applications for SaaS, PaaS, and application providers to generate immersive digital experiences.

ADLINK is a global provider of leading-edge computing solutions. ADLINK is popular for providing a comprehensive portfolio of optimized heterogeneous computing solutions including embedded MXM GPU modules and PCI Express graphics based on NVIDIA Quadro GPUs. These facilities enable edge systems to tap into the power of GPU computing.

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