Rapidly Deploy AI to Thousands of Edge Locations

EDJX and Zeblok Computational promise an AI MicroCloud.

This week, decentralized global serverless edge computing company EDJX and AI company Zeblok Computational announced a partnership to integrate the EDJX Platform with Zeblok’s Ai-MicroCloud. The former offers engineers a decentralized operating system, EdjOS, that is tailored to the development of IoT, AI and machine to machine (M2M) applications. Ai-MicroCloud is a cloud-native, turnkey machine learning (ML) ops platform that specializes in deploying AI applications to thousands of edge locations. 

 (Image courtesy of Bigstock).

(Image courtesy of Bigstock.)

“EDJX’s strategic alignment with Zeblok combines capabilities that bring to market unsurpassed competitive differentiation, scaling and value for both of our customers for delivering new edge and AI applications,” said Benjamin Thomas, EDJX CEO.

The EDJX Platform offers compute, network and storage tools while Ai-MicroCloud makes it easier to scale and deploy AI applications at the edge. Meanwhile, EdjOS will help developers create, evaluate and deploy applications throughout the Internet of Things (IoT). It also enables the serverless distribution of compute resources for these applications.

Why Engineers Need to Pay Attention

With both of EDJX and Zeblok’s technology together, engineers will be better equipped to help cloud service providers, ORMs, ISVs and other businesses offer AI technology, from cloud-to-edge, for smart cities, Industry 4.0, smart transportation, logistics and even smart retail applications.

“By 2035, there will be one trillion Edge devices, requiring many millions of Multi-Access Edge Computing data centers (MECs), with most data created and acted upon at MECs,” said Zeblok Computational CEO Mouli Narayanan. “Zeblok’s Ai-MicroCloud integration with the EDJX decentralized edge mesh will give Zeblok customers a global serverless edge pathway to scale next-gen AI applications.”

As a result, engineers can curate and aggregate AI assets like algorithms, third-party ISVs and models into a custom app store for easy access, workflow automations and rapid product development. In other words, they can use repeatable application lifecycle management processes at lower costs.

Written by

Shawn Wasserman

For over 10 years, Shawn Wasserman has informed, inspired and engaged the engineering community through online content. As a senior writer at WTWH media, he produces branded content to help engineers streamline their operations via new tools, technologies and software. While a senior editor at Engineering.com, Shawn wrote stories about CAE, simulation, PLM, CAD, IoT, AI and more. During his time as the blog manager at Ansys, Shawn produced content featuring stories, tips, tricks and interesting use cases for CAE technologies. Shawn holds a master’s degree in Bioengineering from the University of Guelph and an undergraduate degree in Chemical Engineering from the University of Waterloo.