Whitepaper Release: Next Generation Edge — Architectures for AI and Machine Learning
Whitepaper Release: Next Generation Edge — Architectures for AI and Machine Learning
The white paper “Next Generation Edge: Edge Computing Architectures for Artificial Intelligence and Machine Learning Use Cases”, developed by the OpenInfra Edge Computing Working Group, is now available. CONFIDENTIAL6G is pleased to have contributed to this important resource, which provides a practical overview of how edge computing and AI are converging to support future applications.
As AI capabilities move closer to where data is created and used, edge architectures play a central role. Unlike traditional centralized AI systems, Edge AI needs to handle unique challenges such as latency constraints, data sovereignty, and stronger security requirements. Addressing these challenges requires careful architectural choices and a clear understanding of infrastructure design and operational needs.
The white paper covers several key areas:
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Architectural frameworks for enabling AI and machine learning at the edge.
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Security, latency, and data governance considerations, critical for real-world deployments.
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Collaboration and open source innovation as essential elements for building sustainable solutions.
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Deployment examples and lessons learned, offering insights into current practices and future directions.
Edge AI is already impacting various sectors, including manufacturing, healthcare, transport, and critical infrastructure. By bringing computing power closer to the source of data, organizations can improve responsiveness, reduce bandwidth usage, and maintain stronger control over sensitive information.
The document reflects a collective effort by researchers, engineers, and industry practitioners to guide the development of scalable, secure, and efficient edge computing environments that can support advanced AI workloads.
📄 Read the full white paper here: Next Generation Edge White Paper
Thank you to all the contributors from the OpenInfra Edge Computing Working Group who helped create this resource for the Edge + AI community: Beth Cohen, Buland Khan, David Solans Noguero, Flavio Esposito, Grigorios Chrysos, Ildiko Vancsa, Julian Thomas, Mahadev Satyanarayanan, Moshe Shadmon, Nenad Gligoric, Rajat Kandoi, Rob Hirschfeld, and Sayed Chhattan Shah.
For further updates on CONFIDENTIAL6G activities in edge computing and AI, follow our news and insights.