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Abstract Recent advancements in edge hardware enabled increasingly complex artificial intelligence workloads to be executed directly on resource-constrained devices. However, single-edge devices remain computationally limited compared with hybrid or cloud alternatives. This work presents a fully edge-based architecture implementing agentic AI on heterogeneous devices for home surveillance with a natural
RecursiveMAS, a recursive multi-agent framework that casts theentire system as a unified latent-space recursive computation 2604.25917v2Download
Every now and then, a survey paper appears that does more than summarize a research field—it attempts to define where that field is heading. The recently released survey Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions is one of those papers. Spanning more than
For many of us working in Edge AI, the name Coral brings back memories of one of the first platforms that made hardware-accelerated on-device machine learning genuinely accessible. The USB Accelerator, the Dev Board, and later the Dev Board Micro became reference platforms for countless prototypes, demos, and research projects.
Read the whitepaper here - https://www.edgeaifoundation.org/edgeai-content/smart-homes-werent-smart-edge-ai-changes-that
You can read the white paper here - https://www.edgeaifoundation.org/edgeai-content/introduction-to-the-edge-ai-foundation-taxonomy
The future of edge AI starts with today's researchers. Breakthroughs in edge AI don't happen by accident. They begin with curious students, dedicated researchers, and early-career innovators who are asking difficult questions and solving problems that will shape the next generation of intelligent systems.That's why the EDGE AI FOUNDATION Scholarship
Our academic community helps us prioritize, design, create, and publish world class edge AI certifications. Our catalog continues to grow, check back for more updates. https://cert.edgeaifoundation.org/collections
