Cross-platform deployment and characterization of an on-device generative conversational agent
1-s2.0-S1383762126002997-mainDownload
EDGE AI FOUNDATION Working Groups are populated by industry partners and academia to drive cross industry initiatives and best practices in a neutral and collaborative environment. Working Groups are open to Strategic Partners and Academia.
1-s2.0-S1383762126002997-mainDownload
In places with unreliable networks and no data-center infrastructure, smaller is better Small Language Models Power Life-Saving Small AI - IEEE Spectrum Small Language Models Power Life-Saving Small AI - IEEE SpectrumDownload
https://latentai.com/wp-content/uploads/2026/08/Edge-AI-Software-Supply-Chain-Visibility.pdf
https://www.mdpi.com/2076-3417/16/16/8157
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.