Simplifying AI for Edge Compute with HAMi

Open-source agents like Hermes and OpenClaw can reason and use tools, but edge deployment is still hard - not the model, the compute underneath: limited memory, tight power budgets, no ops team. Democratizing agentic AI means fixing the compute layer. This deep dive covers GPU and memory slicing at the edge: carving one device's unified memory so multiple agents run concurrently on hardware as small as an NVIDIA Jetson, and time-sharing when demand exceeds memory. We compare Jetson-class GPUs with NPUs from Axelera and DeepX - higher performance per watt - and what it takes to make them schedulable. HAMi, the CNCF Incubation project for hardware-agnostic GPU virtualization, is that layer: one scheduling plane across heterogeneous accelerators, fine-grained memory slicing, open source. A blueprint for edge AI without a cloud budget.