FPGA-AI - Khan BMS Battlefield Management System
FPGA-AI — FPGA ML Acceleration — is one of the unglamorous primitives modern BMS lives or dies on. Here is how Khan BMS engineers it.
Think of FPGA-AI the way a database engineer thinks of a write-ahead log: unglamorous, structural, and the reason the system is recoverable when something else fails.
Inside Khan BMS, FPGA-AI is exposed to mission planners as a capability bundle rather than a vendor SDK. The planner composes effects out of FPGA-AI-derived primitives; the integration path for new hardware is a manifest, not a code branch.
FPGA-AI is anchored at the Arban — ten nodes under one tactical leader. Small enough to reason about by hand, large enough to absorb the loss of a node without re-planning. Authority for FPGA-AI is bounded at this tier; nothing the Arban does can poison its parent.
Done right, FPGA-AI disappears into the background and the operator is free to think about the fight. That is the bar Khan BMS holds itself to.