This paper proposes "split-brain" inference, where the video is processed partly on the camera, subject to a limit on computation. Then, intermediate values are transmitted, limited by network capacity, to a cloud datacenter for further DNN inference. The objective is to rely on the cloud for "overflow" capacity.