Systems, devices, and methods related to a Deep Learning Accelerator and memory are described. For example, a data storage device may be configured to execute instructions with matrix operands and configured with: an interface to receive a video stream; and random access memory to buffer a portion of the video stream as an input to an Artificial Neural Network and to store instructions executable by the Deep Learning Accelerator and matrices of the Artificial Neural Network. The Deep Learning Accelerator can execute the instructions to generate an output of the Artificial Neural Network, including analytics of the buffer portion. A video encoder in the data storage device may use the analytics to compress the portion of the video stream for storing in the device.