A camera-trap project in the Serengeti asks a frozen language model about bursts of frames from a frozen image encoder. A small Q-Former squeezes each frame into a few learned query tokens, while an MLP projector passes every patch. Then project every patch of 64 frames, keep only 4 queries, or let the queries ignore the question. This lesson needs JavaScript.