Multimodal AI Breaks at the Tokenizer, Not the Model

TL;DR — The gap between a multimodal demo and a production system isn't model capability — it's the token economics of turning video and audio into sequences the transformer can read. Naive frame sampling and fixed-window audio chunking quietly blow up cost, latency, and accuracy long before the language model does any reasoning. Treating modality ingestion as a retrieval problem, not a context-stuffing problem, is the fix most teams skip. Every multimodal demo follows the same script: drop in a short clip, ask a question about it, watch the model nail it. Then someone tries it on a forty-minu