Multimodal sounded exciting but integration turned complex

Multimodal systems sound simple in theory because they promise one model that can understand text, images, audio, or video together. In practice, integration creates a new set of problems around alignment, latency, preprocessing, and evaluation.

Each modality has its own failure modes. An image may be high quality but context-poor, audio may be noisy, and text may not fully explain what the other signals mean. The system has to reconcile all of that before it can respond well.

The complexity is worth it when the use case truly needs multiple forms of input. But if the product only needs one signal, multimodal can add cost and confusion without enough payoff.