What do multimodal models process?

Multimodal models are designed to handle and analyze data from various sources simultaneously. This capability allows them to integrate and understand diverse types of inputs, which can include images, text, audio, and video. By processing multiple modalities, these models can create richer representations and context, enabling more sophisticated analyses and generating more nuanced outputs. This characteristic is particularly valuable in applications such as multimedia content analysis, where combining visual and textual data can lead to enhanced understanding and insights that would not be achievable by analyzing just one type of data alone.

The other choices entail limitations in what the models can process. For instance, the first option suggests that only text inputs are processed, which contradicts the definition of multimodal models. The option focusing solely on audio inputs also misses the broader capability of these models to integrate other modalities. The choice referencing only structured databases narrows the data types too much, ignoring the flexibility and adaptability of multimodal models in dealing with unstructured data such as images and videos. Therefore, the correct answer reflects the comprehensive nature of multimodal models, encompassing a wide array of input types for multifaceted analyses.