What does "Multimodal Generative AI" refer to?

"Multimodal Generative AI" refers to models that have the capability to process and generate multiple types of data inputs, such as text, images, audio, and more, either simultaneously or independently. This ability allows for richer interactions and more versatile applications since the AI can take advantage of the different characteristics of each data type.

Such models integrate various forms of input to produce coherent and contextually relevant outputs. For example, a multimodal AI system might take an image and a textual description as input and then generate a detailed report or a creative piece that incorporates elements of both, enhancing the overall quality and applicability of the generated content.

By focusing on integrating and generating across different modalities, these AI systems enable more complex interactivity and richer user experiences, moving beyond the limitations imposed by singular input or output types. This is what sets multimodal systems apart from those that are restricted to text-only, structured data, or a single output format.