any-modality LLM

An any-modality model is the ambitious end of the spectrum: one network that can accept text, images, audio, and video as input and also produce several of them as output — describe a photo in speech, generate an image from a paragraph, answer a spoken question with text. Instead of bolting a separate tool onto a language model for each task, the goal is a single unified system that fluidly mixes whatever modalities a conversation needs.

The unifying idea is to tokenise everything. If images, audio, and video can all be turned into discrete tokens from a shared vocabulary — the way text already is — then one transformer can read and write across modalities with the same next-token machinery. Output then runs back through modality-specific decoders that turn the predicted tokens into pixels or sound. Some systems instead route to specialist generators; the any-to-any label covers both unified and modular designs.

Generality costs quality. A jack-of-all-modalities often trails specialists at each one, and training such models is data-hungry and unstable. Truly seamless any-to-any systems are still an active research frontier, not a solved product.