Multimodal LLMs Basics: How LLMs Process Text, Images, Audio & Videos

Multimodal Large Language Models overcome AI's traditional limitation of processing only one type of data by converting text, images, audio, and video into unified mathematical representations called embedding vectors. These systems use vision transformers to treat image patches like text tokens, audio encoders to convert sound into visual spectrograms, and projection layers to align different data types into a shared mathematical space where a single transformer can reason across all modalities simultaneously.