Encoders, fusion, and decoders work together to understand diverse data.
A multimodal AI system consists of three main components. First, encoders convert raw data like text, images, sound, log files, videos, IoT sensor information, and time series into vectors stored in a latent space. Second, the fusion mechanism combines multiple types of data to find what’s most relevant. Third, decoders deliver information from the latent space into something we understand, for example, finding an image of a house. These components work together to process virtually any data type.
— Multimodal AI In 2025: From Healthcare To eCommerce And Beyond · Forbes