Multimodal AI
Multimodal AI refers to artificial intelligence systems that can process, understand, and generate information across multiple types of data, such as text, images, audio, and video.
What is Multimodal AI?
Multimodal AI combines information from different modalities to understand inputs and produce more comprehensive responses. For example, a model may analyze an image along with a text prompt, interpret spoken language, or generate text based on visual and audio information. These systems can use different models or a unified model to process multiple data types.
Why is Multimodal AI Important?
Multimodal AI allows systems to work with information in forms that more closely resemble how people communicate and interact with the world. It can improve the usefulness of AI applications by combining complementary information from multiple sources and enabling richer interactions.
Common use cases
Multimodal AI is commonly used for visual question answering, document analysis, speech assistants, image and video understanding, content generation, accessibility tools, and AI agents.