Multimodal AI
AI systems capable of processing and correlating multiple types of data such as text, images, and audio.
Detailed Definition
Multimodal AI refers to AI systems that can simultaneously understand, process, and correlate information from multiple different types of data sources (modalities), such as text, images, audio, video, or even sensor data. Unlike unimodal AI that processes only single types of data, multimodal AI can more comprehensively understand the world and perform more complex tasks, such as generating descriptions based on images, controlling image editing through voice commands, or identifying objects in videos and describing their behaviors. GPT-4V is an example of multimodal AI. These systems represent a significant step toward more general artificial intelligence that can interact with the world in ways similar to human perception and understanding.
Advanced ConceptsMore in this Category
Artificial General Intelligence (AGI)
A hypothetical type of AI that matches or exceeds human cognitive abilities across all domains.
Cognitive Computing
AI systems that simulate human thought processes, emphasizing learning, reasoning, and natural interaction.
Foundation Model
Large-scale AI models trained on diverse data that serve as the basis for various downstream applications.
RAG (Retrieval-Augmented Generation)
A technique that enhances AI responses by retrieving relevant information from external knowledge sources.