Multi-Modal

Multi-modal (or multimodal) refers to systems or methods that can process or integrate multiple types of data, typically from different modalities such as text, image, audio, video, and other sensory inputs. Multi-modal systems aim to understand and generate outputs based on this diverse, merged information, mimicking human perception, where we simultaneously use different senses (e.g., seeing, hearing, and reading) to interpret the world.

In machine learning and AI, multi-modal models combine data from different modalities to improve the performance of tasks like classification, generation, captioning, and more. For example, an AI model that processes both images and text could interpret and respond to visual and written information in a cohesive and context-aware manner.

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