Multi-Modal learning refers to AI models that learn from multiple sources of data, such as text, images, and audio. By incorporating information from multiple modalities, these models can capture richer and more comprehensive representations. Multimodal Learning finds applications in areas like sentiment analysis, image captioning, and video understanding.
Supervised Learning is a Machine Learning approach where models are trained using labelled data, with both input and output pairs. By learning from the…