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.
Human-in-the-loop refers to a collaborative approach where humans and AI systems work together to achieve optimal results. It involves combining human expertise, judgement, and…