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.
Adversarial machine learning involves studying and defending AI models against attacks or adversarial examples designed to deceive the system. By understanding vulnerabilities and deploying…