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.
Neuroevolution is a type of AI learning that combines neural networks and evolutionary algorithms. Neuroevolution algorithms evolve neural networks over generations, adapting them to…