Multimodal Learning

Multimodal learning is a method where computers analyze and combine information from different sources or types of data—like images, text, audio, or videos—to better understand and interpret complex information. By integrating these diverse inputs, the system gains a more comprehensive view, similar to how humans use multiple senses to perceive the world. This approach improves tasks such as speech recognition, image captioning, and sentiment analysis, making AI more accurate and versatile in real-world applications.