Vision, Language, and Multimodal AI
Vision, Language, and Multimodal AI Vision, language, and other senses come together in modern AI. Multimodal AI combines images, text, and sometimes sound to understand and explain the world. This helps systems describe what they see, answer questions about a scene, or follow instructions that mix words and pictures. The field is growing, and today we see practical tools in education, design, and accessibility. Two ideas stand out. First, shared representations align what the model sees with what it reads. Training on large sets of image-text pairs helps the model connect words to visuals. Second, flexible learning comes from multitask training, where the same model learns image captioning, question answering, and grounding tasks at once. Together these ideas make models more capable and less fragile when facing new image or text prompts. ...