Multimodal AI
AI that can work with more than one kind of input, such as text, images, sound, and sometimes video, rather than text alone. You might show it a photo and ask a question about it, or have it describe a picture in words. AI that handles several formats like this is called multimodal AI.
The word “modal” here refers to a mode, meaning a type of information: written text is one mode, images are another, and audio is another again. Early AI tools usually handled only one. Multimodal AI can take in and work across several at once, which makes it far more flexible and closer to how we naturally communicate.
In practice this opens up some genuinely useful things. You can photograph a handwritten note and ask the AI to type it up, snap a picture of a broken appliance and ask what the part is called, or paste a chart and ask it to explain the trend. The AI is reading the image and your words together, then answering with both in mind.
This blending of formats is why AI has started to feel less like a text box and more like a capable assistant. It matches how you already think, where a question might involve a picture, a document, and a spoken note all at the same time.
Most leading chat tools are now multimodal to some degree, building on the same large language model foundations and the wider world of generative AI. If a tool lets you upload a photo or speak to it as well as type, you are using multimodal AI.