Multimodal

Multimodal AI refers to systems that can process and generate more than one type of data. While early AI models were usually "unimodal" -- a text model could only handle text, an image model could only handle images -- modern multimodal models can work across multiple formats. You can show them a photo and ask a question about it, or give them text and have them generate an image, audio, or even video.

This matters because the real world is not just text or just images -- it is everything all at once. When you look at a restaurant menu with photos, you are processing text and images simultaneously. Multimodal AI can do the same thing. You can upload a screenshot of an error message and ask the AI to help you fix it. You can share a photo of a plant and ask what species it is. You can even describe a scene and get back an image, audio narration, or video.

GPT-4, Claude, and Gemini are all multimodal -- they can understand both text and images. Gemini can also process audio and video. Models like DALL-E and Midjourney are multimodal in the other direction: they take text and produce images. ElevenLabs takes text and produces speech. This cross-format ability is becoming a standard feature of modern AI rather than a special bonus.

The trend is moving toward models that seamlessly handle every type of media. Instead of needing separate tools for text, images, and audio, you might eventually have one AI assistant that naturally works with all of them, just like a human does.