Multimodal AI refers to AI systems that can process and understand multiple types of input, not just text. A multimodal model can work with text, images, audio, video, and other data types together. This is a big step forward from earlier AI that could only handle one type at a time.
Examples of Multimodal AI
- GPT-4o: Can analyze images you send along with a text question and respond intelligently
- Google Gemini: Handles text, images, code, audio, and video in one model
- Claude: Can read and analyze images alongside text inputs
Practical Uses for Website Builders
- Upload a screenshot of a website and ask an AI to critique the design
- Share a chart image and ask the AI to explain the data
- Describe a product with an image and let AI generate a product description
- Use AI to read scanned documents or infographics and extract information
Why It’s a Game Changer
Most real-world problems involve multiple types of information. Being able to combine them in one AI interaction makes workflows much faster. You don’t need separate tools for different data types.
Related: Artificial Intelligence
