Multimodal AI

What is Multimodal AI?

Multimodal AI refers to artificial intelligence systems that can process, understand, and generate content across multiple types of data (modalities) — including text, images, audio, video, and code — within a single unified model.

The breakthrough of multimodal AI is that these models don't just handle each modality separately; they understand the relationships between modalities. A multimodal model can look at a photo and describe it, listen to audio and transcribe it, or watch a video and answer questions about what happened.

Leading Multimodal Models

Code Example — Vision with OpenAI

from openai import OpenAI

client = OpenAI()

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Describe this image in detail"},
            {"type": "image_url", "image_url": {
                "url": "https://example.com/photo.jpg"
            }}
        ]
    }]
)
print(response.choices[0].message.content)

Applications