Intermediate · Generative AI

Multi-Modal AI

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. AI systems that process and reason across multiple data types — text, images, audio, video — in a unified model.

Technical Definition

AI systems that process and reason across multiple data types — text, images, audio, video — in a unified model.

How it works

Multi-modal models encode each modality with specialized encoders, then align them in shared representation space. This enables image captioning, visual QA, text-to-image generation, and video understanding. Alignment is often learned through contrastive objectives.

Related Concepts

• Large Language Model (LLM) — A massive neural network trained on vast text corpora to understand and generate human language with remarkable fluency.
• Embedding — A dense vector representation that captures semantic meaning, mapping discrete items like words into continuous mathematical space.
• Vision Transformer (ViT) — An architecture that applies the Transformer to images by splitting them into patches and processing them as sequences.
• CLIP — A multi-modal model connecting images and text in a shared embedding space for zero-shot visual classification.