Text-to-Image

Simple Definition

Text-to-image AI generates pictures from written descriptions. You type a prompt — “a serene mountain lake at sunset, photorealistic” — and the AI produces an image matching your description.

It’s one of the most visible applications of generative AI, and the quality has improved dramatically since 2022.

How It Works

Most text-to-image tools use diffusion models — a technique where the AI starts with random noise and progressively refines it into a coherent image guided by the text prompt.

The AI was trained on billions of image-text pairs (images with captions), learning to associate visual concepts with language descriptions.

Leading Text-to-Image Tools

• Midjourney — high-quality artistic and photorealistic images, runs in Discord
• DALL-E 3 — built into ChatGPT, follows prompts very accurately
• Stable Diffusion — open-source, can run locally
• Adobe Firefly — integrated into Adobe products, commercially safe
• Ideogram — strong at text within images

Getting Good Results: Prompt Tips

• Be specific about style: “oil painting,” “photorealistic,” “flat illustration,” “watercolor”
• Describe the lighting: “golden hour,” “studio lighting,” “dramatic shadows”
• Set the mood: “serene,” “chaotic,” “minimalist”
• Specify composition: “close-up portrait,” “wide angle,” “bird’s eye view”

Practical Uses

• Marketing and social media visuals
• Blog post illustrations
• Concept art and mockups
• Product visualization
• Presentation graphics

Related Terms

• Diffusion Model — the AI architecture behind most image generators
• Generative AI — text-to-image is a major type of generative AI
• Multimodal AI — AI that handles both text and images
• Prompt Engineering — writing good prompts applies to image generation too