How does AI image generation work?
Text-to-image models learn the relationship between words and pictures from massive datasets. When you write a prompt, the model starts from noise and progressively refines it into an image that matches your description. You don’t need to draw — you describe, and the model renders. The skill shifts from illustration to clear, structured prompting.
Which AI image generator should you use?
Match the tool to the look. Midjourney produces highly aesthetic, stylized art with little effort and suits concept art and marketing visuals. DALL·E follows complex instructions and text-in-image well, making it strong for precise, literal requests. Stable Diffusion is open-source and endlessly customizable — ideal if you want local control, custom models, or fine-tuned styles. The comparison guides here test them on identical prompts.
How do you write a good image prompt?
Build the prompt in layers: the subject, the style or medium, lighting, composition or camera angle, and quality or detail cues. "A red fox in a snowy forest, oil painting, soft morning light, shallow depth of field" beats "a fox." Add or remove descriptors to steer the result, and reuse a seed when you want consistent variations.
How do you refine and finish an image?
A single generation is rarely the final asset. Use inpainting to fix or replace parts, vary a result to explore alternatives, and upscale to increase resolution for print or web. Bringing the output into an editor for color and cropping turns an AI draft into a polished, professional image.
What about copyright and commercial use?
Rights differ by tool and plan. Some generators grant commercial use on paid tiers; others restrict it or operate in legal gray areas depending on your region. Before using AI images commercially, confirm the license, and avoid prompts that imitate a living artist’s name or a trademarked character.