How AI Image Generators Work: Your Questions Answered

Twelve seconds. That's roughly how long it takes to type "a corgi in an astronaut suit, oil painting, dramatic lighting" into Midjourney and get four images back. Text goes in. Pictures come out. No camera, no sketchbook, no stock photo library.

I get asked how AI image generators work about once a week now, usually by someone who just watched a friend produce a birthday card in thirty seconds. So here's the plain-English version — plus the questions people actually ask, including the uncomfortable ones.

How AI Image Generators Actually Work

They don't draw. They denoise. That's the whole trick, and nearly everything strange about these tools follows from it.

During training, the model chewed through hundreds of millions of image-and-caption pairs scraped from the web. It learned statistical associations: what "golden hour" tends to look like, which shapes show up near the word "cathedral," how skin tones behave under hard flash. No understanding of a cathedral. Just a very deep sense of what tends to sit next to what.

Two halves do the work. One reads your words, one makes pictures, and they meet in the middle:

• A text encoder (CLIP for most Stable Diffusion models, T5 for newer ones like SD 3.5 and Flux.1) converts your prompt into a long list of numbers — an embedding. That's all your sentence ever becomes.
• The generator starts with a square of pure random noise. Actual static, like a dead TV channel.
• It removes a bit of that noise, compares the result against your embedding, removes a bit more. Twenty to fifty rounds of this.
• With latent diffusion — the technique behind Stable Diffusion, and the reason this stuff runs on a gaming GPU instead of a server farm — the whole process happens in a compressed mathematical space and only becomes pixels at the very end.

Older models used a U-Net as the denoiser. Newer ones use transformers. You don't need to care, honestly. It changes the output quality, not your job.

Why the same prompt gives you different pictures

That starting noise is random, and its random value is called the seed. Lock the seed, keep the model and settings identical, and you'll get the same image every time. Change it and you get a cousin, not a twin. This is why "I got a great one and can't recreate it" is such a common complaint — save your seeds.

Why typing "no elephants" gives you elephants

Text encoders are lousy at negation. The word "elephants" gets full attention weight; the "no" quietly evaporates. If your tool has a negative prompt field (Stable Diffusion, ComfyUI, most local setups), use it. If it doesn't (DALL·E 3, Midjourney), describe what you do want instead: "an empty beach at dawn" beats "a beach with no people, no umbrellas, no dogs."

AI Image Prompt Tips That Actually Change the Result

Here's my honest take after two years of fiddling: prompting is maybe 20% vocabulary and 80% knowing what you want. Vague ideas produce vague pictures, no matter how many "8K, masterpiece, trending on ArtStation" tokens you bolt on.

You want	Add this to the prompt
A specific look	Medium and era — "35mm film photo, 1990s," "gouache illustration"
Better lighting	"soft window light," "backlit," "overcast"
A particular shot	"wide angle," "macro," "eye level," "bird's eye"
Less default gloss	"candid," "documentary," "unretouched" (models default to over-polished)
Control over shape	Aspect ratio flags — --ar 16:9, or the equivalent in your tool

The bigger fork in the road is how you write. DALL·E 3, Imagen, and Gemini's image model (the one the internet nicknamed "Nano Banana") handle full sentences and paragraphs beautifully — write them a brief like you'd write a creative director. Midjourney still rewards short, comma-separated fragments plus parameters like --ar 3:2 or --style raw. Same idea, different dialect.

Why Hands and Text Still Come Out Wrong

Fingers are a nightmare for a denoiser. Hands are small, they twist into thousands of configurations, and they're often partly hidden in the training data — so the model learns "finger-ish texture" rather than anatomy. Six fingers is the statistical average of not paying close attention.

Text was worse, and for a real reason: spelling requires letter-by-letter reasoning, and diffusion models think in fuzzy visual blobs, not characters. This has improved dramatically — 2025-era models from OpenAI and Google render short phrases correctly most of the time. Four-word signs still break. Assume you'll fix text in Photoshop for anything client-facing.

Is AI Art Stealing? The Uncomfortable Question

Most of these models were trained on images pulled from the open web without asking. That's simply true, and it's why Getty is suing Stability AI and a group of artists is suing several labs. No final ruling has landed in the US yet. Separately, the US Copyright Office has been clear that a purely AI-generated image can't be copyrighted — you need meaningful human authorship to claim anything.

My position: it's reasonable to feel uneasy, and reasonable to use these tools anyway. What I'd push back on is pretending the sourcing question doesn't exist. If you're doing commercial work, look for models trained on licensed or opted-in data — Adobe Firefly is the obvious one, and it's included with Creative Cloud. And read the terms before you sell anything. Midjourney, OpenAI, and Adobe all grant commercial rights on paid tiers, but the details differ, and free tiers often don't.

Which Generator Should You Actually Pay For?

• Midjourney (v7, from $10/month) — still the best-looking output per keystroke. Weird Discord-era baggage, but the web editor fixed most of that. Start here if aesthetics matter more than precision.
• ChatGPT Plus ($20/month) — best at following a long, complicated instruction, and best at editing an existing image conversationally. Great all-rounder.
• Google Gemini — strong at edits and character consistency; generous free tier.
• Adobe Firefly — the safe choice for client work. Slightly less wild, fully licensed training data, lives inside Photoshop.
• Stable Diffusion 3.5 or Flux.1 via ComfyUI — free, open weights, runs on your own GPU, absurdly flexible. Also the steepest learning curve of the bunch. Flux's "dev" weights are non-commercial, so check licenses before you sell.

Don't pay for three. Pick one, use it for a month, then decide.

How to Get Consistent Characters and Styles

This is the question that separates hobbyists from people billing clients. Three approaches, in order of effort:

1. Seeds and reference images. Midjourney's --cref, or an image prompt in most tools, keeps a face roughly recognizable across shots. Cheap and fast.
2. Inpainting. Generate the scene, then mask and regenerate just the face or the hands. Every serious tool has this now.
3. LoRA training. Twenty to thirty images of your subject, an hour on a rented GPU, and you get a small adapter file that locks a character or style permanently. Overkill for a hobby. Essential for a comic book.

Key Takeaways

• AI image generators don't draw — they start with random noise and remove it step by step, guided by your text.
• Your prompt becomes a list of numbers, not a sentence the model "reads." Specificity matters far more than magic words.
• Negation barely works. Describe what you want, not what you don't.
• Save your seeds if you care about reproducing a result.
• Training data provenance is a real, unresolved legal issue — use licensed models like Firefly for commercial work.
• One paid subscription is plenty. Learn it properly before adding a second.

Frequently Asked Questions

How do AI image generators work in simple terms?

Think of a sculptor who starts with a block of static instead of stone. The model removes noise in small steps, checking against your prompt each time, until a picture emerges. Text-to-image AI learned this by studying hundreds of millions of captioned images, which is why it recognizes "brutalist library" without anyone programming a library.

Is AI art stealing from artists?

It's contested and unresolved. Most major models were trained on copyrighted images scraped from the web without permission or payment, and several lawsuits are working through the courts. Some tools — Adobe Firefly notably — train only on licensed or public-domain material. If that distinction matters to you, it's worth choosing accordingly.

What's the best AI image generator for beginners?

Start with ChatGPT's image generation if you already pay for Plus, or Midjourney at $10/month if you care most about how the pictures look. Both take plain English and forgive sloppy prompts. Skip ComfyUI and Stable Diffusion until you've hit a wall you actually want to climb.