Two years ago, knowing the difference between --ar 16:9 --s 750 --c 40 and --ar 3:2 --s 250 --c 15 was a genuine edge.
Every mainstream diffusion model follows the same three-part recipe: a text encoder tokenizes your prompt, a diffusion backbone denoises in latent space, and a...
Every image generator on the market does the same thing at the end of its diffusion process: it hands you a raster file. A grid of pixels.
OpenAI killed DALL-E on a Monday and nobody threw a funeral.
Most image generation workflows aren't about getting one perfect shot.
OpenAI confirmed it: DALL-E 2 and DALL-E 3 both go dark on May 12. Not deprecated-but-still-kinda-works dark.
"The camera got more precise, but the photographer left.
Six months ago, the cheapest production-grade image API cost around fifteen cents per generation.
There's a threshold where a tool stops being a tool and starts being an instrument. For image generation, that threshold is about one second.
Midjourney spent a month being the fastest image generator nobody wanted to use. V8.
On April 4, three image generators nobody had heard of appeared on LM Arena's blind evaluation page.
Five months ago, Microsoft's image generation was a footnote. MAI-Image-1 sat at ninth place on the Arena.
Three weeks ago Midjourney shipped the update its community spent two years begging for: readable text in generated images.
Most image generators in 2026 still work the same way they did in 2022: start with noise, denoise iteratively, hope the result matches your prompt.
Most image generators work like a reflex. Prompt goes in, probability distribution gets sampled, pixels come out.
Microsoft's MAI-Image-2 debuted on April 2nd and immediately landed third on the Arena.ai leaderboard — behind only Google's Gemini 3.
Two weeks into Midjourney V8 Alpha, I can confirm it's the fastest image generator I've used from any commercial platform.