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How Far Generative AI Has Come (And My Experiments with It)

Lately, I’ve been spending a good amount of time deep in experimentation mode with Stable Diffusion, specifically diving into newer architectures like Qwen-Image and Z-Image-Turbo from Alibaba. I have to say, they’ve been fascinating to work with—largely due to the sheer fidelity and nuance they output straight out of the box.

Prompt Reupscale with Qwen-Image-Edit-2511

My testing has spanned a pretty wide spectrum, ranging from generating fictional yet hyper-realistic portraits to editing existing photos across various styles, from anime-inspired aesthetics to real-world people and public figures. It honestly blows my mind how far this technology has come in such a short window. It wasn’t all that long ago that we were regularly troubleshooting the classic AI quirks: extra fingers, warped geometry, and melting hands. Today, the results are so shockingly convincing that it genuinely borders on the uncanny.

Even so, it’s incredible to witness firsthand just how fast the broader ecosystem around generative AI and Stable Diffusion is evolving. Between optimizing models locally and pushing them through their paces, the pace of innovation keeps making it feel like a completely new playing field every few months.

By Justin Au

I'm Justin Au, an IT worker and technology enthusiast. Professionally, I work extensively with Linux environments, primarily Ubuntu and Debian. Outside of work, I'm an avid homelabber and tinkerer, focusing on self-hosted infrastructure and the practical deployment of AI technologies. I love exploring open-source solutions and figuring out how to make modern tech run locally and efficiently.