“In the 2000s we had green beer. In 2023, we had green leprechauns—manufactured.”
— Wing

March 17, 2023 wasn’t just about shamrocks and pints. It became a showcase of how generative AI can crank out absurdly convincing holiday art—and leave us wondering if we’re celebrating Ireland… or a neural network.

🤖 Leprechauns That Look Too Real

AI tools pumped out photorealistic leprechauns holding frothy beers and pots of gold. One standout popped up on Freepik and Dreamstime, with crisp 3D visuals of a thumb‑up leprechaun with beer and coins—so polished you’d swear it was a Pixar asset. :contentReference[oaicite:2]{index=2}

“Back in the ’90s, we worried about catfishing on AOL. In 2023, the catfish has a perfect voice clone and video.”
— Wing

Valentine’s Day 2023 was weird.

Not because of flowers or bad chocolate. But because something darker was creeping through the wires.

Suddenly, everywhere you looked:

• A Korean influencer’s video was revealed as fully synthetic.
• Celebrities were denying AI-generated “confession” clips.
• A streamer’s private likeness was deepfaked into adult content.
• Voice AI tools cloned dead partners, promising “one last conversation.”

What should’ve been a day about connection… became one about doubt.

“In the early 2000s, we had watermark wars. In 2022, we had style laundering.”
— Wing

It’s December 2022.

You’re browsing Etsy, Gumroad, or even a local convention artist alley. There’s a print of a fox samurai under cherry blossoms. It’s striking. Detailed. Ethereal.
You buy it.

But hours later, something nags you.
Was that… AI-generated?

And if it was—shouldn’t they have told you?

🎭 The Invisible Flood

By late 2022, generative AI art had become too good. Midjourney v4 and Stable Diffusion with custom models were cranking out pieces that mimicked human imperfections: rough brush textures, faux pencil strokes, even “digital signature” scribbles in corners.

“In the ‘90s, we worried about scanners stealing art. In 2022, the art stole itself.”
— Wing

The year was 2022. Stable Diffusion had just exploded onto GitHub. Midjourney was suddenly all over Twitter with ethereal, hyper-detailed portraits. And somewhere on ArtStation, someone posted their latest concept piece—only to be accused of using AI.

The war drums were starting to beat.

🎨 Artists Felt It First

Professional and hobbyist artists alike raised alarms. It wasn’t the tech—they’d seen Photoshop evolve for decades. It wasn’t even automation—many used tools like Clip Studio’s perspective rulers or photo references without shame.

“Back in my day, we overclocked our Pentiums to run Quake faster. Now we’re doing it for language models.”
— Wing, mid-rant, 2022

In the year 2022, a new frontier opened up for hobbyists and developers alike: Large Language Models (LLMs) stopped being pure research tools and started becoming part of the daily build cycle for curious engineers and indie coders. But with that shift came a new dilemma—do you run your AI workloads locally, or pipe them out to the cloud?