Why I Built Imagen4 After 200 Failed AI Image Generations

Tired of AI tools that can't get hands right? I created Imagen4 to solve modern AI image generation - one model that nails details other AIs miss.

It was 3 AM when I finally admitted defeat. My client needed a simple product mockup - just a phone with a custom case design. After 47 generations across 5 tools, every AI still gave me:

• Six-fingered hands 🤦

• Floating logos

• "Abstract" textures that looked like GPU artifacts

I had promised "AI magic" and delivered nightmare fuel instead.

Why Most AI Image Tools Fail
Through 200+ failed attempts, I discovered three fatal flaws in current gen AI:

1. The Frankenstein Effect
   
   Models stitch together random trained elements instead of understanding spatial relationships. That's why you get:
   
   background = random_cityscape()
   
   foreground = random_person()
   
   return background + foreground # 🤮

2. Training Data Blind Spots
   
   Most models fail on:
   
   • Hands (obviously)
   
   • Text (always garbled)
   
   • Branded items (illegal training data)

3. No Creative Constraints
   
   Without proper guidance, AIs default to "psychedelic clipart" aesthetics.

The Solution: Constrained AI Generation
The breakthrough came when I stopped treating AI as a black box and started giving it:

1. Physical constraints (depth maps, normal vectors)
2. Style anchors (reference color palettes)
3. Iterative refinement

That's why I built https://www.imagen4.org/

Try It Yourself (Free Tier Available)