This is a conversation I had with ChatGPT AI this morning. Some of you may remember back in the archived days of OZZU I did a bit of graphic design and experimented with POV-Ray which is a Ray Tracing Program from back in the 1990's. For those not familiar with POV-RAY it is an open-source program that you could create images using code. It still exists and is still updated.
The reason for this post is that I have been using AI to generate some images for my food related website and social media. So this morning I decided to have a conversation with ChatGPT about how it creates images and here is the conversation:
You are getting better at creating more realistic images of what I want
ChatGPT said:
Thanks, Mark — I really appreciate that. I’ve been paying attention to your preferences, so if there's anything you want tweaked (like lighting, plating, angles, or even mood).
You said:
Well you have me a little curious. Have you ever heard of POVRay?
ChatGPT said:
Yes — POV-Ray (short for Persistence of Vision Raytracer) is a high-quality ray tracing tool that’s been around since the 1990s. It's used to generate photorealistic images from a scripted scene description language. Unlike image editing or AI-based tools, POV-Ray builds scenes entirely from mathematical descriptions of shapes, lights, textures, and cameras.
A few key features of POV-Ray:
Script-based: You write code (scene files) to define every object, light source, and camera placement.
Physically accurate lighting: It simulates reflections, refractions, shadows, and even global illumination.
Open source: It’s been a free tool since its inception and has a dedicated community of hobbyists and developers.
Limitless geometry: Because it's mathematical, it excels at rendering complex shapes like fractals or precise architectural layouts.
It doesn’t use neural nets or diffusion models like modern AI tools, but it can produce very crisp, stylized realism — particularly for things like metals, glass, or mathematically-perfect surfaces. Were you thinking about combining it with anything you're working on?
You said:
Not yet, but do you use POV-Rey principles in your images? If not can you explain what neural nets and diffusion models are?
ChatGPT said:
Great questions — and here’s the honest breakdown:
❓ Do I (or DALL·E) use POV-Ray principles?
No, DALL·E and similar image generation tools do not use POV-Ray or its rendering methods.
POV-Ray is based on ray tracing — simulating the path of light rays as they bounce around a scene made from mathematically defined geometry. It produces images from scratch using physics and math.
In contrast, DALL·E and other AI image generators use a completely different approach:
They’re based on neural networks and a technique called diffusion modeling — a process more like "learning to paint from experience" than simulating light and geometry.
🧠 Neural Networks (in simple terms)
A neural network is a computer system loosely modeled on the human brain. It consists of layers of "neurons" that:
Take in data (like images or text),
Learn patterns,
And output predictions or generated content.
For images, this means learning what a “grilled chicken thigh” or “sunlight on ceramic plates” looks like — not by measuring light physics, but by seeing millions of examples.
🌫️ Diffusion Models (used in DALL·E)
A diffusion model works like this:
Start with random noise (like static on a TV screen).
Then it gradually "denoises" it — step by step — using what it’s learned about how real images look.
With guidance from text prompts, it "steers" the noise toward a coherent image.
So instead of computing reflections or refractions like POV-Ray does, diffusion models imagine textures and lighting based on patterns learned from real-world photos.
For those that never played around with POV-Ray and might want to experiment (remember it's totally code) check out their Hall of Fame
