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  "path": "/t/collection-of-gpt-image-generator-2-0-issues-bugs-and-work-around-tips-check-first-post/1379535?page=7#post_141",
  "publishedAt": "2026-05-04T16:58:46.000Z",
  "site": "https://community.openai.com",
  "textContent": "Chain_L:\n\n> It looks like the model is **stumbling** when it tries to calculate complex light interactions (caustics) with fine, volumetric, repeating textures. I suspect the neural network is either trying to **cut corners** to save resources by applying a procedural Voronoi (?) pattern, or it’s getting **bogged down** in these complex calculations and just outputting whatever is left over. These are just my assumptions.\n\nIf you should be a little interested in the technology: these AI systems do not calculate light or caustics effects like a ray tracer.\n\nIn principle, it works in such a way that they analyze an extremely large number of images for patterns and assign them to words. And then from these patterns, they can reconstruct entirely new patterns and so images.\n\nSo it does not matter how complex an image would be for a ray tracer, but whether the engine manages to organize the patterns in such a way that they result in an aesthetic image, and follow the prompt as well as possible.\n\n(It is also important whether an image is the first one in a session / after restarting the window, or whether many have already been made. The first images are often a little better than the following ones.)\n\nI will look at the two prompts as soon as I have time and analyze the differences…",
  "title": "Collection of GPT-image-generator 2.0 issues, bugs, and work-around tips (check first post)"
}