Been liking Alex O’Connor’s ChatGPT explanation videos and ChatGPT related experiments.
Alex O’Conner makes content related to philosophy and religion but I particularly enjoyed, in addition to this video, one where he gaslights ChatGPT using moral dilemmas.
In this video he tells you the reason why it is so hard to get ChatGPT to do this. Short Answer: most images you find of wine are either empty glasses or partially full because who fills their wine to the top?
Image generation uses DallE and is not Baked into the model.
All it does is give it a prompt. Generates and shows you the results for that prompt.
You can click the pictures to see that prompt and you will see that it verbosely requested it overflowing but dalle does not always interpret that prompt the same, actually i found llms rather suck at prompting image generation models because they behave very strongly on certain words.
A similar experiment was done with “street with no lanterns” always resulting in a lantern.
If I ask you to imagine a street with no lanterns, are you imagining lanterns or no lanterns?
Lanterns of course.
Would take an image generation model at least 3 steps which it doesn’t have right now.
A review step to see if the output matches the prompt.
A identification step to detect elements that don’t match
A redo step to mix that area in the background image (remove) or regenerates an improvement.
Right now you cant iterate on images. Every minor tweak is a completely new image. At least not with dalle because you cant control the seed.
It might be more accurate to use something like Leonardo.AI rather than ChatGPT because you can edit existing images as needed and set the seed. You can even keep a consistent ‘character’ and reuse it in many pictures. Its dreamshaper model is based on SD. I have had the most accurate results with Leonardo. I don’t use ChatGPT/Dall-E for images, it uses too much on a free plan.