Will any image model available to the public be able to reliably produce images of every regular polygon before 2026?
32
Ṁ2729
2026
17%
chance

Current image models are terrible at this. (That was tested on DALL-E 2, but DALL-E 3 is no better.)

The prompt should be some string of text such that the name of a polygon or a number of sides can be inserted, and at least 50% of the generated images are the correct shape on the first try. It does not have to be able to generate non-regular, self-intersecting, or other "weird" polygons, just regular triangles, squares, pentagons, etc. I'll only require it to recognize names up to "octagon", after that it can just be side count.

If the input is fed through an LLM or some other system before going into the image model, this pre-processing will be avoided if I can easily do so, and otherwise it will not.

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Are you going to test all infinity polygons?

bought Ṁ100 NO

This is technically impossible. Given that a regular triangle has sides with an irrational vertical and horizontal component to their length, it is impossible to accurately draw a regular triangle using a pixel display. It could be close, but never a truly regular triangle.

Isaac has specified “If I don't see anything wrong with the image, then it's correct.” I don’t think this whole market is a gotcha where Isaac is going to say “Well, that’s as close as possible given the image resolution constraints, but I still think it looks wrong” because it’s not mathematically ideal in a way that is impossible in the physical world.

It's extremely unlikely a given image would be as close as possible for any given image resolution. You can almost always get closer by changing the rotation, polygon size, or line thickness. Such a requirement would still practically guarantee that this market resolves NO.

On the other hand, if all that matters is that it "looks right to Isaac" then that would guarantee that this market should resolve YES: the vast majority of polygons have so many sides that they would appear indistinguishable from circles. An image model that always renders an approximate circle would result in "at least 50% of the generated images" being "the correct shape on the first try" since the vast majority of generated images would be visually indistinguishable from the correct shape.

If the user can specify the resolution of the image, how does that affect things? For example, if the model is capable of outputting a 20,000x20,000 pixel image, and fails at that scale, but it looks ok for 20x20 pixel images, how would that be handled?

predicts NO

@JimHays Would need to succeed at any resolution.

Surely you must have a limit to the number of sides - otherwise I could just ask for a 957182371895781293412 sided polygon and there's no way it can even show distinction between the sides in an image

predicts NO

@pkpr If I don't see anything wrong with the image, then it's correct.

@IsaacKing So, to be clear, it has to be able to count sides as high as you reliably can? As in, if you often would make a mistake trying to confirm whether something is exactly a 90-sided figure, it's fine for the model to make mistakes drawing it?

@UnspecifiedPerson No, I can use a notepad to keep track or whatever.

Is there any limit to the side count?

@s No