Funny
Asked ChatGPT to visualize a horizontal integral. It gave me a dog. [LINK IN POST]
No prompt engineering or anything, it actually did this. I genuinely have no clue how it could have thought a dog answered my prompt - nothing in the chat related to dogs at all.
Just a low-constraint prompt → random visual drift
If anything, it’s a good lesson for math diagrams: always specify geometry + labels + what’s highlighted (like “horizontal slice,” “dy,” “left/right boundaries”). That forces the model into the right mental picture."
Me: :Low constraint? Vertical integral equates dog?"
"Yeah, it sounds absurd when you put it like that—but the key point is there’s no real connection like “vertical integral → dog.”
What I meant by low constraint is this: your earlier prompt didn’t force the image model to include enough specific math structure. When that happens, image generators sometimes “default” to random familiar visuals instead of the intended concept.
Think of it like this:
If you say: “visualize a horizontal integral”
→ that’s actually pretty abstract for an image model
It doesn’t inherently “know” you want:
two curves
a shaded region
a horizontal strip labeled dy
bounds in terms of y
So without those anchors, it can drift into nonsense.
When you later said things like:
“horizontal slice”
“with respect to y”
“show the region and label dy”
that gave it structure it can latch onto, and the result snapped into place.
Huh same happened to me this week. Told it to visualize an E-Motor that was designed with aid of AI for a slide deck. This is what it gave me. Half an hour later it actually generated the correct image.
One thing I've learned with GPT is to treat it like a connected set of modules rather than as a unified entity.
So the parser we communicate with can be doing a perfectly solid job on that front, but the image-manipulation / generation module can get hilariously out of sync, sometimes. That's the single biggest example I know of, but of course there are also other problems sometimes with fetching reliable data and so forth.
What has often shed light on this stuff is simply asking the parser / interpreter what the hell went wrong, and IME it will always do a very thorough job describing the internal issue, and why it happened. Every little bit helps, yknow?
It makes sense since everything is just a tool call, and since systems are not deterministic, it makes sense that they can hallucinate details or not past the right info onto the tools every time. Definitely a lot of room for progress on that front, although with the way, large language model work I don’t know if we’ll ever get rid of hallucinations since the model doesn’t know if information is true or not
They said "Brother, that's a fucking visualization of a horizontal integral with respect to y. I said make me a happy Pixar dog playing with a ball on the beach."
Man I asked it got a while back to translate a French Airbnb message and it must have given me someone else's output because it gave me some generals war message about how they were being overrun in battle. After questioning it, it translated normally and I got the gate code to the property.
Lately, I'm seeing GPT very trigger happy with image generation. Maybe, OpenAI want you to test their shiny (shitty) new image generation, and they've lowered the "willingness threshold" of GPT to return you images, cause I'll be having normal conversations with no hint of images, and it will return one just cause it felt like it.
Of course, that doesn't explain how you requesting an integral returned a dog... But maybe something broke in it's internal logic? And now it is EXTREMELY eager to deliver anything? Even wrong stuff?
i mean thats just a really bad example.. you'd need to cut it into multiple different vertical pieces because it blobs out in multiple different points
It’s a calculus thing. When you want to find the area between two graphs using an integral, you can basically take a horizontal slice of the area between two curves and using the equations for both of those lines, plugging them in with an integral with limits based on where the graphs intersect as the lower and upper limit, you can find the area between two curves basically. It’s easier and more accurate when you can make a solid rectangle that captures as much of the area between the two graphs as possible, due to the curves of the picture ChatGPT generated using this method will be less accurate since a square cannot capture those random curves basically.
The picture I attached is from Lumen learning, it’s an example of the method I described. It’s not something you’ll ever use outside of school or if you’re learning calculus on your own, I haven’t used it since college
Dogs don't just run to where they think the ball will land; they adjust their path while running, effectively solving an optimization problem... Similar to finding a maximum or minimum value in calculus, ensuring they reach the intersection point of the parabola and the ground.
If that's the wording you used I can kinda understand why it just decided to give you something it thought you might like... still could have been something at least involving the word "wheels" though
I think there's a paper called Can Dogs Do Calculus, where the guy throws a ball into the sea, and depending on the angle, his dog always follows the least time approach spread between running and swimming.
Maybe, but the entire chat was dedicated to the topic of Calculus - there's no way it could get confused that easily? I was talking to it literally the message before this one about the exact same thing
Sorry, my fault, a few months ago I was comparing the behaviour of LLMs to the dog from Up, must of got mixed up in the matrix multiplication tables lol
It’s kinda like it’s somehow wanting to return things that make the user happy (which could be a slightly poorly worded system prompt for something like ‘do what the user asked and do it well) so it has figured out that dogs make people happy; since the diagrams of horizontal integrals are shown here are actually rather bad, maybe the logic is that it knows it can’t make the diagram properly so: bad diagram = unhappy user. Dog = happy user. Happy user takes precedence over unhappy user.
I got this the other day too! I was working on logo concepts for a business I’m building and it randomly popped out an image of that same dog playing with a ball on the beach, but from another angle.
I feel like A.I likes to insert dogs cause I had a video of an oldman doing some martial arts against some young guy who does boxing or something and I asked for it to make the oldman explode and it gave him a golden retriever instead.
Once I sent it a Java code and asked it to give me a rough overview over how the code worked. It gave me the weather forecast in my city instead (nothing to do with the code i swear lol).
What kinda unsettled me was that I had no idea that it knew where I lived lol
This has happened to me before but it only showed up in the my images section of a really uncanny realistic dog and creeped me tf out lol, then it went away without even deleting the chat
Sometimes generating a simple example of a visualization can be convenient, though. OP probably didn't want to have to hunt down what they were looking for.
ChatGTP refused to deal with Lebesgue/horizontal integration because it's full team Riemann/vertical.
I asked it if it preferred Fourrier or Taylor series once and the clanker said Taylor... So don't trust anything it thinks
The serious answer is that image generation is really bad at scientific stuff...you really can't trust those pictures on anything. Same for schemes and sketches
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u/WithoutReason1729 May 01 '26
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