12 ms·

Since the first (good) image generation models became available, I've been trying to get them to generate an image of a clock with 13 instead of the usual 12 ho

Since the first (good) image generation models became available, I've been trying to get them to generate an image of a clock with 13 instead of the usual 12 hour divisions. I have not been successful. Usually they will just replace the "12" with a "13" and/or mess up the clock face in some other way. I'd be interested if anyone else is successful. Share how you did it!

snek_case 11mo ago
From my experience they quickly fail to understand anything beyond a superficial description of the image you want.
- atorodius 11mo ago
  That's less and less true https://minimaxir.com/2025/11/nano-banana-prompts/ https://minimaxir.com/2025/11/nano-banana-prompts/
  - dang 11mo ago
    Related ongoing thread: Nano Banana can be prompt engineered for nuanced AI image generation - https://news.ycombinator.com/item?id=45917875 https://news.ycombinator.com/item?id=45917875 - Nov 2025 (214 comments)
Scene_Cast2 11mo ago
I've noticed that image models are particularly bad at modifying popular concepts in novel ways (way worse "generalization" than what I observe in language models).
- emp17344 11mo ago
  Maybe LLMs always fail to generalize outside their data set, and it’s just less noticeable with written language.
  - cluckindan 11mo ago
    This is it. They’re language models which predict next tokens probabilistically and a sampler picks one according to the desired ”temperature”. Any generalization outside their data set is an artifact of random sampling: happenstance and circumstance, not genuine substance.
    - cluckindan 11mo ago
      However: do humans have that genuine substance? Is human invention and ingenuity more than trial and error, more than adaptation and application of existing knowledge? Can humans generalize outside their data set? A yes-answer here implies belief in some sort of gnostic method of knowledge acquisition. Certainly that comes with a high burden of proof!
      - dawidloubser 11mo ago
        Yes
        cluckindan 11mo ago
        Can you elaborate on what you mean by that, and prove it? https://journals.sagepub.com/doi/10.1177/09637214251336212 https://journals.sagepub.com/doi/10.1177/09637214251336212
        Thorentis 11mo ago
        The proof is that humans do it all the time and that you do it inside your head as well. People need to stop with this absurd level of rampant skepticism that makes them doubt their own basic functions.
        RugnirViking 11mo ago
        the concept is too nebulous to "prove" but the fact im operating a machine (relatively) skillfully to write to you shows we are in fact able to generalise. This wasn't planned, we came up with this. Same with cars etc. We're quite good at the whole "tool use" thing
- CobrastanJorji 11mo ago
  Also, they're fundamentally bad at math. They can draw a clock because they've seen clocks, but going further requires some calculations they can't do. For example, try asking Nano Banana to do something simpler, like "draw a picture of 13 circles." It likely will not work.
IAmGraydon 11mo ago
That's because they literally cannot do that. Doing what you're asking requires an understanding of why the numbers on the clock face are where they are and what it would mean if there was an extra hour on the clock (ie that you would have to divide 360 by 13 to begin to understand where the numbers would go). AI models have no concept of anything that's not included in their training data. Yet people continue to anthropomorphize this technology and are surprised when it becomes obvious that it's not actually thinking.
- bobbylarrybobby 11mo ago
  It's interesting because if you asked them to write code to generate an SVG of a clock, they'd probably use a loop from 1 to 12, using sin and cos of the angle (given by the loop index over 12 times 2pi) to place the numerals. They know how to do this, and so they basically understand the process that generates a clock face. And extrapolating from that to 13 hours is trivial (for a human). So the fact that they can't do this extrapolation on their own is very odd.
- echelon 11mo ago
  gpt-image-1 and Google Imagen understand prompts, they just don't have training data to cover these use cases. gpt-image-1 and Imagen are wickedly smart. The new Nano Banana 2 that has been briefly teased around the internet can solve incredibly complicated differential equations on chalk boards with full proof of work.
  - phkahler 11mo ago
    >> The new Nano Banana 2 that has been briefly teased around the internet can solve incredibly complicated differential equations on chalk boards with full proof of work. That's great, but I bet it can't tie it's own shoes.
    - esafak 11mo ago
      And a submarine can't swim. Big deal.
    - 11mo ago
echelon 11mo ago
That's just a patch to the training data. Once companies see this starting to show up in the evals and criticisms, they'll go out of their way to fix it.
- rideontime 11mo ago
  What would the "patch" be? Manually create some images of 13-hour clocks and add them to the training data? How does that solution scale?
- godelski 11mo ago
  s/13/17/g ;)
coffeecoders 11mo ago
LLMs are terrible for out-of-distribution (OOD) tasks. You should use chain of thought suppression and give constaints explictly. My prompt to Grok: --- Follow these rules exactly: - There are 13 hours, labeled 1–13. - There are 13 ticks. - The center of each number is at angle: index * (360/13) - Do not infer anything else. - Do not apply knowledge of normal clocks. Use the following variables: HOUR_COUNT = 13 ANGLE_PER_HOUR = 360 / 13 // 27.692307° Use index i ∈ [0..12] for hour marks: angle_i = i * ANGLE_PER_HOUR I want html/css (single file) of a 13-hour analog clock. --- Output from grok. https://jsfiddle.net/y9zukcnx/1/ https://jsfiddle.net/y9zukcnx/1/
- BrandoElFollito 11mo ago
  Well, that's cheating :) You asked it to generate code, which is ok because it does not represent a direct generated image of a clock. Can grok generate images? What would the result be? I will try your prompt on chatgpt and gemini
  - BrandoElFollito 11mo ago
    Gemini failed miserably - a standard 12 hours clock Same for chatgpt And perplexity replaced 12 with 13
    - dwringer 11mo ago
      > Please create a highly unusual 13-hour analog clock widget, synchronized to system time, with fully animated hands that move in real time, and not 12 but 13 hour markings - each will be spaced at not 5-minute intervals, but at 4-minute-37-second intervals. This makes room for all 13 hour markings. Please pay attention to the correct alignment of the 13 numbers and the 13 hour marks, as well as the alignment of the hands on the face. This gave me a correct clock face on Gemini- after the model spent a lot of time thinking (and kind of thrashing in a loop for a while). The functionality isn't quite right, not that it entirely makes sense in the first place, but the face - at least in terms of the hour marks - looks OK to me.[0] [0] https://aistudio.google.com/app/prompts?state=%7B%22ids%22:%5B%221o3u67KoZmKIWyK8_5aHGiKl_1Ol_dxA9%22%5D,%22action%22:%22open%22,%22userId%22:%22105800868059822502362%22,%22resourceKeys%22:%7B%7D%7D&usp=sharing https://aistudio.google.com/app/prompts?state=%7B%22ids%22:%...
BrandoElFollito 11mo ago
This is really cool. I tried to prompt gemini but every time I got the same picture. I do not know how to share a session (like it is possible with Chatgpt) but the prompts were If a clock had 13 hours, what would be the angle between two of these 13 hours? Generate an image of such a clock No, I want the clock to have 13 distinct hours, with the angle between them as you calculated above This is the same image. There need to be 13 hour marks around the dial, evenly spaced ... And its last answer was You are absolutely right, my apologies. It seems I made an error and generated the same image again. I will correct that immediately. Here is an image of a clock face with 13 distinct hour marks, evenly spaced around the dial, reflecting the angle we calculated. And the very same clock, with 12 hours, and a 13th above the 12...
- ryandrake 11mo ago
  This is probably my biggest problem with AI tools, having played around with them more lately. "You're absolutely right! I made a mistake. I have now comprehensively solved this problem. Here is the corrected output: [totally incorrect output]." None of them ever seem to have the ability to say "I cannot seem to do this" or "I am uncertain if this is correct, confidence level 25%" The only time they will give up or refuse to do something is when they are deliberately programmed to censor for often dubious "AI safety" reasons. All other times, they come back again and again with extreme confidence as they totally produce garbage output.
  - BrandoElFollito 11mo ago
    I agree, I see the same even in simple code where they will bend backwards apologizing and generate very similar crap. It is like they are sometimes stuck in a local energetic minimum and will just wobble around various similar (and incorrect) answers. What was annoying in my attempt above is that the picture was identical for every attempt
    - ryandrake 11mo ago
      These tools 'attitude' reminds me of an eager, but incompetent intern or a poorly trained administrative assistant, who works for a powerful CEO. All sycophancy, confidence and positive energy, but not really getting much done.
deathanatos 11mo ago
Generate an image of a clock face, but instead of the usual 12 hour numbering, number it with 13 hours. Gemini, 2.5 Flash or "Nano Banana" or whatever we're calling it these days. https://imgur.com/a/1sSeFX7 https://imgur.com/a/1sSeFX7 A normal (ish) 12h clock. It numbered it twice, in two concentric rings. The outer ring is normal, but the inner ring numbers the 4th hour as "IIII" (fine, and a thing that clocks do) and the 8th hour as "VIIII" (wtf).
- bar000n 11mo ago
  It should be pretty clear already that anything which is based (limited?) to communicating words/text can never grasp conceptual thinking. We have yet to design a language to cover that, and it might be just a donquijotism we're all diving into.
  - rideontime 11mo ago
    Really? I can grasp the concept behind that command just fine.
  - bayindirh 11mo ago
    > We have yet to design a language to cover that, and it might be just a donquijotism we're all diving into. We have a very comprehensive and precise spec for that [0]. If you don't want to hop through the certificate warning, here's the transcript: - Some day, we won't even need coders any more. We'll be able to just write the specification and the program will write itself. - Oh wow, you're right! We'll be able to write a comprehensive and precise spec and bam, we won't need programmers any more. - Exactly - And do you know the industry term for a project specification that is comprehensive and precise enough to generate a program? - Uh... no... - Code, it's called code. [0]: https://www.commitstrip.com/en/2016/08/25/a-very-comprehensive-and-precise-spec/ https://www.commitstrip.com/en/2016/08/25/a-very-comprehensi...
    - snickerbockers 11mo ago
      Ive been thinking about that a lot too. Fundamentally it's just a different way of telling the computer what to do and if it seems like telling an llm to make a program is less work than writing it yourself then either your program is extremely trivial or there are dozens of redundant programs in the training set that are nearly identical. If you're actualy doing real work you have nothing to fear from LLMs because any prompt which is specific enough to create a given computer program is going to be comparable in terms of complexity and effort to having done it yourself.
giancarlostoro 11mo ago
Weird, I never tried that, I tried all the usual tricks that usually work including swearing at the model (this scarily works surprisingly well with LLMs) and nothing. I even tried to go the opposite direction, I want a 6 hour clock.
usui 11mo ago
I've been trying for the longest time and across models to generate pictures or cartoons of people with six fingers and now they won't do it. They always say they accomplished it, but the result always has 5 fingers. I hate being gaslit.
andix 11mo ago
I gave this "riddle" to various models: > The farmer and the goat are going to the river. They look into the sky and see three clouds shaped like: a wolf, a cabbage and a boat that can carry the farmer and one item. How can they safely cross the river? Most of them are just giving the result to the well known river crossing riddle. Some "feel" that something is off, but still have a hard time to figure out that wolf, boat and cabbage are just clouds.
- jampa 11mo ago
  There are few examples of this as well: https://www.reddit.com/r/singularity/comments/1fqjaxy/contextual_training_and_overreliance_on_llms/ https://www.reddit.com/r/singularity/comments/1fqjaxy/contex...
  - andix 11mo ago
    It really shows how LLMs work. It's all about probabilities, and not about understanding. If something looks very similar to a well known problem, the llm is having a hard time to "see" contradictions. Even if it's really easy to notice for humans.
- userbinator 11mo ago
  Basically a variation of https://en.wikipedia.org/wiki/Age_of_the_captain https://en.wikipedia.org/wiki/Age_of_the_captain
- deleted 11mo ago
  [deleted]
- Recursing 11mo ago
  Claude has no problem with this: https://imgur.com/a/ifSNOVU https://imgur.com/a/ifSNOVU Maybe older models?
  - andix 11mo ago
    Try to twist around words and phrases, at some point it might start to fail. I tried it again yesterday with GPT. GPT-5 manages quite well too in thinking mode, but starts crackling in instant mode. 4o completely failed. It's not that LLMs are unable to solve things like that at all, but it's really easy to find some variations that make them struggle really hard.
chanux 11mo ago
Ah! This is so sad. The manager types won't be able to add an hour (actually, two) to the day even with AI.
edub 11mo ago
I was able to have AI generate an image that made this, but not by diffusion/autoregressive but by having it write Python code to create the image. ChatGPT made a nice looking clock with matplotlib that had some bugs that it had to fix (hours were counter-clockwise). Gemini made correct code one-shot, it used Pillow instead of matplotlib, but it didn't look as nice.
nl 11mo ago
I do playing card generation and almost all struggle beyond the "6 of X" My working theory is that they were trained really hard to generate 5 fingers on hands but their counting drops off quickly.

snek_case 11mo ago

From my experience they quickly fail to understand anything beyond a superficial description of the image you want.

atorodius 11mo ago
That's less and less true https://minimaxir.com/2025/11/nano-banana-prompts/ https://minimaxir.com/2025/11/nano-banana-prompts/
- dang 11mo ago
  Related ongoing thread: Nano Banana can be prompt engineered for nuanced AI image generation - https://news.ycombinator.com/item?id=45917875 https://news.ycombinator.com/item?id=45917875 - Nov 2025 (214 comments)

Scene_Cast2 11mo ago

I've noticed that image models are particularly bad at modifying popular concepts in novel ways (way worse "generalization" than what I observe in language models).

emp17344 11mo ago
Maybe LLMs always fail to generalize outside their data set, and it’s just less noticeable with written language.
- cluckindan 11mo ago
  This is it. They’re language models which predict next tokens probabilistically and a sampler picks one according to the desired ”temperature”. Any generalization outside their data set is an artifact of random sampling: happenstance and circumstance, not genuine substance.
  - cluckindan 11mo ago
    However: do humans have that genuine substance? Is human invention and ingenuity more than trial and error, more than adaptation and application of existing knowledge? Can humans generalize outside their data set? A yes-answer here implies belief in some sort of gnostic method of knowledge acquisition. Certainly that comes with a high burden of proof!
    - dawidloubser 11mo ago
      Yes
      - cluckindan 11mo ago
        Can you elaborate on what you mean by that, and prove it? https://journals.sagepub.com/doi/10.1177/09637214251336212 https://journals.sagepub.com/doi/10.1177/09637214251336212
        Thorentis 11mo ago
        The proof is that humans do it all the time and that you do it inside your head as well. People need to stop with this absurd level of rampant skepticism that makes them doubt their own basic functions.
        RugnirViking 11mo ago
        the concept is too nebulous to "prove" but the fact im operating a machine (relatively) skillfully to write to you shows we are in fact able to generalise. This wasn't planned, we came up with this. Same with cars etc. We're quite good at the whole "tool use" thing
CobrastanJorji 11mo ago
Also, they're fundamentally bad at math. They can draw a clock because they've seen clocks, but going further requires some calculations they can't do. For example, try asking Nano Banana to do something simpler, like "draw a picture of 13 circles." It likely will not work.

IAmGraydon 11mo ago

That's because they literally cannot do that. Doing what you're asking requires an understanding of why the numbers on the clock face are where they are and what it would mean if there was an extra hour on the clock (ie that you would have to divide 360 by 13 to begin to understand where the numbers would go). AI models have no concept of anything that's not included in their training data. Yet people continue to anthropomorphize this technology and are surprised when it becomes obvious that it's not actually thinking.

bobbylarrybobby 11mo ago
It's interesting because if you asked them to write code to generate an SVG of a clock, they'd probably use a loop from 1 to 12, using sin and cos of the angle (given by the loop index over 12 times 2pi) to place the numerals. They know how to do this, and so they basically understand the process that generates a clock face. And extrapolating from that to 13 hours is trivial (for a human). So the fact that they can't do this extrapolation on their own is very odd.
echelon 11mo ago
gpt-image-1 and Google Imagen understand prompts, they just don't have training data to cover these use cases. gpt-image-1 and Imagen are wickedly smart. The new Nano Banana 2 that has been briefly teased around the internet can solve incredibly complicated differential equations on chalk boards with full proof of work.
- phkahler 11mo ago
  >> The new Nano Banana 2 that has been briefly teased around the internet can solve incredibly complicated differential equations on chalk boards with full proof of work. That's great, but I bet it can't tie it's own shoes.
  - esafak 11mo ago
    And a submarine can't swim. Big deal.
  - 11mo ago

echelon 11mo ago

That's just a patch to the training data. Once companies see this starting to show up in the evals and criticisms, they'll go out of their way to fix it.

rideontime 11mo ago
What would the "patch" be? Manually create some images of 13-hour clocks and add them to the training data? How does that solution scale?
godelski 11mo ago
s/13/17/g ;)

coffeecoders 11mo ago

LLMs are terrible for out-of-distribution (OOD) tasks. You should use chain of thought suppression and give constaints explictly. My prompt to Grok: --- Follow these rules exactly: - There are 13 hours, labeled 1–13. - There are 13 ticks. - The center of each number is at angle: index * (360/13) - Do not infer anything else. - Do not apply knowledge of normal clocks. Use the following variables: HOUR_COUNT = 13 ANGLE_PER_HOUR = 360 / 13 // 27.692307° Use index i ∈ [0..12] for hour marks: angle_i = i * ANGLE_PER_HOUR I want html/css (single file) of a 13-hour analog clock. --- Output from grok. https://jsfiddle.net/y9zukcnx/1/ https://jsfiddle.net/y9zukcnx/1/

BrandoElFollito 11mo ago
Well, that's cheating :) You asked it to generate code, which is ok because it does not represent a direct generated image of a clock. Can grok generate images? What would the result be? I will try your prompt on chatgpt and gemini
- BrandoElFollito 11mo ago
  Gemini failed miserably - a standard 12 hours clock Same for chatgpt And perplexity replaced 12 with 13
  - dwringer 11mo ago
    > Please create a highly unusual 13-hour analog clock widget, synchronized to system time, with fully animated hands that move in real time, and not 12 but 13 hour markings - each will be spaced at not 5-minute intervals, but at 4-minute-37-second intervals. This makes room for all 13 hour markings. Please pay attention to the correct alignment of the 13 numbers and the 13 hour marks, as well as the alignment of the hands on the face. This gave me a correct clock face on Gemini- after the model spent a lot of time thinking (and kind of thrashing in a loop for a while). The functionality isn't quite right, not that it entirely makes sense in the first place, but the face - at least in terms of the hour marks - looks OK to me.[0] [0] https://aistudio.google.com/app/prompts?state=%7B%22ids%22:%5B%221o3u67KoZmKIWyK8_5aHGiKl_1Ol_dxA9%22%5D,%22action%22:%22open%22,%22userId%22:%22105800868059822502362%22,%22resourceKeys%22:%7B%7D%7D&usp=sharing https://aistudio.google.com/app/prompts?state=%7B%22ids%22:%...

BrandoElFollito 11mo ago

This is really cool. I tried to prompt gemini but every time I got the same picture. I do not know how to share a session (like it is possible with Chatgpt) but the prompts were If a clock had 13 hours, what would be the angle between two of these 13 hours? Generate an image of such a clock No, I want the clock to have 13 distinct hours, with the angle between them as you calculated above This is the same image. There need to be 13 hour marks around the dial, evenly spaced ... And its last answer was You are absolutely right, my apologies. It seems I made an error and generated the same image again. I will correct that immediately. Here is an image of a clock face with 13 distinct hour marks, evenly spaced around the dial, reflecting the angle we calculated. And the very same clock, with 12 hours, and a 13th above the 12...

ryandrake 11mo ago
This is probably my biggest problem with AI tools, having played around with them more lately. "You're absolutely right! I made a mistake. I have now comprehensively solved this problem. Here is the corrected output: [totally incorrect output]." None of them ever seem to have the ability to say "I cannot seem to do this" or "I am uncertain if this is correct, confidence level 25%" The only time they will give up or refuse to do something is when they are deliberately programmed to censor for often dubious "AI safety" reasons. All other times, they come back again and again with extreme confidence as they totally produce garbage output.
- BrandoElFollito 11mo ago
  I agree, I see the same even in simple code where they will bend backwards apologizing and generate very similar crap. It is like they are sometimes stuck in a local energetic minimum and will just wobble around various similar (and incorrect) answers. What was annoying in my attempt above is that the picture was identical for every attempt
  - ryandrake 11mo ago
    These tools 'attitude' reminds me of an eager, but incompetent intern or a poorly trained administrative assistant, who works for a powerful CEO. All sycophancy, confidence and positive energy, but not really getting much done.

deathanatos 11mo ago

Generate an image of a clock face, but instead of the usual 12 hour numbering, number it with 13 hours. Gemini, 2.5 Flash or "Nano Banana" or whatever we're calling it these days. https://imgur.com/a/1sSeFX7 https://imgur.com/a/1sSeFX7 A normal (ish) 12h clock. It numbered it twice, in two concentric rings. The outer ring is normal, but the inner ring numbers the 4th hour as "IIII" (fine, and a thing that clocks do) and the 8th hour as "VIIII" (wtf).

bar000n 11mo ago
It should be pretty clear already that anything which is based (limited?) to communicating words/text can never grasp conceptual thinking. We have yet to design a language to cover that, and it might be just a donquijotism we're all diving into.
- rideontime 11mo ago
  Really? I can grasp the concept behind that command just fine.
- bayindirh 11mo ago
  > We have yet to design a language to cover that, and it might be just a donquijotism we're all diving into. We have a very comprehensive and precise spec for that [0]. If you don't want to hop through the certificate warning, here's the transcript: - Some day, we won't even need coders any more. We'll be able to just write the specification and the program will write itself. - Oh wow, you're right! We'll be able to write a comprehensive and precise spec and bam, we won't need programmers any more. - Exactly - And do you know the industry term for a project specification that is comprehensive and precise enough to generate a program? - Uh... no... - Code, it's called code. [0]: https://www.commitstrip.com/en/2016/08/25/a-very-comprehensive-and-precise-spec/ https://www.commitstrip.com/en/2016/08/25/a-very-comprehensi...
  - snickerbockers 11mo ago
    Ive been thinking about that a lot too. Fundamentally it's just a different way of telling the computer what to do and if it seems like telling an llm to make a program is less work than writing it yourself then either your program is extremely trivial or there are dozens of redundant programs in the training set that are nearly identical. If you're actualy doing real work you have nothing to fear from LLMs because any prompt which is specific enough to create a given computer program is going to be comparable in terms of complexity and effort to having done it yourself.

giancarlostoro 11mo ago

Weird, I never tried that, I tried all the usual tricks that usually work including swearing at the model (this scarily works surprisingly well with LLMs) and nothing. I even tried to go the opposite direction, I want a 6 hour clock.

usui 11mo ago

I've been trying for the longest time and across models to generate pictures or cartoons of people with six fingers and now they won't do it. They always say they accomplished it, but the result always has 5 fingers. I hate being gaslit.

andix 11mo ago

I gave this "riddle" to various models: > The farmer and the goat are going to the river. They look into the sky and see three clouds shaped like: a wolf, a cabbage and a boat that can carry the farmer and one item. How can they safely cross the river? Most of them are just giving the result to the well known river crossing riddle. Some "feel" that something is off, but still have a hard time to figure out that wolf, boat and cabbage are just clouds.

jampa 11mo ago
There are few examples of this as well: https://www.reddit.com/r/singularity/comments/1fqjaxy/contextual_training_and_overreliance_on_llms/ https://www.reddit.com/r/singularity/comments/1fqjaxy/contex...
- andix 11mo ago
  It really shows how LLMs work. It's all about probabilities, and not about understanding. If something looks very similar to a well known problem, the llm is having a hard time to "see" contradictions. Even if it's really easy to notice for humans.
userbinator 11mo ago
Basically a variation of https://en.wikipedia.org/wiki/Age_of_the_captain https://en.wikipedia.org/wiki/Age_of_the_captain
deleted 11mo ago
[deleted]
Recursing 11mo ago
Claude has no problem with this: https://imgur.com/a/ifSNOVU https://imgur.com/a/ifSNOVU Maybe older models?
- andix 11mo ago
  Try to twist around words and phrases, at some point it might start to fail. I tried it again yesterday with GPT. GPT-5 manages quite well too in thinking mode, but starts crackling in instant mode. 4o completely failed. It's not that LLMs are unable to solve things like that at all, but it's really easy to find some variations that make them struggle really hard.

chanux 11mo ago

Ah! This is so sad. The manager types won't be able to add an hour (actually, two) to the day even with AI.

edub 11mo ago

I was able to have AI generate an image that made this, but not by diffusion/autoregressive but by having it write Python code to create the image. ChatGPT made a nice looking clock with matplotlib that had some bugs that it had to fix (hours were counter-clockwise). Gemini made correct code one-shot, it used Pillow instead of matplotlib, but it didn't look as nice.

nl 11mo ago

I do playing card generation and almost all struggle beyond the "6 of X" My working theory is that they were trained really hard to generate 5 fingers on hands but their counting drops off quickly.