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Show HN: A Dalle-3 and GPT4-Vision feedback loop

dalle.party

21–30 of 156 posts

Re: Show HN: A Dalle-3 and GPT4-Vision feedback loop

#21
It’s cool to see how certain prompts and themes stay relatively stable, like the gnome example. But then “cat lecturing mice” quickly goes off the rails into weird surreal sloth banana territory.

My best guess to try to explain this would be that “gnome + art style + mushroom” will draw from a lot more concrete examples in the training data, whereas the AI is forced to reach a bit wider to try to concoct some image for the weird scenario given in the cat example.

Re: Show HN: A Dalle-3 and GPT4-Vision feedback loop

#22
Cool idea! I made one with the starting prompt "an artificial intelligence painting a picture of itself": https://dalle.party/?party=wszvbrOx

It consistently shows a robot painting on a canvas. The first 4 are paintings of robots, the next 3 are galaxies, and the final 2 are landscapes.

Re: Show HN: A Dalle-3 and GPT4-Vision feedback loop

#26
I figured this would quickly go off the rails into surreal territory, but instead it ended up being progressive technological de-evolution.

Starting prompt: "A futuristic hybrid of a steam engine train and a DaVinci flying machine"

Results: https://dalle.party/?party=14ESewbz

(Addendum: In case anyone was curious how costs scale by iteration, the full ten iterations in this result billed $0.21 against my credit balance.)

Re: Show HN: A Dalle-3 and GPT4-Vision feedback loop

#27
post #23
post #2

Also, descent into Corgi insanity: https://dalle.party/?party=oxXJE9J4

So do I understand correctly that the corgi was purely made up from GPT-4's interpretation of the picture?

No, in that case there is a custom prompt (visible in the top dropdown) telling GPT4 to replace everything with corgis when it writes a new prompt.

Re: Show HN: A Dalle-3 and GPT4-Vision feedback loop

#28
post #25

Question: how are you protecting those API keys? I'm reluctant to enter mine into what could easily be an API Key scraper.

The entire thing is frontend only (except for the share feature) so the server never sees your key. You can validate that by watching the network tab in developer console. You can also make a new / revoke an API key to be extra sure.

Re: Show HN: A Dalle-3 and GPT4-Vision feedback loop

#30
The "create text version of image" prompt matters a ton.

I tried three, demo here:

default

  https://dalle.party/?party=JfiwmJra
hyper-long + max detail + compression - This shows that with enough text, it can do a really good job of reproducing very, very similar images

  https://dalle.party/?party=QtEqq4Mu
   
hyper-long + max detail + compression + telling it to cut all that down to 12 words - This seems okay. I might be losing too much detail

  https://dalle.party/?party=0utxvJ9y
Overall the extreme content filtering and lying error messages are not ideal; will probably improve in the future. If you send too long, or too risky a prompt, or the image it generates is randomly too risky, you either get told about it or lied to that you've hit rate limits. Sometimes you also really do hit ratelimits.

Also, you can't raise your rate limits until you prove it by having paid over X amount to openai. This kind of makes sense as a way to prevent new sign-ups from blowing thousands of dollars of cap mistakenly.

Hyper detail prompt:

Look at this image and extract all the vital elements. List them in your mind including position, style, shape, texture, color, everything else essential to convey their meaning. Now think about the theme of the image and write that down, too. Now write out the composition and organization of the image in terms of placement, size, relationships, focus. Now think about the emotions - what is everyone feeling and thinking and doing towards each other? Now, take all that data and think about a very long, detailed summary including all elements. Then "compress" this data using abbreviations, shortenings, artistic metaphors, references to things which might help others understand it, labels and select pull-quotes. Then add even more detail by reviewing what we reviewed before. Now do one final pass considering the input image again, making sure to include everything from it in the output one, too. Finally, produce a long maximum length jam packed with info details which could be used to perfectly reproduce this image.

Final shrink to 12 words:

NOW, re-read ALL of that twice, thinking deeply about it, then compress it down to just 12 very carefully chosen words which with infinite precision, poetry, beauty and love contain all the detail, and output them, in quotes.

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