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  • It's Genetic Programming via LLM, cool!
    by iambenm
  • This is really nice, and it's a good reminder that we're so early with regards to how AI can be used to make art.

    And the fact that it's flowers creates a pretty nice mental model for it! One can plant seeds and cultivate the plants that grow from them but ultimately aren't in complete control of the outcome.

    by Brendinooo
  • Really liked your video presentation, thanks for sharing, especially the part of image generators locking us into a certain context immediately, reducing us to spectators instead of creatives.

    Played a lot with p5js some years ago, might pick it up again and try some of your ideas. The reinforcement learning part sounds about above my skill level though. :)

    by mskogly
  • Really awesome! Been thinking about how to get LLMs to do generative art (yes, the pre-AI definition of generative art). Love to see this approach and results!
    by lxrogers
  • A fun diversion and general capabilities test that I like to do is to ask the models to "programmatically assign color and alpha values to a png to generate an image. it should be a painting or whatever subject interests you in the moment. 800x800" or something along those lines, and they'll make a "generative" art piece for you. For example first time I tried this Claude Fable used Python to generate a transparent PNG of a quartz crystal with inclusions that were variable depending on the seed number. So anyway yeah it's surprisingly easy to get the frontier models nowadays to make cool art!
    by lindyman
  • Thank you for sharing this! did not expect to find my work on HN randomly haha
    by kickingkeys
  • I think this actually might be one of the best ways to train people to use AI. I can see this honing people's prompting abilities and expressiveness, along with constraints and desired outcome.

    Wild the possibilities

    by _boffin_
  • Beautiful.

    I am reminded of a paper I was inspired by a long time ago [0], (okay it's 2018 so I guess just 8 years ago, but it feels like longer, from the before-times), that demonstrated learning brush strokes. At the time there was already a lot of work on GANs, but these are pixel-based methods, and I was really interested in the idea of how to derive descriptive methods of scene generation/understanding. I found this work really interesting because it combined RL and GAN techniques in a creative way. I miss that kind of research.

    Now of course VLMs have shown that you can mix modalities in generalized sequence-to-sequence problems and it doesn't surprise me that this kind of thing is possible, but it's so nice to see it done well using modern techniques.

    [0] https://proceedings.mlr.press/v80/ganin18a.html

    by radarsat1

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