Show HN: Watch 14-Byte AI "brains" attempt to solve a 2D maze (Its hard)

5 comments

• vunderba8 hours ago
  Neat! Maybe consider doing a longer postmortem&#x2F;blog post on this.<p>Small bit of feedback: it might help to add an explicit small (i) icon for areas which contain tooltips especially for interfaces (phones) that don&#x27;t support hover events. I discovered that the models (such as pareto-r1) had additional information by complete accident~
  • purple-leafy4 hours ago
    Thank you for your feedback!<p>I definitely will be - my experimentation outpaced my understanding a bit, so I’m slowing down to understand and verify my exact claims.<p>One of the most fun projects I have ever worked on and I’m excited to share the discoveries.<p>What kind of postmortem would you like to see? A blog or a hackernews post? And what interests you the most? Is it the compression, the visuals, the neural networks, the discoveries, or something else?<p>I will update the frontend based on the icon feedback for sure :) thank you!
• iwhalen11 hours ago
  If your goal is to get the network as small as possible, you could try using NEAT[1]. A cool example of a small network for a hard task using NEAT is MarI&#x2F;O[2].<p>[1]: <a href="https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Neuroevolution_of_augmenting_topologies" rel="nofollow">https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Neuroevolution_of_augmenting_t...</a><p>[2]: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=qv6UVOQ0F44" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=qv6UVOQ0F44</a>
  • purple-leafy4 hours ago
    I will be reading this one asap, my goal is as small as possible ! So far 14 bytes has been hard for me to beat
• purple-leafy17 hours ago
  Facts:<p>- 14 Bytes does not include the runtime! - All that counts towards the 14 Bytes is the model weights - Lack of git history is because my actual repo is private, this is just the frontend for now + models
• elil1713 hours ago
  I would love to understand what the inputs actually are. Very neat visualization.
  • purple-leafy4 hours ago
    Thank you I will update the frontend with a legend and some better alignment understanding with the visuals.<p>As a quick note, they are mostly immediate environment observations like “is there a wall in front of me, to my left, to my right” etc or “was my last move illegal”.<p>But every model is different, some have very rich input information like “there is a wall diagonal to my front right” and some only have very coarse inputs.<p>Because I have trained over 2000 models now I need to go back and get an LLM to label the inputs for me, definitely not a manual task :)
• zaydmulani10 hours ago
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