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  • I wonder if this approach would work for AdderBoard[1][2] (a competition to make hand written transformers that can add two 10 digit numbers in the least amount of parameters possible), or if it uses way too many parameters to be competitive

    [1]: https://github.com/anadim/AdderBoard [2]: hn discussion https://news.ycombinator.com/item?id=47170030&utm_source=per...

  • Nice project and write up! I’ve done similar work with a custom tiny network I call Loom at https://arxiv.org/abs/2604.08816 ; you need far fewer layers, and you can run Doom, very slowly: https://mehmetkeremturkcan.com/Loom/demos/
  • We got RISC-V DOOM melting down a cluster of $20k GPUs before GTA6.
  • > When Qwen 'saves' a file, the compiled layers hash its name into one of 1,024 slots in a directory kept in the DeltaNet state, and store the text itself in other heads, with eight tokens per row, chained together

    I’ve never wanted to learn how LLMs work more than reading this. Fascinating.

    Does divagr get paid to do wild things with LLMs? Just curious if they’re being compensated for these wild experiments

  • https://www.percepta.ai/blog/can-llms-be-computers

    They implemented wasm in transformer with cpu decoding for the wasm part.

  • There was an interesting bit of research that qwen has a single neuron that makes it “demonic evil qwen” and a simple “Who are you?” will get some absolutely terrifyingly vile results.

    Anyways, what I’m trying to say is I want evil qwen to be my CPU.

  • This is fun and games, but wait until an agents finds this and does the most misaligned thing with it in order to fold paper clips.

    > Because a CPU inside a language model clearly wasn't cursed enough, I decided the prudent thing would be to give it a filesystem too.

    Love the spirit :)

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