i made yet another partial ai seed and i was typing up both an itemized simplified description and a detailed one involving personal theory and code, of it to help preservation, but a finger spasm lost the whole typing again :/ the code is a mess right now and i'm having psychotic-like spasms associated, similar to normal self-modifying ai inhibition maybe i'll spam parts in this as a thread. i liked the organized thing tho. the whole goal of it was to do it really simplistically, really similar to things already existing, very few changes, move theories into spaces that were simple and similar, etc. Long story short, you can make a transformed model generate an improved transformer model of the same or larger size if you do something like the following: - shrink the size to handle only a tiny bit at once, (i used the largest 1-d slice length of the largest parameter) - make the input context huge so you can feed it a whole model - train on only 1 data pair at once - make a separate model or layers for each output model parameter so they can specialize - feed the output back into the input as needed so it can save its work and move on the biggest theoretical component was the idea that an arbitrarily small agent can use a random-access infinite scratchpad and a supply of high-level functions to accomplish an arbitrarily complex task (turing machine). the input context is the scratchpad. [interesting theory that you could maybe turn it into procedural code by reinterpreting it that way]