I fed 24 years of my blog posts to a Markov model

I did something similar many years ago. I fed about half a million words (two decades of mostly fantasy and science fiction writing) into a Markov model that could generate text using a “gram slider” ranging from 2-grams to 5-grams.

I used it as a kind of “dream well” whenever I wanted to draw some muse from the same deep spring. It felt like a spiritual successor to what I used to do as a kid: flipping to a random page in an old 1950s Funk & Wagnalls dictionary and using whatever I found there as a writing seed.

First of all: Thank you for giving.

Giving 24 years of your experience, thoughts and life time to us.

This is special in these times of wondering, baiting and consuming only.

I recall a Markov chain bot on IRC in the mid 2000s. I didn't see anything better until gpt came along!

I just realized, one of the things that people might start doing is making a gamma model of their personality. I won't even approach who they were as a person, but it will give their Descendants (or bored researchers) a 60% approximation of who they were and their views. (60% is pulled from nowhere to justify my gamma designation, since there isn't a good scale for personality mirror quality for LLMs as far as I'm aware.)

now i wonder if you can compare vs feeding into a GPT style transformer of a similar Order of Magnitude in param count..

Megahal/Hailo (cpanm -n hailo for Perl users) can still be fun too.

Usage:

      hailo -t corpus.txt -b brain.brn

      hailo -b brain.brn

By default Hailo chooses the easy engine. If you want something more "realistic", pick the advanced one mentioned at 'perldoc hailo' with the -e flag.

I usually have this technical hypothetical discussions with ChatGpt, I can share if you like, me asking him this: aren't LLMs just huge Markov Chains?! And now I see your project... Funny