think my favorite reading from last week's paperthon was "Towards knowledge-based tutors: a survey and appraisal of Intelligent Tutoring Systems" by Sokolnicki. it basically breaks down intelligent tutoring systems into each module and connects them with knowledge-based topics

been trying to make use of my schooling and do something with my week off from school so i made a little sudoku solver in using constraint propagation and the most constrained variable heuristic: . was thinking of doing the wasm thing and making a webapp for it but eh, mb later.

interesting article on using speech recognition and nlp to preserve and teach the Maori language te reo and touches on and colonialism

cs grad school, knowledge-based ai, educational technology, raven's progressive matrices 

finishing up my knowledge-based class and up next is educational technology (or ) in two weeks, which i'm looking forward in that i've been wanting to learn about tech applications to education for awhile and also not looking forward to because i still don't have a solid project idea yet.

i liked kbai in ways over other ai classes i've taken in that it gives a theoretical context to everything and ties things to human cognition, it formalizes theories on how humans would solve problems and puts the focus on incremental learning, not having a whole bunch of data points at once but getting little bits of data one-at-a-time, and i kind of find this approach more interesting than the ml approach of lots and lots of data and finding best fits to that data but i'm sure i'll find ml interesting too.

the final project was centered around , which tests an aspect of "intelligence" (put in quotes here because of my wariness of intelligence tests) through figuring out relationships between sets of pictures and looking back, it's kinda neat how i could make an agent do not too bad on it and actually pick out these different kinds of relationships.

i'm derek, he/him. currently in central california and have lived in new york for a bit too

originally went through school up through (lol i'd be surprised if that hashtag actually worked and referred to doctor of musical arts) studying with aspirations of being a "new music" percussionist but didn't stick the landing in music academia. i got a degree somewhere along the way and had been getting heavily into and sorts of things working at a media lab during the dma so when covid, hit decided to go back to (online) grad school studying computer science. things i'm really into studying cs-wise are /#ml things (more leaning on the ai-side but we'll see) and "soft-cs"/"extra-cs" sorta intersectional things like and and starting to read about and other things. not sure where my cs studies will go yet but it'd be nice be able to research ai things more. also, i'm really into / sorta things.

other things i'm into are anime and manga (mostly iyashikei, mecha, and ikuhara things), video games, riichi mahjong, animals (mostly cats, sea otters and puffins), stars are cool, and also vast desolate expanses.

think my website better sums up things:

also, i'm finishing up this class kbai (knowledge-based ai) and it's the third! class i've taken with ai in the name and one thing that i have learned about ai (and maybe life?!) in these three classes is that a lot of problems can be solved with the A* algorithm. so there you go, if you're having problems, any sort of problems, throw A* at it and see what happens.

We are an instance for discussions around cultural freedom, experimental, new media art, net and computational culture, and things like that.

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