hi fediverse, I just posted transcripts of a few talks and lectures I've given over the past few years, mostly concerning the connections between machine learning, language and poetry: https://posts.decontextualize.com
(notes and summaries in individual posts below)
"Desire (under)lines: Notes toward a queer phenomenology of spell check" asserts that spell check is a "straightening device" (following Sara Ahmed's use of that term) that attempts to curb spelling's material, expressive, and sensual qualities. Includes a fun proto-Indo-European etymology aside https://posts.decontextualize.com/queer-in-ai-20
(originally prepared for the EACL 2021 Queer in AI Social)
"Language models can only write poetry" is an attempt to categorize the outputs of language models (from Tzara's newspaper cutups to Markov chains to GPT-3) using speech act theory. Touches on the immersive fallacy, Jhave's ReRites, Janelle Shane's AI Weirdness, Kristeva, etc. https://posts.decontextualize.com/language-model
(excerpted from my Vector Institute / BMOLab "distinguished lecture")
@aparrish these are great! as an aside, following up on one of the references in this, do you know when people started refering to bigram (etc) models as "markov chains"? hayes' scientific american article doesn't use the term (he says "eddington monkey", which I much prefer)
@mewo2 that is a really good question and I don't know! Cramer in _Words Made Flesh_ dates it back to Theo Lutz?
@aparrish @mewo2 This 1961 paper is the earliest relevant reference I can find. This biography of the author, Hockett, claims that he was the person who pioneered application of Markov chains to language and grammar in 1955:
earliest generation of text by markov chain: claude shannon, 1948: https://people.math.harvard.edu/~ctm/home/text/others/shannon/entropy/entropy.pdf (calls it a "markoff process")
earliest suggestion of doing this creatively: francois le lionnais, 1963
then by 1968, kawano can say "many computer-aided works of art have been experimentally produced with this method"
the lutz reference is interesting - cramer claims he used markov chains in 1959, but afaik he used a madlib/grammar? http://stuttgarter-schule.de/lutz_schule_en.htm
@darius @aparrish then the whole business seems to have been independently reinvented by bennett in 1977: https://www.jstor.org/stable/27848169 (no reference to markov or shannon, who you'd sort of assume a physicist who previously worked at bell labs would have heard of)
hayes picks it up from bennett, then kenner from hayes, and suddenly you have a second independent tradition
@darius @aparrish kenner and o'rourke (1984) do make reference to shannon, but none of the work from the 60s. kenner was a literary critic who wrote about modernist writers in france, so it's likely he was aware of the oulipo manifesto, but he probably didn't know what a markov chain was, so may not have understood what le lionnais was saying
more markov chain history
@mewo2 @aparrish Not sure if you found this survey paper, it's mostly about music, but it's nice and I like the broad conclusions and it amuses me (especially given Allison's teaching experience) that there is a big focus on "hey Markov can be approximately as good as AI if you do it right" in 1988
more markov chain history
@darius @aparrish yes, I saw that, although re-reading it now I notice that it cites hiller and baker (1963) as deriving their transition probabilities from a traditionally composed piece of music, which definitely fills one of the gaps - still more interested in who was the first to do it for text though
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