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mrbukkake

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Moon landings stopped because the US stopped spending something like 2% of GDP on them. "surely technology advanced to put there at least one man in those 50 years" does technological advancement preclude the need to allocate resources? This is about the level of critical thinking I expect from a conspiracy retard

The Dopamine Trap 7 months ago

Mate what were you hoping a kid would get out of Ingmar Bergman and Antiononi movies and Javascript? Imagine forcing a child to watch Red Desert lmao. And now you're writing off her curiosity because she's not interested in AI architecture or whatever. Let people develop their own interests jfc

The Dopamine Trap 7 months ago

I'm instantly suspicious of anything online that uses the "dopamine" buzzword. The name of the neurotransmitter seems to just be used to mean "good feeling" so the grifter writing the article can make their self help content or specious moralising sound scientific

I see 8 out of 195 "unknowns"which seems to be pretty good coverage. The remaining unknowns are things like serial verb constructions and reduplication, which are very uncommon in European languages. I'm not sure why these are uncoded but based on my knowledge of the methodology for Grambank it's possibly that these typological features aren't mentioned in any source. I agree it seems like these should be straightforward to code however, I'll ask someone

"it" has two functions in English. the first is what you described. The technical term is an anaphor, basically a "syntactic variable" pronoun that stands in for a previous noun phrase in subject or object position. This inspired anaphoric macros in Common Lisp: https://en.wikipedia.org/wiki/Anaphoric_macro

The other function is as a dummy subject, as in "it rained", "it's cold". English grammar requires a subject (unlike many other languages, where a pronoun in subject position can be ommitted without the sentence becoming ungrammatical). So here "it" doesn't refer to anything, it's (haha) just there to fulfill a syntactic requirement

t. linguist

Nice idea, naive implementation which leads to the output being unconvincing as hypothetical English words. I had a brief look and it seems to be proportionally selecting and sticking together sequences of letters sampled from English words (lib/word-probability.ts). This doesn't take into account syllable boundaries, the way the English spelling system maps between phones/phonemes and the phonotactic properties of English which is why the output looks unconvincing.

A better approach would be to use a markov chain built from sampling English text letter-by letter... an even better approach would be to build your stats from some source of English words in IPA transcription with syllable boundaries etc marked, then map from IPA to spelling via some kind of lookup table. We use a similar process in reverse in my research group for building datasets for doing Bayesian phylogenies of language families

Absolutely. These debates are as old as linguistics, there was a lot of controversy in the 19th century between supporters of the tree and wave theories. It's an active area of debate now too with a lot of cross pollination between biology and linguistics. A good recent summary of the issues is Jacques and List 2019 which is available here: https://hcommons.org/deposits/objects/hc:25642/datastreams/C... The authors' application to historical linguistics of the concept of incomplete lineage sorting from population genetics I think is particularly cool

Some of the assumptions about language in this paper are just total junk lol... this one is particularly good "...and for the rest, overlapping vocabulary is a good proxy for similar languages" - this is so wrong I don't even know where to start. The grouping of language by family is also bizarre, the genetic groupings they give for each language are at all sorts of different levels. They say that cultural and geographic proximity was also a factor in grouping, but e.g. the Mongolic and Kra-Dai families have essentially nothing in common apart from the fact the people who speak them look sort of similar to a European. Grouping the Afroasiatic languages Somali and Amharic with the Niger-Congo set also seems like the only criterion was the physical appearance of the speakers...

There is also no way for a reader of the paper to judge the effectiveness of the algorithm. They cite this evaluation of "semantic accuracy", but nothing about the design of the task, participant selection, example data.

This paper is pretty much junk science. Even the reference section is amateurishly formatted