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I wonder how she puts her left leg like that. It seems physically impossible to bend it sideways even if you are Elvis.



https://foto-history.livejournal.com/18509639.html

upd. I guess it's something like that:

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Smuggling in the Kan extension for dummies.


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https://www.youtube.com/watch?v=xTVSMJhDoOQ

Technology toolkit re-use is an extension problem. E.g. Julius Cesar's guide for building army camps using common agricultural approaches of the time. The use of steam engine manufacturing toolkit for railroads, steam ships, etc.

Technology choice or development is a lifting problem. E.g. discovery/choice of the right data set for a desired ML application (see IBM's recent failure vs TikTok's success).

In the LRRH narrative we see the failure of an existing solution to the extension problem, i.e. the werwolf destroys the girl's ability to deliver the medicine to her grandma.
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This is probably the most beautiful illustrations to Red Riding Hood that I've ever seen. The wolf figure is pure evil and it oozes temptation mixed with deception.



Read more... )
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В декабре будет год с тех пор, когда я был в Европе. С американским паспортом сейчас ни в одну приличную страну не пускают. Тоска.


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AI is better at understanding people than the other way around.



The original post is about how one perceives political celebrities based on external attributes, not the substance of the discussion. That is, the focus is on the image not content. Therefore, the AI bot sees through the veil of words and detects fashion, while the human deludes herself with the appearances of politics.
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As they say on Twitter, this didn't age well:


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The financial crisis killed America's Second Industrial Revolution, which started in the early 1960s.



https://www.wsj.com/articles/trumps-promise-to-revive-coal-thwarted-by-falling-demand-cheaper-alternatives-11600269350
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Как ни странно, у молодежи в России есть будущее. А в Белоруссии нет.
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С наступающим!


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В декабре в Париже у меня будет свидание с Дорой. Лет десять ее уже не видел.

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The obligatory sunset picture. Well, it's almost time to go home.

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Rather than assuming that both situations (e.g., past and present) are random samples from the same underlying population, we posit two distinct settings. We refer to the first as L (for learning) and the second as T (for target) and ask how these match.

DOI: 10.1177/0963721415591878

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