[FRIAM] Optimizing for maximal serendipity or how Alan Turing misdirected ALife

Marcus Daniels marcus at snoutfarm.com
Thu May 28 12:39:32 EDT 2020


I would say that companies like Twitter should massively annotate serious offenders and cancel accounts as needed.    It doesn't have to come from top, but it isn't going to come from the bottom.   There should be processes to keep conspicuous liars from ever gaining visibility.   They don't have to involve black vans, as satisfying as that might be.   But maybe advanced natural language processing codes that escalate issues to editors.

On 5/28/20, 9:15 AM, "Friam on behalf of uǝlƃ ☣" <friam-bounces at redfish.com on behalf of gepropella at gmail.com> wrote:

    The additional power is to mislead someone into thinking an expression is about one thing, when it's really about another thing. I.e. in this context, it's a way to troll and "riff" off some arbitrary string you found in some other post. In some contexts, however, it's more serious. Conspiracy theories use metaphor liberally in order to *trick* suckers into thinking something that's simply not true.

    On 5/28/20 9:08 AM, Marcus Daniels wrote:
    > It seems to me like the value of metaphors fits into a sparse dictionary learning approach.   If you want to compress a picture of, say, the new Apple headquarters, it helps if one has seen a circle or a torus in some form, and can just refer to that.   It would also help to have seen pictures of trees and shrubs to tweak, and to have seen solar panels.   Some features will be unique, and simple atoms are needed to refine the image.  I'm skeptical that metaphor is the best enduring representation though.   After one has seen many circles and ovals (or conic sections), a parameterized (even dependent) type becomes evident. 


    -- 
    ☣ uǝlƃ

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