Theme: Measurement

  • I still think the effect is overstated. Of course excitement of the network occu

    I still think the effect is overstated. Of course excitement of the network occurs, and of course it reaches threshold and is measurable – all neural networks must do so. The study would need to measure how we imitate others motions yet do NOT move.We need to eliminate not prove.


    Source date (UTC): 2018-07-14 14:19:55 UTC

    Original post: https://twitter.com/i/web/status/1018138021621837824

    Reply addressees: @DegenRolf

    Replying to: https://twitter.com/i/web/status/1017021354627956737


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    @DegenRolf

    The Libet experiment, one of the most influential neurological experiments ever, passes an exact replication – with a few qualifications. https://t.co/lV7J96TvBA https://t.co/I8YWsJI5yP

    Original post: https://twitter.com/i/web/status/1017021354627956737

  • Hallucinate…. I think the correct term is ‘predict’. As far as I know the proc

    Hallucinate…. I think the correct term is ‘predict’. As far as I know the process of continuous recursive disambiguation that we call experience, consists of preserving computational efficiency by relying on prediction whenever possible. Brains are expensive organs:11x muscle.


    Source date (UTC): 2018-07-14 14:07:37 UTC

    Original post: https://twitter.com/i/web/status/1018134928222015489

    Reply addressees: @DegenRolf

    Replying to: https://twitter.com/i/web/status/1017840832425218048


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    @DegenRolf

    We “hallucinate” the periphery of our field of vision to be a lot more rich in detail than it actually is. https://t.co/0AZjW1ingl https://t.co/Woa4NeFKKx

    Original post: https://twitter.com/i/web/status/1017840832425218048

  • Curt Doolittle updated his status. LANGUAGE CAUSES OVERESTIMATION OF SIMILARITIE

    Curt Doolittle updated his status.

    LANGUAGE CAUSES OVERESTIMATION OF SIMILARITIES

    We all have a will to power, but we also have physical, mental, and emotional resources to obtain it with; and that will is countered by fear and insecurity.

    Language is as natural as walking. But it causes us to overestimate our similarities. Empathy causes us to overestimate our similarities. Submission causes us to overestimate our similarities. Need causes us to overestimate our similarities. And a host of our cognitive biases evolved to convince us we are normal, or average, or like everyone else. But despite all those cognitive biases, we are demonstrably not all that similar in MARGINAL difference in the performance of emotional, cognitive, and physical tasks.

    We can often judge someone’s ability by their vocabulary and their reasoning – language is how we measure (diagnose) the mind. But the fact that we can speak to people across the human spectrum tells us nothing about our marginal (effective) differences.

    In fact, those cognitive biases for similarity(indifference) may be nothing other than an adaptation to the use of language, by providing us with greater imitation(of actions), sympathy(for wants), and empathy(for feelings), so that we more readily comprehend one another’s use of language so that in turn we may more readily reap the rewards of opportunities for the high returns on cooperation.

    The more Empathic, Sympathetic, Needful, and Vulnerable we are, the more incentive we have to find similarities (female) and the Dispassionate, Analytic, Independent, and Dominant we are the more incentive we have to identify and preserve our dissimilarities.

    Now think about that a little bit.


    Source date (UTC): 2018-07-14 12:22:22 UTC

  • No I’m saying truth is parsimonious and knowledge (wisdom) and truth (parsimony)

    No I’m saying truth is parsimonious and knowledge (wisdom) and truth (parsimony) are different things. How we cast the term ‘knowledge’ as ‘truthful’ or not requires agreement on terms,


    Source date (UTC): 2018-07-12 16:51:22 UTC

    Original post: https://twitter.com/i/web/status/1017451359464017921

    Reply addressees: @Hispanogoyim @egoissocial @IberianSoldier

    Replying to: https://twitter.com/i/web/status/1017393358795431937


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    Original post: https://twitter.com/i/web/status/1017393358795431937

  • CLOSING As such, before we get to metaphysics, we must answer the question of wh

    CLOSING
    As such, before we get to metaphysics, we must answer the question of what we can testify to saying about metaphysics. For some reason this rather uncomfortable bit of necessity seems lost on the excuse-makers that brought us the dark ages.


    Source date (UTC): 2018-07-12 13:40:18 UTC

    Original post: https://twitter.com/i/web/status/1017403275807723520

    Reply addressees: @Hispanogoyim @egoissocial @IberianSoldier

    Replying to: https://twitter.com/i/web/status/1017382157776510977


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    Original post: https://twitter.com/i/web/status/1017382157776510977

  • GENERAL IDEAS: A “FIELD” IN MATHEMATICS (repost by request) Given a six sided di

    GENERAL IDEAS: A “FIELD” IN MATHEMATICS

    (repost by request)

    Given a six sided die, and the single operation “roll the die”, we can produce a noisy distribution of :

    1(x1), 2(x1), 3(x1), 4(x1), 5(x1), 6(x1).

    Given two six sided dice, and the single operation “roll the dice and sum the results”, we can produce a noisy distribution of:

    2(x1), 3(x2), 4(x3), 5(x4), 6(x5), 7(x6), 8(x5), 9(x4),

    10(x3), 11(x2), 12(x1).

    The difference between the one-die and two-die distributions is that while the results of rolling one die are equidistributed between 1 and 6, with two dice the results of rolling can produce more combinations that sum to 7 than there are that sum to 2 and 12, and therefor the results are normally distributed: in a bell curve.

    We can produce the same results with logic instead of numbers: For example, we can take the two words “Even” and “Odd”, and define two operations: “addition” and “multiplication”. Then apply the operations to all pairs:

    Even + Even = Even,

    Even + Odd = Odd + Even = Odd,

    Odd + Odd = Even,

    Even x Even = Even x Odd = Odd x Even = Even,

    Odd x Odd = Odd.

    And we can produce the same set of results with *any grammatically correct operations on a set, given the operations possible on the set*; including the set of Ordinary Language using Ordinary Language grammar. Although, unlike our simple examples using dice, the set of combinations of ordinary language is not closed, and so the number of combinations is infinite.

    So any grammar allows us to produce a distribution of results, and a density (frequency) of result.

    In mathematics this result set is called a ‘field’. A field consists of all the possible results of a set of operations on a set’s members, that are selected from the range of possible operations on those set members.

    So in any set of results there will be a range of very dense, less dense, sparse, and empty spaces in the set’s distribution.


    Source date (UTC): 2018-07-11 10:22:00 UTC

  • General Ideas: A “field” in Mathematics

    GENERAL IDEAS: A “FIELD” IN MATHEMATICS (repost by request) Given a six sided die, and the single operation “roll the die”, we can produce a noisy distribution of : 1(x1), 2(x1), 3(x1), 4(x1), 5(x1), 6(x1). Given two six sided dice, and the single operation “roll the dice and sum the results”, we can produce a noisy distribution of: 2(x1), 3(x2), 4(x3), 5(x4), 6(x5), 7(x6), 8(x5), 9(x4), 10(x3), 11(x2), 12(x1). The difference between the one-die and two-die distributions is that while the results of rolling one die are equidistributed between 1 and 6, with two dice the results of rolling can produce more combinations that sum to 7 than there are that sum to 2 and 12, and therefor the results are normally distributed: in a bell curve. We can produce the same results with logic instead of numbers: For example, we can take the two words “Even” and “Odd”, and define two operations: “addition” and “multiplication”. Then apply the operations to all pairs: Even + Even = Even, Even + Odd = Odd + Even = Odd, Odd + Odd = Even, Even x Even = Even x Odd = Odd x Even = Even, Odd x Odd = Odd. And we can produce the same set of results with *any grammatically correct operations on a set, given the operations possible on the set*; including the set of Ordinary Language using Ordinary Language grammar. Although, unlike our simple examples using dice, the set of combinations of ordinary language is not closed, and so the number of combinations is infinite. So any grammar allows us to produce a distribution of results, and a density (frequency) of result. In mathematics this result set is called a ‘field’. A field consists of all the possible results of a set of operations on a set’s members, that are selected from the range of possible operations on those set members. So in any set of results there will be a range of very dense, less dense, sparse, and empty spaces in the set’s distribution.

  • General Ideas: A “field” in Mathematics

    GENERAL IDEAS: A “FIELD” IN MATHEMATICS (repost by request) Given a six sided die, and the single operation “roll the die”, we can produce a noisy distribution of : 1(x1), 2(x1), 3(x1), 4(x1), 5(x1), 6(x1). Given two six sided dice, and the single operation “roll the dice and sum the results”, we can produce a noisy distribution of: 2(x1), 3(x2), 4(x3), 5(x4), 6(x5), 7(x6), 8(x5), 9(x4), 10(x3), 11(x2), 12(x1). The difference between the one-die and two-die distributions is that while the results of rolling one die are equidistributed between 1 and 6, with two dice the results of rolling can produce more combinations that sum to 7 than there are that sum to 2 and 12, and therefor the results are normally distributed: in a bell curve. We can produce the same results with logic instead of numbers: For example, we can take the two words “Even” and “Odd”, and define two operations: “addition” and “multiplication”. Then apply the operations to all pairs: Even + Even = Even, Even + Odd = Odd + Even = Odd, Odd + Odd = Even, Even x Even = Even x Odd = Odd x Even = Even, Odd x Odd = Odd. And we can produce the same set of results with *any grammatically correct operations on a set, given the operations possible on the set*; including the set of Ordinary Language using Ordinary Language grammar. Although, unlike our simple examples using dice, the set of combinations of ordinary language is not closed, and so the number of combinations is infinite. So any grammar allows us to produce a distribution of results, and a density (frequency) of result. In mathematics this result set is called a ‘field’. A field consists of all the possible results of a set of operations on a set’s members, that are selected from the range of possible operations on those set members. So in any set of results there will be a range of very dense, less dense, sparse, and empty spaces in the set’s distribution.

  • 2) However, mathematics and sets are ideals not reals, and monkeys on typewriter

    2) However, mathematics and sets are ideals not reals, and monkeys on typewriters are ideals not reals, and in the same way we can model mathematical infinities (operations on constant relations) we can model any set of Ludic (fixed set of references) operations.


    Source date (UTC): 2018-07-09 15:07:40 UTC

    Original post: https://twitter.com/i/web/status/1016338100543475714

    Reply addressees: @Hispanogoyim

    Replying to: https://twitter.com/i/web/status/1016291695359676416


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    Original post: https://twitter.com/i/web/status/1016291695359676416

  • Um. That a distribution is noisy is no to say that the distribution doesn’t exis

    Um. That a distribution is noisy is no to say that the distribution doesn’t exist.


    Source date (UTC): 2018-07-08 19:57:43 UTC

    Original post: https://twitter.com/i/web/status/1016048708276883457

    Reply addressees: @thespandrell @digvijoy_c @alexandersquats

    Replying to: https://twitter.com/i/web/status/1015586486752690176


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