The silver lining: “The amount of energy needed to sustain bullshit *that is obvious to all* is an order of magnitude bigger than that needed to produce it.”
When I called my congressman, the Democrat John Mannion, to say I would no longer support him financially because of his vote for crypto, the person I spoke to said it was a shame to lose support over one issue, which tells me they don't understand how seriously wrong this is. He also voted for the Laken Riley act, another black mark.
Very pleased to see you have recovered and with a good healthy “feistiness and all without the assistance of RFK. I’m thinking we should rename crypto as krypton, which should be much more accurate.
Within the context of scientific analysis, Brandolini's law can be put to use not just on the bullshit being presented, but can also bring the bullshitter under scrutiny as well. When the lying becomes apparent on multiple occasions throughout a stretch of scientific research, the bullshitter becomes more obvious than the bullshit itself, and because the bullshitter loses credibility, the ensuing bullshit is easier to identify.[11][12] In addition, the challenge of refuting bullshit does not just come from its time-consuming nature, but also from the challenge of defying and confronting one's community.
then 1 Dem. leader - the lowest ranked Rep. Joe Neguse - voted against the GENIUS bill. Even 4 out of 5 Dem. leaders is horrible. I don't see myself ever voting for another Democrat until ALL these leaders are gone.
Order and magnitude are separate concepts in mathematics. "Order of magnitude" is a barbarism but one that is sadly commonplace.
Magnitude refers to the size of a number (or the evaluated resulted of a function). In base 10, a thousand is a magnitude bigger than a hundred.
Order refers to the scaling property of a function. Computer scientists use "Big O" notation to talk about, for example, how different algorithms for searching or sorting arrays of N elements require different numbers of steps to run as N grows, e.g. O(nlog(n)) is an algorithm that takes n * log(n) steps to act on an array of n items.
When I called my congressman, the Democrat John Mannion, to say I would no longer support him financially because of his vote for crypto, the person I spoke to said it was a shame to lose support over one issue, which tells me they don't understand how seriously wrong this is. He also voted for the Laken Riley act, another black mark.
Didn't have a crypto takedown on the cards this week but thank you 🙌
Very pleased to see you have recovered and with a good healthy “feistiness and all without the assistance of RFK. I’m thinking we should rename crypto as krypton, which should be much more accurate.
Within the context of scientific analysis, Brandolini's law can be put to use not just on the bullshit being presented, but can also bring the bullshitter under scrutiny as well. When the lying becomes apparent on multiple occasions throughout a stretch of scientific research, the bullshitter becomes more obvious than the bullshit itself, and because the bullshitter loses credibility, the ensuing bullshit is easier to identify.[11][12] In addition, the challenge of refuting bullshit does not just come from its time-consuming nature, but also from the challenge of defying and confronting one's community.
This is my kind of science!
"every member of the House Democratic leadership voted for the [GENIUS] bill"
Not exactly true, if your definition of the 5 Dem. House leaders is this web page,
https://www.house.gov/leadership
then 1 Dem. leader - the lowest ranked Rep. Joe Neguse - voted against the GENIUS bill. Even 4 out of 5 Dem. leaders is horrible. I don't see myself ever voting for another Democrat until ALL these leaders are gone.
Order and magnitude are separate concepts in mathematics. "Order of magnitude" is a barbarism but one that is sadly commonplace.
Magnitude refers to the size of a number (or the evaluated resulted of a function). In base 10, a thousand is a magnitude bigger than a hundred.
Order refers to the scaling property of a function. Computer scientists use "Big O" notation to talk about, for example, how different algorithms for searching or sorting arrays of N elements require different numbers of steps to run as N grows, e.g. O(nlog(n)) is an algorithm that takes n * log(n) steps to act on an array of n items.
An "order of magnitude" is a nonsense.