minkzilla

Thanks for responding, I do think you interpreted my comment correctly.

I see size as negatively correlated (maybe as a semi-direct cause) with preserving company mission. Hence why I was confused by you addressing it. It would never cross my mind to argue that size has protected Costco.

I haven’t read your book, just skimmed the post so I don’t know if it’s convincing. But I’d like to argue that those companies failing their mission is proof that they did not have good leadership. however, that makes the argument a little circular.

I’m aware of FedMart (Acquired podcast on Costco is very entertaining). I think Sol Price was a bad leader and selling out to Hugo Mann was putting profit above other things.

The parent comment didn’t say anything about size or wall street. It said leadership is what has preserved it.

Which it doesn’t seem you have refuted in any meaningful way. You just restated what the parent comment is responding to with no further reasoning as to why leadership doesn’t account for it.

Certainly not the earliest example and can be interpreted in many ways but one of my favorite ancient examples of “introspection” is the phrase “Know Thyself” inscribed on the Temple of Apollo at Delphi.

https://en.wikipedia.org/wiki/Know_thyself

To make them stick you have to decline meetings scheduled during that time

  Location: Salt Lake City
  Remote: Yes or Hybrid
  Willing to relocate: No
  Technologies: C#, .NET, AWS, Postgres, TypeScript, React
  Résumé/CV: josephgilmore.com/static/files/joseph-gilmore-resume.pdf

Maybe instead of all the wealth flowing to a couple huge companies in a couple countries wealth would be distributed more broadly.

Robust and redundant manufacturing spread across the world with more opportunity for innovation?

nextdns lets you set times when domains are blocked. Originally I had it just for my computer but soon realized I needed it for my phone as well.

Author covers how IANA handles Königsberg, it is logically its own timezone.

  An IANA timezone uniquely refers to the set of regions that not only share the same current rules and projected future rules for civil time, but also share the same history of civil time since 1970-01-01 00:00+0. In other words, this definition is more restrictive about which regions can be grouped under a single IANA timezone, because if a given region changed its civil time rules at any point since 1970 in a a way that deviates from the history of civil time for other regions, then that region can't be grouped with the others

  sad but true: learn "yes" then learn blame other grugs when fail, ideal career advice

Location: Salt Lake City, UT

Remote: Yes, hybrid preferred

Willing to relocate: Yes, as long as the location has good access to the outdoors

Technologies: C#, .NET, PostgreSQL, Pulumi, Git, JavaScript, TypeScript, React, Tailwind CSS, Many AWS Services, Docker, Bitbucket Pipelines, Bash. Recently interested in F# and more functional designs

Résumé/CV: https://josephgilmore.com/static/files/joseph-gilmore-resume...

Email: career@josephgilmore.com

Hello, I’m an experienced full stack developer with a focus on backend, performance, and technical leadership. I am looking for an opportunity where I can work with customers and stakeholders to solve the right problems, rather than just slinging code.

I’m open to full time and contract.

The walled garden is not a walled garden if everyone else has doors in.

It doesn't have to be the worst possible implementation to be less desirable than the walled garden for me. I get so much spam in whatsapp, groupMe, telegram, and from sms. Some of it is even from legitimate contacts but then they signed up for something or did something and it sends one of those stupid "join me on {thing}" messages. The only place I don't get spam is imessage

Is that comparable to the energy to run the freezer in the bar?

Yes.

https://text.npr.org is also a text only version of npr

That is what this article is about, changing the expectations of researchers and journals to be willing to publish and read research without p values.

    The "right to privacy" includes the right to medical privacy and privacy over your body. It's not the government's concern to dictate what and how you can treat your own body. The natural extension being that it violates the 14th Amendment for the government to surveil intimate medical decisions.

In terms of the history I have not dug into it but there seems to be conflicting arguments based on your priors. It doesn't seem cut and dry enough to just say it was a right then so it is now, if it was why not just do that instead of the whole privacy deal?

From Dobbs majority opinion: "English cases dating all the way back to the 13th century corroborate the treaties' statements that abortion was a crime."

I am also skeptical of origionalism. I don't know how much bearing 13-18th century common law should have on modern day law, especially when there was assuredly a diverse set of opinions on abortion just like today. Why shouldn't the 20th century have the same amount of weight as the 18th?

To me it seems that even if you believe abortion is morally right Roe was legislating from the bench. These things should come from congress not the supreme court.

I don't agree with overruling Chevron but saying "if they are going to try and override Chevron from the bench without legislation, then we have to ignore them" makes no sense because Chevron was not made by legislation in the first place. It was made by SCOTUS. It comes from the case Chevron U.S.A., Inc. v. Natural Resources Defense Council, Inc.

Could you expand on "our fundamental rights extend to the modern era" and how that connects to the legality of abortion being based on the right to privacy?

Posted elsewhere in this thread but here is the reasoning why from Melissa Holyoak, who voted no. This rule goes further than just the cancellation mentioned in this article and there are some legitimate concerns with that. It is unclear but I think Melissa Holyoak would have voted yes if it was just the cancellation rule.

https://www.ftc.gov/system/files/ftc_gov/pdf/holyoak-dissent...

Chevron deference is about statutory interpretation so it really depends on the statue they are doing it under and any ambiguities that arise around the ability to do this. It may be clearly covered or it may not be, we would have to look. And if there are ambiguities it may go the way of the FTC, but since Chevron is gone, not automatically.

Ah that makes sense. I must admit I did not even read the analysis of the comic.

The point of the comic that that from the outside no one knows how far along hard problems are, not that in and of themselves they are hard. Both the tasks in the comic rely on decades of foundational work in computing and even photography, the author is not saying all of that was easy up until GIS.

    The all items index rose 2.9 percent for the 12 months ending July, the smallest 12-month increase since March 2021.

I guess I misread the first part of the article while skimming. I think the key is this paragraph

    computability is about whether a computer program exists to map inputs to outputs in a specified way; it says nothing about how hard it might be to choose or find or write that program. Writing the program could even require settling God’s existence, for all the definition of computability cares.

I saw it elsewhere in the comments but I think computability as defined in Computer Science and used by the author is more strict a definition than you or I are/were thinking, and that is really the main point of the article. People confuse computability with "can it be computed". Missing values (such as knowledge of God's existence or null values) mean you can not computer something but that is a different thing.

AN interesting and non rigorous way to think of it is can the compiler optimize away the non compute-able part. So this:

    if (God does exist)
      return isPrime(3)

    else 
      return isPrime(5)

But they will save more than $6M the second year because AWS will up their prices.

There is a big practicality problem I see with this algorithm. The thresh defined in the paper relies on the length of the stream. It seems to me that in a scenario where you have a big enough data set to desire a solution that doesn't just store every unique value you don't know the length. I did not make it through all the proofs but I believe they use the fact that the defined threshold has the length in it to prove error bounds. If I were to use this in a scenario where I need to know error bounds i would probably ballpark the length of my stream to estimate error bounds and then use the algorithm with a ballpark threshold depending on my systems memory.

Another practical thing is the "exception" if nothing is removed on line 6 in the original algorithm. This also seems needed for the proof but you would not want in production, though the chance of hitting it should be vanishingly small so maybe worth the gamble?

Here is my faithful interpretation of the algorithm. And then a re-interpretation with some "practical" improvements that almost certainly make the provability of the correctness impossible.

    func CountUnique(scanner *bufio.Scanner, epsilon float64, delta float64, m int) int {

    X := make(map[string]bool)
    p := 1.0
    thresh := int(math.Ceil((12 / (epsilon * epsilon)) \* math.Log(8*float64(m)/delta)))

    for scanner.Scan() {
        a := scanner.Text()
        delete(X, a)
        if rand.Float64() < p {
            X[a] = true
        }

        if len(X) == thresh {
            for key := range X {
                if rand.Float64() < 0.5 {
                    delete(X, key)
                }
            }
            p /= 2
            if len(X) == thresh {
                panic("Error")
            }
        }
    }

    return int(float64(len(X)) / p)

  func CountUnique2(scanner *bufio.Scanner, thresh int) int {

     //threshold passed in, based on system memory / estimates
    X := make(map[string]bool)
    p := 1.0

    for scanner.Scan() {
        a := scanner.Text()
        delete(X, a)
        if rand.Float64() < p {
            X[a] = true
        }

        if len(X) >= thresh {  // >= instead of == and remove the panic below
            for key := range X {
                if rand.Float64() < 0.5 {
                    delete(X, key)
                }
            }
            p /= 2
        }
    }

    return int(float64(len(X)) / p)

I tested it with Shakespeare's work. The actual unique word count is 71,595. With the second algorithm it is interesting to play with the threshold. Here are some examples.

threshold 1000 Mean Absolute Error: 2150.44 Root Mean Squared Error: 2758.33 Standard Deviation: 2732.61

threshold 2000 Mean Absolute Error: 1723.72 Root Mean Squared Error: 2212.74 Standard Deviation: 2199.39

threshold 10000 Mean Absolute Error: 442.76 Root Mean Squared Error: 556.74 Standard Deviation: 555.53

threshold 50000 Mean Absolute Error: 217.28 Root Mean Squared Error: 267.39 Standard Deviation: 262.84

I have had a good manager and here are some concrete examples. He thought it was important to deliver what we promised so he would work with us to get good estimates and would then bring those outside our team and argue for a reasonable time/scope. He would deflect stupid requests (add AI to our project that had no reason for it). In my four years working under him he got us two off cycle inflation adjustments by going to HR and telling them to retain good talent in software we need to pay more.