stopping

Strongly agree. I'm deeply disappointed with the depth of discourse in other internet communities which implement upvoting; the highest voted comments are usually shallow hot takes or low-effort jokes. However, on HN the most substantial and interesting comments are the ones that typically find their way to the top of the discussion. I can't remember the last time I ever learned anything new and interesting from any other social media site, whereas the HN community continuously offers a wealth of deliberately considered perspectives.

Major thanks to the HN community and those who keep it running!

Inflation is a safety net. Inflation prevents populations from fearfully (or speculatively) hoarding money. When a population collectively decides to hoard money, demand for goods and services tanks, jobs are cut in response, and so on in a vicious cycle until the entire economy grinds to a halt. Such a situation is extremely difficult to recover from without government monetary policy to stimulate demand.

Not exactly. The only way a state government could deprive the federal government of federal tax income is to tax their residents at a rate of 100%. Even with an uncapped SALT deduction, the federal government is entitled to tax whatever income you have leftover after paying state/local taxes.

Sales tax is indeed double taxation. That's why you're allowed to deduct it on your federal taxes under the SALT rules.

I addressed this in another comment: https://news.ycombinator.com/item?id=28452001

To summarize, you have to have the ability to correct statistical aberrations after manufacture via extensive validation and testing, as opposed to design aberrations which can largely be eliminated through destructive iteration. Without the former process, you'll launch a million telescopes and not a single one will work.

I do agree with this. Most systems have significant basis in unnecessary or outdated methodologies. I think with the JWST project (with partial hindsight), we probably could have benefited from having a "stepping stone" optical telescope after Hubble which we could have used to proof out some of the hard parts of JWST. We learn quite a lot from just running missions beginning-to-end, and extremely long cycle times sacrifice this learning opportunity. It also means that we focus less on developing extensible "platforms" in favor of one-of-a-kind systems which have somewhat less carryover knowledge for the next project. Shorter mission timelines mean that you can better leverage state-of-the-art technology, rather than being forced into a design which constrains you to decade-old technology.

There are two key differences between rockets and space telescopes (any space-faring probe, really) which prohibits "iterate to failure" as a development technique:

1. Forensics difficulty. You need extensive data to debug issues for complex systems. You can collect so much more data from terrestrial testing, which allows you to do the extensive forensic analysis required to achieve the required component reliability. Once you put a telescope in space, you can't inspect it anymore. A lot of the sensitive components which might fail on JWST have to be inspected to microscopic precision in order to perform adequate failure analysis.

2. Design requirements are far, far more precise. Many failures in deep space are effectively impossible to correct in later iterations due to point 1. Telemetry and sensor data is enough to debug rockets, but for JWST you would need to ship so much extra data/sensor infrastructure alongside the telescope that the whole project becomes recursively intractable.

The system complexity is so high that you absolutely must have the ability to make arbitrary system corrections because the chance of "building everything correctly the first time" is effectively zero, even with perfect hindsight! Essentially, any time you build the thing from scratch, you will always find mission-ending statistical deviations. The objective of on-ground testing is to identify and correct those specific deviations, until the whole system is within design tolerances. If you were to totally rebuild it, the next iteration will have a totally different set of statistical deviations which will need to be corrected. This process of development involves "hardening" the entire system through extensive testing, because it impossible to build a fully-hardened system to start with, even after "learning" from previous attempts.

I don't disagree with your point re: Boeing v SpaceX, but precision scientific instrumentation is a very, very different domain where "move fast and break things" cannot be naively applied. The sensitivity to failure is so ridiculously high that you need 6 to 7 sigmas of reliability for each of ten thousand critical components in order to even have just a 90% chance of mission success. Something as simple as an instrument bring slightly out of tolerance, faulty rad-hardening on a CPU, the sun shield having a minor tear, are all enough to completely jeopardize the entire mission. As a fully integrated system, JWST is at least an order of magnitude more complex than Starship, whose main design goals (launch, orbit, land, don't explode) tend to favor a more iterative approach.

The cost doesn't come from a lack of production efficiency. A significant fraction of the cost is for testing/validation of the spacecraft, which must be done for every unit you produce. Simulating operating conditions on Earth is extremely expensive and time consuming.

This is a better example, which also illustrates that planting evidence is a criminal offense: https://www.youtube.com/watch?v=UANRvFNc0hw

And to GP's point, here's an NYT investigation into a suspicious arrest from 2018: https://www.youtube.com/watch?v=DrfZuPFrH8A

This is not true. Using the U.S. as an example, there have been over 70,000 COVID deaths since April (previous 5 months). Yearly auto accident deaths typically are between 30,000 and 40,000. COVID has killed twice as many people in less than half the time, even during a period of widely available vaccines.

Sample size isn't the problem you think it is. The difference in statistical confidence between sample sizes of a hundred million (COVID vaccine doses) and a billion (flu vaccines) is basically zero.

Perhaps you could try to make a case that we need more time to evaluate the long-term effects of the vaccines. Historically speaking, we know that side effects for any vaccine are incredibly rare after more than a few months. mRNA vaccine technology has been researched for decades and there are no indicators that there are long-term complications resulting from their use. Other vaccine technologies show similar long-term safety.

My crows have done this sometimes when I'm on my bike! Although they'll usually only follow alongside me as far as their territory extends, about the length of a parking lot. Not quite a phalanx either, just a bird or two.

Pre-WFH, there were several groups of crows near my office covering distinct territories around my building. I made a habit of feeding and interacting with a few of these groups, every day for several months. Here are my experiences:

* I did indeed see a crow "anting" one time, and was initially as bewildered as the photographer in TFA. Surprisingly I was able to get much closer to the bird than they normally allow, but stepped back as soon as I saw it wasn't actually in distress.

* The best way to get close to a crow is to back up towards it; they are extremely wary of eye contact and will immediately become alert if you look at them or move towards them with your body facing forward. Over time, I used this method to get close to them and demonstrate that I wasn't a threat. I "trained" the crows to recognize that if they let me get close, I'll drop some food for them. After a while you don't have to do the backwards shimmy, but it's a good default strategy for approaching naturally skittish creatures.

* If you feed crows in exactly the same place every day, they will recognize you and fly to the "feeding spot". Crows pay very close attention to your movements and behaviors, and like most animals will try to develop a mental model to figure out when you're going to feed them. If presented with consistent causal behaviors, the birds will essentially train themselves.

* Crows are very sensitive to changes in appearance and behavior. I switched jackets one day and was met with immediate suspicion.

* My most fruitful experiment was right before the lockdown. I would stand in a specific location for a little while and watch the birds (watching them from a distance piques their curiosity and alertness to you). With them watching, I would pretend to plant food somewhere nearby and then move away. The crows would fly over, and I would immediately reward them. After a few weeks of this, I began gesturing towards nearby objects with my hand, and the birds would investigate the object immediately after I move away. After consistently rewarding this behavior, I was able to advance to "pointing to a semi-nearby object with my arm". One crow eventually figured out how to fly to the object I was pointing at, and I did a few successful tests to make sure the crow would fly specifically to the object I was pointing at, and not at some other nearby object. I have yet to train them to land on distant objects, but I'm hopeful!

* Crows like pistachios (they have multiple techniques for cracking the shell), and love cashews and peanuts (unsalted are best for the birds). They'll almost always opt for the "more convenient" snack, especially when they're competing with other crows. I try to reward the "bravest" crows first, by slowly moving away from the food pile until one crow moves in. Like other animals, crows also learn by observing the reward loop from a distance, and you can use this to get a large number of them to trust you.

* Crows are very curious when they feel safe, and it is mutually entertaining to set up unusual scenarios (such as hiding food inside or under tricky objects, like empty water bottles or closed paper containers).

> One need only look at wtfhappenedin1971.com to understand why.

A bunch of scary-looking graphs haphazardly thrown together with huge ads abutting either end is not an argument. This comment is guilty of its own accusation: cherry-picking data to paint a dishonest narrative.

I don't think that differences in life expectancy are the main driver for the results seen here. Life expectancy between sexes varies by 3-5 years, so you should expect the average age difference be around 2 years. I don't think this is enough to cause a 12-year difference in the peak dating pools, assuming that the demographics of the single population match the overall population. In reality, the demographics do not match; younger men (<30 y/o) and older women (>50 y/o) are more likely to be single compared to the baseline:

https://www.pewresearch.org/social-trends/2020/08/20/a-profi...

50% of men under 30 are single, compared to ~25% of men 30 and above.

49% of women over 65 are single, compared to ~27% of women under 65.

Edit:

Here are the population proportions for each of the age bands in the above source (numbers fudged from https://www.populationpyramid.net/united-states-of-america/2...):

    18-29: 17% (Avg. age ~24)
    30-49: 28% (Avg. age ~40)
    50-64: 21% (Avg. age ~57)
    65+:   17% (Avg. age ~72)

It's not too hard to calculate the age of the average single man/woman. The average single man is ~43. The average single woman is ~51.

> This isn't a calculus I've thought through in depth, but the answer is almost certainly not "nobody."

That's fair; I don't doubt that there are isolated, contemporary examples where un-masking would have led to a better situational outcomes.

As far as if "public reaction" should factor into individual choice, my stance is more based in principle than practicality; bending to the will of popular opinion is a strategy that is highly stifling, due to the fickle and stochastic nature of group opinions. I think it's dangerous to suggest that there are any societal circumstances where everyone should just "side with the crowd." Superseding reason with groupthink rarely yields anything but disastrous outcomes, so I believe that if one can tolerate the ridicule and aggression, then they should stand by their principles.

> But it's pretty myopic to ignore the history of superficial social striations.

I'm having difficulty understanding what this comment is implying. Should other peoples' opinions and reactions to wearing a mask (or not wearing a mask) be a factor in one's own individual decision making?

Equating basic precautionary measures with fear culture doesn't sound right. There's absolutely nothing inherently wrong with an individual deciding to wear a mask. I do agree that the tribalism that surrounds masks is ugly and harmful to society as a whole, but I'm fundamentally opposed to throwing away smart, simple solutions just because they're stained by politics.

Anecdotally, dozens of people in my social circle (aged 30-50) reported that the worst vaccine side effects were (1) a sore arm and (2) 24-48 hours of sleepy brain fog (even after the second dose). Among first and second degree connections on Facebook, I know of exactly two people who experienced the full gamut of flu-like symptoms, such as fever, chills, and whole-body aches for a day or two. Take this with a grain of salt, but I'd estimate an upper bound of 10% for "moderately unpleasant" side effects among young-ish, moderately healthy individuals.

FYI: The J&J vaccine directly injects DNA into the cell nucleus to begin spike protein production. DNA-based vaccines have been tested before (see J&J's Ebola vaccine), and I believe the general consensus is that mRNA is a safer technology due to its inherently short lifetime.

The number of excess deaths in the world is quite similar to the number of known COVID deaths. In fact, excess deaths is the higher number. It's very likely that the number of COVID deaths is currently underestimated, as spread of other infectious diseases has been drastically diminished by the lockdowns.

What is the social cost of wearing masks? Genuinely curious.

My personal rules of thumb are:

1. Keep the business logic as un-indented as possible.

2. If there are several branching happy-paths, give them the same indentation.

I generally choose the "early return" pattern if there is (1) more than one precondition that must be met before executing a (2) medium-sized "happy path" code body. In these situations, having the meat of your function inside a deeply nested flow control structure is unwieldy, and for indentation-sensitive languages it is far too easy to lose track of which condition body you're currently in. In Python, this has bitten me more times than I can count.

So, my standard "early return" pattern follows this prototype:

  if (!discriminatingPrecondition) {
    // Some cases we ignore intentionally.
    return false;
  }

  if (!criticalPrecondition) {
    std::err << "Error: Precondition not met!" << std::endl;
    return false;
  }

  if (!fixablePrecondition) {
    scheduleRemedyForPrecondition();
    return false;
  }

  // Happy path
  
  return true;

However, for code with a single precondition statement without specific remediation logic for each precondition, I might occasionally prefer:

  if (preConditionA && preConditionB && preConditionC) {
    // happy path
  } else {
    std::err << "Error: Preconditions not met!" << std::endl;
  }

In the above examples, single entry/exit forces a structure like this:

  if (preConditionA) {
    if (preConditionB) {
      if (preConditionC) {
        // happy path
        ...
        ...
        ...
      } else {
        std::err << "User not authenticated!";
      }
    } else {
      std::err << "No server connection!";
      scheduleServerConnection();
    }
  } else {
    std::err << "No network connection!";
    scheduleConnectionCheck();
  }

Now, outside of "precondition" checking, it makes sense to use if/else or switch statements when conditions lead to similar happy path bodies. For example:

  if (shouldStand) {
    stand();
  } else {
    // No implied difference of statement body importance based on indentation
    sit();
  }

Versus:

  if (shouldStand) {
    stand();
    return;
  }
  // Hmm, is this path significantly different from the one above?
  sit();

So, in the "branching happy path" situation I opt for the former.

> Government-run healthcare is not socially optimal.

This needs justification, especially since socialized medicine works better in so many other countries.

He certainly doesn't know how to operate an espresso machine: https://www.youtube.com/watch?v=J3UQmKiVH9E

AZ and Hawaii experience ranges of [10-14 hours] and [11-13.5 hours] of daylight across the whole year, respectively. More southern latitudes can get away with not shifting their clocks because the daylight variance is much smaller. In AZ, sunrise varies from 5:15AM to 7:25AM. In Seattle, without DST, it would range from 4:11AM to 7:57AM. If we use "civil twilight" (bright enough for outdoor activities), Seattle would start experiencing daylight at 3:30AM in mid-summer.

"Amazon built the Fire stick to be compatible with Chromecast. Google then changed the Chromecast protocols repeatedly to prevent this."

I don't believe this is true. Do you have a source?

FYI: This article was likely published in summer 2020.

Did you accidentally reply to my comment? I didn't state any position on the issue, just offered a 3-sentence correction to someone else's comment.