I think it's interesting to see an article like this every couple of weeks. The way I view it is that we're watching the five stages of grief (with regard to the "death of the office") play out in real time, at population scale.
At first it was denial - "everyone will be back in the office eventually!"
Then it was anger - "you will RTO or you will lose your job!"
Now it seems like we've finally hit bargaining - "you'll come in 3 days per week, wait, 2 days, wait, special exception for the last week of every month".
I wonder how long it goes on until we get to depression and acceptance?
This would require spacetime to be quantized (presumably at the Planck length or something smaller) though, yes?
I've always thought entanglement makes more intuitive sense on a graph substrate of some kind, where the "spooky action at a distance" is actually just an anomalous edge in the graph connecting two vertices which would otherwise be more distantly separated. This begs the question of how the edges in the graph came to be or whether they're modifiable at all though.
Different generations have different investment preferences, so the best hedges are going to be things Millennials want that Boomers do not typically own.
Baby boomer mass retirement. This will increase the selling of shares across the board, since boomers will need to liquidate their assets to finance their living expenses when they are no longer taking salaries.
"Passive investing" is a largely beaten-to-death turn of phrase because you can't truly be a passive investor in anything. Every "passive investing" focused fund has some degree of selection bias, because the index itself is arbitrarily declaring that it's only buying the "top 500" or whathaveyou. So you're "passively" investing in the top 500 companies, which means "actively" choosing not to invest in the rest.
You can go one level up from there and buy VTSAX if you want to buy everything and truly "passively" invest in US stocks, but again, you'd be "actively" choosing not to invest in international stocks then.
TL;DR for folks is that they left a lot of debug information in the build. The C code was compiled with no optimizations (and included debugging symbols), and GOAL uses a string-based table for global functions/variables/types, so they're starting with all those for free. Plus they don't think the GOAL compiler did too much tricky-to-undo optimization either.
I like the notion of breaking job satisfaction into "motivators" and "hygiene factors" (Herzberg's motivation-hygiene theory [1]).
Motivators actively cause job satisfaction. Things like finding personal fulfillment, meaningful work, and other top-of-Maslow's-hierarchy stuff.
Hygiene factors cause dissatisfaction in their absence, but aren't standalone motivators. Salary probably fits in this bucket - if you learn that you're underpaid, you're likely to feel demotivated and look for work elsewhere. If you learn that you're overpaid, that can cause dissatisfaction too (feeling like you have to serve out the rest of a prison sentence until your shares/options vest is pretty common in our industry).
Compensation isn't everything, but if it seems unfair, it's absolutely enough to motivate people to make changes. I think we're seeing a reevaluation of labor market expectations with the whole Great Resignation thing, where those who are in demand are realizing just how demanded their skills are (and getting pissed off that they're undercompensated in their $current_job), and the old generation you speak of is trotting forward with their fingers in their ears, blinded by normalcy bias to the fundamental shift happening in front of them - a big labor market awakening.
If your "shields" went down because you had a negative workplace experience, but then you found out that you could double your salary once you started looking, I think it's totally fair to consider both the toxic culture and the compensation your "why" factors.
It's easy to use something like compensation or new challenges as a post-hoc rationalization for making a move too, even when the real reason you started looking is perhaps different and requires some introspection. As an example, you might not start looking because you want more money, but it's fairly socially acceptable to say "I left because I was made an offer I can't refuse" as a justification when you do actually leave.
This depends on broader society accepting that COVID is endemic though, and the cessation of all sorts of regulations. I don't doubt it will happen eventually, but I'm not sure if another year is enough time. There has to be some sort of common knowledge catalyst that changes the general approach; as long as events are still being cancelled due to COVID cases, we're not out of the woods and "living with the disease" quite yet.
Additionally, I think "undoing" the remote workforce transition is going to be nigh impossible for many companies. How do you get your employees back to the office? You probably tell them their employment is contingent on being in the office; that's the only leverage you really have as an employer. Many people have moved since the onset of the pandemic, and with the labor market as tight as it is, few companies are going to be able to stomach laying off employees who moved away and don't want to move somewhere near a physical office location.
So companies have a Hobson's choice: declare an "on-site" culture and axe all the people who no longer wish to be on-site (with no guarantee that you'll be able to hire replacements in a timely manner), or declare a "hybrid" culture and allow people to opt into coming into the office instead of having it mandated (with no guarantee that people will actually show up to the office and make your real estate expenses worthwhile).
I think a lot of companies are going to choose option #2 now, and a lot of those who choose #2 are going to reevaluate that gargantuan office lease expense in a few years' time when comparing the cost with the actual utilization of the space. I think a not-insignificant portion of the option #2 companies will end up being "full remote" companies as a result, it'll just take them a few years to get there. I think the option #1 companies will probably be fine if they're in cities where there's enough talent, but their long-term success is kind of a toss-up in my opinion. It truly depends on whether the social benefits of in-person interaction gives them a competitive advantage versus world-spanning remote companies who can be more selective with their talent.
Judging by the historic job changing trends in the last few months, I think your suggestion that "through quitting everyone reorganizes themselves" is already happening.
The only question that remains to be answered is whether remote or in-office companies have structural advantages over the other type, and it will probably take a decade or so before there's enough data to conclusively call it.
Fees and chargebacks are the ones that usually come to mind. Oftentimes major credit card provider networks set a "minimum" interchange fee to disincentivize small transactions (a chargeback on a ten-cent transaction is often not worth the squeeze from a support/processing perspective).
Basically all major payment networks are facilitated by a middleman of some sort, and that middleman entity usually has operational costs that disincentivize them from offering micropayments.
Your point about a "balance" lands though - nothing stops NYT from making one "big" charge and then deducting from it other than consumer psychology (paying $10 up front can feel different than paying $0.05 at a time, for example).
Lightning network theoretically makes micropayments possible, and that should be celebrated for enabling new ways of online monetization that the tech world writ large can explore.
Imagine if you could buy access to a paywalled news article for $0.02 (on an article-by-article basis) instead of having to purchase a monthly subscription. Or imagine being able to pay $0.10 to watch a particular episode of a show without needing to subscribe to the streaming service. How many people would prefer doing that instead of using current SaaS subscription models (which exist largely because it's a huge hassle to implement credit card-based micropayments)?
Subscription businesses should be on guard: micropayments open up advertising-independent ways for creators to monetize content. With all the well-deserved criticism of ad-based businesses in recent years (particularly social media), it's possible that micropayments enable business models that don't rely on ads the way many online businesses have up to this point. That's huge, and kudos to Twitter for taking the leap.
In my opinion, a lot of these problems are organizational in nature as the tech industry wrestles with how to integrate data science into product development.
Too often there are siloed "data science teams" who do the best they can to field asks from tons of different business areas. Within those teams there are handoffs to labeling teams run offshore in MTurk style, handoffs to data engineers to build ETL to feed the modeling efforts, and then when models are finally trained there's a handoff to machine learning engineers to implement them!
Clearly data scientists need to be better integrated into product development flows, and not treated like a strange specialized black box.
Richard Bartle is a luminary in the field of game design. He invented a system for classifying gamers' preferred game actions called the "Bartle taxonomy", which helps game designers understand player motivations better. Think of it like user personas in software development - Killers love competition, Explorers love discovery, Achievers love mastery, and Socializers play games for social reasons. When designing a game for mass appeal it's often important to make sure players of all stripes find reasons to enjoy it, and Bartle's taxonomy is a great framework for analyzing how different types of players will interact with a game.
You can take an online version of the Bartle taxonomy questionnaire to get your own results here:
I think people are so accustomed to having to trust each other that the notion of something being "trustless" is really foreign.
If you tried to live a trustless life, you couldn't get surgery, ride on a plane, get food from a grocery store, etc. - all of those things rely on implicit trust in other human beings. The whole of human society was built on trust!
I think the premise here is that there is some sort of physical limitation that causes cyanobacteria to have a maximum "carrying capacity" of oxygen, and stretching timecycles causes that threshold to be exceeded, leading to oxygen leaks.
Analogously, think of memory management in a computing context. You have a program running that gradually allocates memory linearly over a certain time period (daytime), but then releases all that memory linearly during another time period (nighttime). Say you're dealing with 4GB of memory and you run the memory-increasing part for 6 hours, then run the memory-decreasing part for the next 6 hours, and so on. Suppose you never allocate the full available 4GB when you're dealing with a 6 hour on/off timecycle (the rate of memory allocation is too low to get to 4GB in 6 hours) - but what happens if you extend the timecycle? There's some timecycle length at which you will finally attempt to allocate more memory than the 4GB your hardware is capable of, so the host OS starts swapping or writing stuff to disk to deal with the excess.
Biological systems don't have a "host OS" that regulates their molecular byproduct management though. Extra atoms/molecules are just going to escape into the surrounding environment. Perhaps the oxygen buildup during the daytime might have worked this way with the cyanobacteria - longer days led to more oxygen being produced than could be physically retained in the immediate vicinity of the cyanobacteria (some type of saturation effect), so all the oxygen in excess of the saturation threshold effectively "escaped" and became unavailable for metabolic "re-consumption" at nighttime. Thinking about the longer nights that accompany the longer days, there's probably a period of time in these longer nights during which all the "nearby" oxygen has been fully consumed, and the cyanobacteria more or less sit idle.
Oxygen saturation in the surrounding environment seems like the missing logical piece from this popsci article.