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In my experience, there’s quite a disparity. We want people that are productive, passionate and enthusiastic. But we send out coding challenges, play 20 questions and draw a B-tree on a whiteboard.
Let’s look at some of these techniques in detail…

Source: How to hire the best developers – Hacker Noon

Having a place to go and people to see outside of school offers a reminder that they needn’t always feel that way. “What I find profoundly empowering about addressing loneliness is that the ultimate solution to loneliness lies in each of us,” Murthy says. “We can be the medicine that each other needs.”

Giving young people a room of their own, and something to do in it, is a good way to get that started.

Source: The Danish have designed a simple way to cope with loneliness — Quartz

Building a team is more complicated than collecting talent¹. I once tried to solve a problem by putting a bunch of PhDs’ in a room. While comments like that sounded good and got me a lot of projects above my level, they were rarely effective at delivering actual results.
Statements like “let’s assemble a multidisciplinary team of incredible people” are gold in meetings if you work for an organization. These statements sound intelligent. They are hard to argue with. And, most importantly, they also have no accountability built in, and they are easy to wiggle out of. If things don’t work out, who can fault a plan that meant putting smart people in a room.
Well … I can. It’s a stupid plan.
The combination of individual intelligence does not make for group intelligence. Thinking about this in the context of the Jobs quote above, “A” players provide a lot more than raw intellectual horsepower. Among other things, they also bring drive, integrity, and an ability to make others better.  “A” players want to work with other “A” players. Accepting that statement doesn’t mean they’re all “the best”.
In my experience solving difficult problems, the best talent available rarely led to the best solutions. You needed the best team. And the best team meant you had to exercise judgment and think about the problem. While there was often one individual with the idea that ultimately solved the problem, it wouldn’t have happened without the team.  The ideas others spark in us are more than we can spark in ourselves.

Source: The Importance of Working With “A” Players

I have been a pilot for 30 years, a software developer for more than 40. I have written extensively about both aviation and software engineering. Now it’s time for me to write about both together.
The Boeing 737 Max has been in the news because of two crashes, practically back to back and involving brand new airplanes. In an industry that relies more than anything on the appearance of total control, total safety, these two crashes pose as close to an existential risk as you can get. Though airliner passenger death rates have fallen over the decades, that achievement is no reason for complacency.
The 737 first appeared in 1967, when I was 3 years old. Back then it was a smallish aircraft with smallish engines and relatively simple systems. Airlines (especially Southwest) loved it because of its simplicity, reliability, and flexibility. Not to mention the fact that it could be flown by a two-person cockpit crew—as opposed to the three or four of previous airliners—which made it a significant cost saver. Over the years, market and technological forces pushed the 737 into ever-larger versions with increasing electronic and mechanical complexity. This is not, by any means, unique to the 737. Airliners constitute enormous capital investments both for the industries that make them and the customers who buy them, and they all go through a similar growth process.

Source: How the Boeing 737 Max Disaster Looks to a Software Developer – IEEE Spectrum

Not only was Darwin thinking broadly, taking in facts at all turns and on many subjects, but he was thinking carefully, This is where Munger’s admiration comes in: Darwin wanted to look at the exceptions. The exceptions to the exceptions. He was on the hunt for truth and not necessarily to confirm some highly-loved idea. Simply put, he didn’t want to be wrong about the nature of reality. To get the theory whole and correct would take lots of detail and time, as we will see.

Source: How Darwin Thought: The Golden Rule of Thinking

And here, faced with crying, I found that the data was helpful. We often say babies are “colicky,” but researchers have an actual definition of colic (three hours of crying, more than three days a week, for more than three weeks) and some estimates of what share of babies fit this description (about 2 percent). But the same data can also tell us that many babies cry just a bit less than that, and almost 20 percent of parents report their baby “cries a lot.” So I was not alone. The data also told me the crying would get better, which it eventually did.

But I also found, more so than in pregnancy, that there are limits to the utility of general information. Parenting is full of decisions, nearly all of which can be agonized over. You can and should learn about the risks and benefits of your parenting choices, but in the end you have to also think about your family preferences — about what works for you.

Source: Opinion | The Data All Guilt-Ridden Parents Need – The New York Times

How does a relational database execute SQL statements and prepared statements (Last Updated On: April 2, 2019) Follow @vlad_mihalcea
Introduction
In this article, we are going to see how a relational database executes SQL statements and prepared statements.
 
SQL statement lifecycle
The main database modules responsible for processing a SQL statement are: the Parser, the

Source: How does a relational database execute SQL statements and prepared statements – Vlad Mihalcea

Certainly, Autopilot remains one of the most controversial elements of Tesla’s cars. The system combines features like adaptive cruise control, lane-keeping, and auto lane-change, and is intended to assist drivers on highways.
Though those features are available on other cars from rival automakers, Tesla’s bullish claims about how capable Autopilot is have prompted criticism from some. Although the official guidance is that drivers are still entirely responsible for the operation of their car, that hasn’t stopped some Tesla owners from performing stunts like napping behind the wheel or even leaving the driver’s seat altogether. Meanwhile a number of high-profile crashes where Autopilot was active has also raised eyebrows.
Tesla, though, insists that Autopilot makes for safer driving, and it says it has the statistics to back that assertion up. “In the 1st quarter, we registered one accident for every 2.87 million miles driven in which drivers had Autopilot engaged,” the automaker said today. “For those driving without Autopilot, we registered one accident for every 1.76 million miles driven. By comparison, NHTSA’s most recent data shows that in the United States there is an automobile crash every 436,000 miles.”

Source: Tesla just revealed its first Autopilot accident rate for 2019 – SlashGear

For over 30 years, Seven-Eleven Japan was the most profitable retailer in Japan. It achieved that stature by relying on each store’s salesclerks to decide what items to stock on that store’s shelves. Many of the salesclerks were part-time, but they were each responsible for maximizing turnover for one part of the store’s inventory, and they received detailed reports so they could monitor their own performance.
The language of hypothesis formulation was part of their process. Each week, Seven-Eleven Japan counselors visited the stores and asked salesclerks three questions:

• What did you hypothesize this week? (That is, what did you order?)
• How did you do? (That is, did you sell what you ordered?)
• How will you do better next week? (That is, how will you incorporate the learning?)

Source: Why Hypotheses Beat Goals

In one study from 2006, psychological researcher Shelly Gable and her colleagues brought young adult couples into the lab to discuss recent positive events from their lives. They psychologists wanted to know how partners would respond to each other’s good news. They found that, in general, couples responded to each other’s good news in four different ways that they called: passive destructive, active destructive, passive constructive, and active constructive.

Source: Masters of Love – The Atlantic – Pocket