A Few Answers To Questions You Always Wondered About

August 14, 2019 | No Comments » | Topics: Answers, Interesting

How Much of a Pilot’s Training Is Emergency Landing Practices?

You can teach anyone to fly straight and level in about 10 seconds. Push the wheel or stick forward, and the ground gets bigger. Pull the wheel or stick back, and the sky gets bigger. Turn or push right, you turn right; turn or push left, you turn left. Congrats, you can fly straight and level. It takes about 10 brain cells to do this, so you can do everything else while you fly straight and level.

Taking off is pretty easy, too. Just point the nose toward the end of the runway (far end!) and apply throttles. When it gets going fast enough to fly, it will, and you get to manage the climb out. Not too hard.

Navigation takes time. You need to fly far enough to get lost and then find where you are on the map. They make you do that so when the screen goes out, you can find your way back. All the other air work is mostly to make sure you don’t drop out of the sky if you screw up somehow.

Landings are where you spend the other 75 percent of your training time, first with power and the wind down the runway, then with a crosswind. When you can land it so smoothly nobody can tell (a “greaser”), you get to move to the hard stuff.

You’ll be flying around the circuit or pattern, and the instructor will calmly reach over and pull the throttle out to idle (go-fast is when the throttle is push full forward or “fire-walled”) and says, “Oh dear, the engine seems to have failed!” You declare a (simulated) emergency and land the plane. You do it from all sides of the field landing into the wind, across the wind, and with the wind (when you have completed everything else), and when you can do it without a sweat, you’ll begin to practice out in the training area.

Flying along at 3,000 feet, the instructor will again play with the throttle and leave you without power. You then have to find a place to land and get ready to do it. You’ll do it over and over again until you learn to fly with one part of your brain looking for a place to put it down if the engine stops, either because the nut-bar instructor beside you decides it’s time or because, well, the engine decides it’s time to stop working. You use the other 99 percent of your brain to keep watching and working on where to put it down safely. On your first trip over a large body of water, you begin to sweat a bit more, because you really want to keep it dry if the engine or engines start to sound funny. (And they always do that first time.)

Flying lessons are not so much about flying but about emergencies. You can’t “pull over” and deal with something on a cloud someplace. You need to be aware at all times of someplace to put the plane down if you really need to.

The only time I had an engine issue, I was flying over the city of Toronto, actually right over the downtown area, where there are no large places to land. Roads are no good—there are always wires crossing every road, and most parks are full of trees. Trees are pretty soft for the most part (they told us that in flight school), but it’s bad form to bash up the plane by putting a branch through the wing.

I was lucky in that it wasn’t a total loss of power, and I was close enough to three airports (not counting Pearson), and I had enough altitude to get to at least one of them at all times. The engine was having issues making full power, and it wasn’t carb ice, I had put the heater on, so getting down back at Buttonville was the best choice. I called them up, they cleared me straight in, and I landed it. Was I worried? Not really. I knew I could land it. I had practiced enough.

Funny story time: Once during training, the instructor idled the engine, and I began to look for a nice spot to land. It was farm country, so there were lots of places to put the plane. I found a nice corn field and had the plane down to about 100 feet ready to land it when the instructor let me add power again to go back up into the sky. As it happens, an airplane with the engine idling is pretty much silent. Well, as it would happen, at the left side of the corn field was a farm house with a garden and a woman bent over tending to her plants, with her back to me. I can see this out my side window. Again, I’m about 100 feet up and maybe 150 feet from her when the airplane becomes rather loud. She was very surprised, to say the least! The look on her face was priceless. I did wave, and she didn’t complain.

Stan Greenspan, licensed private pilot

 

What Are The Risks And Benefits Of Artificial Intelligence?

There’s a lot of misinformation about the risks and opportunities surrounding artificial intelligence (AI). It’s a complicated topic, but I’ll try to unpack a few key points here.

Let’s start with a quick definition: AI is the simulation of human intelligence by machines. Example of AI systems used regularly in developed countries include Amazon’s Alexa, smart replies in Gmail, Chatbots, predictive searches in Google, and recommendations. At a baseline level, AI helps improve our everyday lives by solving pain points, streamlining processes, and advancing human knowledge.

It’s understandable why many consumers find the idea of AI intimidating or unsettling – science fiction movies have been obsessed with robot takeovers for years and recent movies like I am Mother portray AI as contributing to a post-apocalyptic world. But the concern isn’t just from Hollywood writers obsessed with the fantastical, world-renowned minds like Stephen Hawking and Elon Musk have also rung the AI warning bell.

To be fair, they raise some important points. But instead of getting defensive, AI researchers should consider feedback and ask themselves: just because I can advance a particular technology, should I? This isn’t a knock on AI (we are AI researchers after all)–but rather a question scientists and researchers in every field should ask themselves when advancing technologies with unknown consequences (ping Google, Facebook). This is particularly true for AI more than other technologies because AI takes part in the decision making. It is easy to know who is responsible for pushing the red button sending missiles to an enemy; it is far more complex when the decision was made by an AI. Any system taking decisions based on data will propagate and amplify human biases. Anyone using AI cannot hide behind this fact and act as if data was a source of absolute truth, they need to take full responsibility for the decision made with their system.

We do think is worth keeping an eye on is AI’s impact on wealth inequalities. As with any advanced technology, AI has the power to increase the wealth gap between the rich and the poor, especially if monopolies are formed. Our vision of work is rooted in the fact that we need people to work to keep the society growing. But with technological progress, this is less and less true. Indeed “AI is taking over jobs,” because machines can do things that used to require humans. Many authors in science-fiction foresee a world where no one needs to work anymore, and all the basic needs are provided by fully autonomous systems. This future is sustainable only by deep restructuration of how wealth from autonomous systems is distributed. Researchers and politicians should continue exploring the feasibility of a universal basic income (UBI). Although considered radical by some, the idea behind UBI was first floated in the 1600s by Sir Thomas More and was even considered by President Richard Nixon.

Yes, there are some areas we need to keep an eye on, but remember, we’re still far from achieving what most consumers consider true AI – technology with consciousness. Instead, over the next few years, you’ll see more of the following AI advancements:

Smarter weather predictions and agriculture

Accurately predicting weather can be difficult, and errors have the potential to hurt businesses, disrupt travel, and endanger lives, especially for those who lack transportation or the ability to quickly seek shelter when needed. Thankfully, AI offers solutions by analyzing data and making future predictions. According to the American Meteorological Society, AI is a game-changer for improving real-time decision making with high-impact weather. This will allow us to predict more accurately natural disasters such as hurricanes, floods but even earthquakes and tsunamis. AI is also starting to be used toward more sustainable agriculture. By employing such software to optimize crops yield, we can reduce the space required without having to resort to damaging techniques like pesticides.

Energy optimization

From micro-architectures to heavy industries, the progress of AI had a significant impact in engineering. The challenges we face today are far more complex than they were a few years ago. Both tiny systems like smart devices and huge structures like buildings need to be more and more energy-efficient. These problems cannot be solved by only traditional engineering science. Today AI and data science help crunching numbers to design green buildings or green energy production for instance.

Self-driving cars everywhere

Sure, if you live in Silicon Valley you routinely come across self-driving cars, especially by the Googleplex. But for the majority of U.S. residents, self-driving driving cars not only seem out of reach, they also seem untrustworthy. According to a recent Reuters/Ipsos survey, half of U.S. residents believe driverless cars are more dangerous than cars driven by people, and nearly two-thirds of respondents said they would not buy a fully autonomous vehicle. This is a mindset that will quickly change, and there will be a tipping point over the next three to five years. As people interact more with cars that have driverless features (automatic breaks, evasive steering, and pre-safe nudging), there comfort level increase. It’s a matter of when, not if, driverless cars become mainstream and dominate American highways.

AI in healthcare

Recent years have witnessed striking advances in the ability of machines to understand and manipulate images, language, and speech, largely fueled by an explosion of research in a subfield of machine learning known as deep learning. Despite the prodigious amounts of machine-readable data generated in healthcare (150 exabytes or 1018 bytes in US alone growing 48% annually), including medical images, clinical notes, and sensor data, the field has been slow to fully benefit from advances in deep learning because the data are subject to important patient privacy laws and the algorithms are subject to regulatory oversight. As deep learning researchers, healthcare providers, and regulatory bodies continue to work together towards making data more accessible, deep learning will enhance the abilities of healthcare providers, resulting in more affordable, accessible, and personalized care.

On-demand language translation

The days of awkward hand pointing are about to be over. Tourists can now depend on sophisticated language translators while traveling internationally. In 2018, Microsoft unveiled neural machine translation (NMT), which provides high-quality translations for both the written word and text that appears in images, such as traffic signs or menus. This advancement will help increase communication, decrease petty misunderstandings, and contribute to a more open and cosmopolitan world where people have a deeper understanding and appreciation for others.

Emile Contal, Co-Founder of Crossing Minds,

 

 

Why Are Younger People More Creative Than Adults?

Children have a more active imagination than adults, and young adults are less constrained by their own prior patterns of thought.

As people become “good at life,” they develop habits of thought that serve them well. These habits are thought styles that “work” (get results, impress people, carry us through difficult situations). As we accumulate “thought techniques,” three things happen.

First, we become more effective and able to “effortlessly” (mindlessly?) navigate tricky waters.Second, we adapt to social norms and accepted ways of thinking, making us more effective with people and society.

Third, we become a prisoner of our own success. Sticking with what works makes us both more successful and less creative. Why be random when you can be right? Unfortunately what works is what worked in the past and misses the enigmatic paths that lead to unexpected surprises.

People who are in creative professions develop personal systems to stay creative. They develop predictable habits that take them into unpredictable territory. This is a lifestyle choice to stay in the uncomfortable territory of the unknown. They may seek out people outside their profession, read random things, or force themselves to brainstorm whimsically. This systemization of creativity doesn’t have the bizarre arc of childhood imagination, but does combine life experience with creativity in a way that can be more impactful (and higher paying) in modern society.

Paul King

 

 

What Do the Wealthiest People Know That Others Don’t?

That big money is served in small increments. Whether that’s return on investments, profits, margins on products you’re selling, whatever. People who don’t understand this are always trying to double or quintuple their money in as few transactions as possible, while the largest and most successful companies and people in the world win by making “small money” over and over again.

That wages and income are about what the job is worth, not the individual. As a person, as a human being, your value is immeasurable. If you went missing in the woods, our society would easily spend five or six figures trying to find and rescue you, without hesitation. But dude, putting a sticker on a box is still only worth $5, if that. Your income potential isn’t about what you need or what the employer can afford; it’s about the value of what you do. Those who are in the upper income brackets have understood and embraced this reality and have worked to bring something of value to the market or their company.

That personal debt is not a “tool.” It’s shackles—delayed gratification is more gratifying than instant gratification. If you can’t pay cash, you can’t afford it. That guy you know making $70,000 per year driving an $80,000 BMW and carrying $15,000 in credit card debt looks like he’s well-off, but he’s an idiot. His entire paycheck is gone by the end of the month, and none of that stuff is his. He’s basically just renting it from the bank. He’s paying more annually in interest than he’s earning in his IRA. One hiccup in his income and the bank takes it all back, making all the money he’s paid thus far for nothing. But the guy who saved up and paid cash? His savings account grows every month and no one will ever show up and take his stuff.

The value of the dollars you have versus unearned future dollars. Those people who got a “great deal” on Ikea furniture or faux leather couches will be buying another one sooner than the person who bought quality goods. And the thing is that the people who cheap out know that when they buy it. They rationalize it by saying, “If I get three years out of it, that’s fine, I can buy a better one later when I can afford it.” When you do this, you’re basically deciding to throw away the money you have and committing future dollars you haven’t even earned yet. A smarter decision: save a little longer and spring for quality goods that don’t need to be replaced so quickly.

Math. The broke person really wanted a particular item but it was more than $100, and he or she didn’t have it. When the item went on sale for 20 percent off, he or she rushed to one of those payday advance places and borrowed the money to get it. The interest on those type of loans of course negated the savings. But the person didn’t care and justified it by thinking, “Oh well, it’s the same money anyway.” He didn’t realize that the problem wasn’t how he bought the item.

The importance of life insurance. I won’t get into the personal responsibility argument about leaving your loved ones to fend for themselves. The point is that life insurance is hands-down the easiest and lowest-impact way to pass wealth on to the next generation. For a few measly dollars a month, your kids can be millionaires (or at least hundred thousand-aires). Even people who will never make enough money in their lifetimes to buy homes and die broke and penniless could leave enough to get all of their grandkids through medical school. It’s a total no-brainer, and you can afford it. If you’re retired, your adult children should be paying the bill for you. Stop making excuses.

That lotteries are just another tax on the poor. You do realize the government keeps half of it, right? That’s before the winner is taxed. Yep, that $7 million jackpot really represents $14 million in actual lottery ticket sales, so you’re basically just voluntarily paying more taxes. You won’t see the 10 percent standing in line buying lottery tickets. Even during the big jackpots. Your odds of winning are 1 in 292 million, yet there are people who drop $20 per week, every week for 40 years or more hoping one day it will be their turn. That same money invested from ages 20 to 60 would be worth $300,000 on their 60th birthday, even with the most conservative market estimates. Or another way to look at it: you could turn $40,000 into $300,000 simply by not playing the lottery. It’s dumb. Stop doing it.

Above all, if you can commit to living within your means, your means will increase over time. Feeling broke today? Look at your paycheck. Now imagine you didn’t have to spend all of that on car payments and a house that’s bigger than what you need, and the credit card payments on all the stuff you bought to fill it. Just imagine that whole paycheck staying in your bank account and not going out the door to those payments. You aren’t so bad off anymore, are you?

Now imagine what your savings account would look like in just one year if you threw it all there and forgot about it. Because that’s where you could be if you thought about money differently.

Successful people know it’s not about how much you make; it’s about how you spend it.

Ron Rule, CEO of As Seen on TV

 



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