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6 Habits of Rich People That You Should Steal

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Some people are wealthy thanks to their inheritance or a stroke of luck on a winning lottery ticket. But the rest? They’re doing little things every day that you may not be doing, even if you think you’re doing everything right.

Sometimes, the things that are making the rich richer may seem like they’ve got nothing to do with money (what does going to the gym have to do with your bank account?). The good news is that we’ve narrowed down their little tricks and secrets so you can take their habits straight to the bank.

1. THEY HAVE MULTIPLE JOBS.

It may seem scatterbrained to juggle a main job and a few other things at the same time, but this is a money-making strategy that’s bringing in big bucks, says Tom Corley, author of Change your Habits, Change Your Life, who spent five years studying the habits of wealthy people. “Sixty-six percent of the wealthy in my study started out either poor or in the middle class,” Corley says. “One of the strategies they used to build their wealth was creating multiple streams of income.”

Nearly all of the self-made millionaires in Corley’s study began their careers working for someone else, and on the side, they had a second business doing something they liked doing. But most didn’t stop at two sources of income: Corley says that 65 percent of the wealthy people had at least three gigs at once.

2. THEY GET TO THE GYM.

You let your gym membership lag because you simply don’t have time for it. After all, isn’t an extra hour at the office going to do more for your bank account than that hour at the gym? Turns out, it isn’t. According to a recent study reported by Psychology Todayphysically active men made 14 to 17 percent more money than less active men. 

3. THEY DON'T SPEND THEIR MONEY.

Have you ever gotten a tax refund and then immediately spent the day shopping for lavish outfits followed by an expensive night out? Chances are, a rich person would have put his refund into his savings account, and then continued on about his day. That’s because they use very strict budgeting tactics to accumulate their wealth, Corley says: 25 percent or less of their monthly net income is spent on housing, 15 percent on food, 10 percent on entertainment (including bars, movies and restaurants), 5 percent on auto loans (they never lease), and 5 percent on vacations. 

4. THEY VISUALIZE THEIR GOALS.

Wealthy people have a vision of where they want to be in life, and they write down this vision in the past tense, as if they’ve already achieved it, says John Ganotis, founder of Credit Card Insider, a consumer education company. Next, they make a habit of reading this visualization the first thing in the morning.

“The idea is to embed this into your sub-conscious to help guide decisions throughout the day, and identify opportunities to move the vision closer to reality,” he says. For example, you may subconsciously think about this vision when you’re asked to go out for a few beers, and you may turn down those beers when you realize that you should really be going home to learn how to code your app to move closer toward your vision, Ganotis says.

5. THEY INVEST. 

A survey by the U.S. Bureau of Labor Statistics found that the upper 20 percent of the wealthy spend about 16 percent of their income on pensions and insurance—and that’s more than six times as much as those in the lower 20 percent spend, Corley says.

But you’re barely scraping by, so you shouldn’t be investing and paying for insurance at the moment, right? Wrong, says Eric Neumann, wealth management advisor with Northwestern Mutual. “Insurance and pensions are needed for everybody, no matter the income,” he says. He says that even those in the bottom 20 percent of the income bracket should be putting aside 15 percent of their income toward pension and insurance, and his general rule of thumb is to save 20 percent of your paycheck.

Neumann says that most people are able to do this by prioritizing their needs over their wants. “Although they will be more dependent on social security in the future, they also need to offset with their own retirement plan, as the social security is increasing for retirement, and is projected to increase again in the future,” Neumann says. “Also, insurance is costing [the middle income] group a higher percentage of their income versus the top 20 percent group, as most insurance plans are not cheaper for the lower income group.” 

6. THEY FAIL.

Twenty-seven percent of the rich people in Corley’s study failed in business at least once in life. “Then, they got back up on their horse and tried again. And that persistence, that never quit attitude, enabled them to learn from their mistakes and failure, and ultimately succeed in life,” he says. 

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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]

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