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5 Rules of Thumb and Their Inventors

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It is a popular custom among learned society to toss around the names of theories without explanation or elaboration-- Murphy's Law, Occam's Razor, and so on. But who were Murphy and Occam, and who are they to come up with these life-governing rules? Below are five well-known rules and laws, and the stories behind their namesakes.

1. Occam's Razor

Occam's razor is known more formally as the law of parsimony or the law of economy, and states that "entities should not be multiplied unneccesarily." Put simply, it is the notion that the simplest explanation is usually the right one. It is named after William of Occam, who was a scholastic philosopher and Franciscan friar that lived in England in the 14th century. His contemporaries were the likes of Thomas Aquinas and the Islamic scholar Averroes. William was the first to write down the principle in its formal wording, and it gained his name due to its frequent usage in medieval philosophy. William was also one of the first to argue that people should not attempt to derive the idea of God from reason or natural logic.

2. Moore's Law

Picture 1Moore's Law is not actually a law, but instead an observation made in 1965 regarding transistors-- specifically, that the number of transistors that can be placed inexpensively in an integrated circuit doubles about every two years. The observation was made by Gordon E. Moore, a graduate of UC-Berkeley and Caltech, in an article in the now-defunct Electronics Magazine. Three years after this observation, Moore co-founded Intel Corporation and served in various positions before becoming its chairman and CEO in 1979, and retiring to a chairman emeritus position in 1997. Nowadays, chip manufacturers treat Moore's Law as a professional challenge, struggling to keep the pace by constantly inventing new ways to squeeze more transistors onto chip surfaces.

3. Murphy's Law

murphyMurphy's Law is also less of a law and more of an old saying: "anything that can go wrong, will go wrong." It is named after Edward Murphy, who was an American aerospace engineer who, funnily enough, worked primarily on safety-critical systems. Most of his efforts went into developing escape systems for experimental aircrafts, such a the F-4 Phantom II and the SR-71 Blackbird. Murphy thought that people in his profession should always consider the worst-case scenario, and so he often cited his old adage as a central tenet of defensive design. However, his efforts to have the law taken seriously were unsuccessful. There also exists a "corollary" to Murphy's Law, called Finagle's Law of Dynamic Negatives, which states "anything that can go wrong, will, at the worst possible moment."

4. Pareto Principle

Vilfredo_ParetoThe Pareto Principle, also known as the "80-20 rule," is the observation that for many events and sets of data, 80% of the effects come from 20% of the causes. It is named after Vilfredo Pareto, an Italian economist who lived and worked around the turn of the 20th century. In 1906, he noted in his research that 20 percent of the population in Italy owned 80 percent of the the land. He extrapolated this relationship to the general distribution of wealth, noting in a book published in 1909 that this proportion applied roughly across time and location. It wasn't until much later that the rule was named after Pareto, by business management consultant Joseph Juran. The rule is now applied very widely, not just to wealth but to quality assurance-- Microsoft has noted that fixing the most-reported 20% of bugs fixes 80% of errors and crashes-- and time management by gurus like Tim Ferriss, author of The 4-Hour Workweek, who encourages people to focus their energies on the 20% of activities that generate 80% of the results. Would-be applicants should use the rule with caution, though-- it is meant to illustrate a general majority-minority relationship, and is not a hard-and-fast law applicable to all cases.

5. Parkinson's Law

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Parkinson's Law states, "work expands so as to fill the time available for its completion." Despite the fact that it is quoted quite soberly today among efficiency experts, Parkinson's Law began as a joke. It was the first sentence of a satire piece published in 1955 in The Economist by Cyril Northcote Parkinson. Parkinson was no economist or scientist, but rather a naval historian and professor, first in Liverpool and then in Singapore. After the success of the article, Parkinson expanded upon his piece in a book called Parkinson's Law. Though the book was only a hundred pages long, it became an instant best seller in the United States.

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iStock // Ekaterina Minaeva
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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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Nick Briggs/Comic Relief
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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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