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"My phone keeps dropping calls. What can I do?"

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DEAR A.J.,
My cell phone keeps dropping calls in midtown New York. This isn’t Siberia; it’s the heart of a major metropolis. I’ve switched devices and providers with no improvement. What can I do?
—NEAL IN NEW YORK

That sounds awful, Neal. Maybe you should consider trading your faulty cell for a classic: the first mobile phone, which Bell Labs introduced in 1946. This sleek device weighed a mere 80 pounds (the equivalent of 300 iPhones or one baby giraffe), looked like a fridge, and required an operator to place calls. Or you may prefer the 1965 mobile phone, which tipped the scales at a svelte 40 pounds. And talk about convenient! If you were one of the 2,000 New Yorkers sharing the system’s three channels, you had to wait only 30 minutes for an open line.

Of course, our fore-callers could always resort to landlines, though those had their own challenges, like a total lack of privacy. In 1950, 70 percent of American callers shared “party lines” with eavesdropping neighbors. And even politicians weren’t immune to this nuisance. During the 1960 presidential race, candidate Hubert Humphrey hosted a TV call-in show, only to be interrupted by an impatient neighbor demanding Humphrey hang up and free the line. The ever-polite Humphrey followed orders!

Then there was the excruciatingly slow rotary dial. You could almost write a letter in the time it took to dial a friend. The higher the number, the slower the rotation, which is why the phone company gave low-numbered area codes to the biggest cities (e.g., 212 for New York, 213 for Los Angeles). Given that consideration, it’s still unclear why England chose 9-9-9 as its first emergency number. Perhaps it’s that famous British dry wit? But even the rotary dial was better than the alternative: Rural callers had to hand crank a generator to alert the operator they wanted to place a call.

The biggest improvement over the years has to be sound quality. When Thomas Watson was testing early phones, he had to shout so loudly that his landlady threatened to evict him. Since engineering is very tough if you’re homeless, Watson rolled himself in a blanket to muffle the noise.

Anyway, just think of all the time you’re saving by not searching for change for pay phones. Back in the day, even the rich had to dig for nickels! Miserly billionaire J. Paul Getty installed a pay phone in his mansion so he didn’t have to foot the bill for his guests’ calls. We’re guessing he wouldn’t be springing for unlimited minutes either.

Got a Modern Problem for A.J.? Email it to letters@mentalfloss.com, or leave a comment below. If he responds to your problem in the magazine or here on the site, we'll send you a free mental_floss t-shirt.

This story originally appeared in mental_floss magazine. Subscribe to our print edition here, and our iPad edition here.

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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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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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