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Mangesh Hattikudur on Working With Young John Green

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So, the strange thing about the first time I met John Green—at a Birmingham house party in 2002—is that at the time, I was kind of a bigger deal than he was. Which is not to say that I am, or ever have been, a “big deal.” (For clarification: I’m not/haven’t ever been.) It’s just that, well, that should put things in perspective.

In 2002, John Green was this guy working for Booklist, who said he was going to write a book. I’ve met a lot of people who say they’re going to write a book, and more often than not, they don’t. Meanwhile, I’d lucked into starting a magazine with my college friends. A very small magazine, called mental_floss, that at that time maybe 400 people subscribed to (from what we could tell, the demographic was my mom, the other co-founders’ moms, and 396 of our moms’ friends).

But in the last few months our magazine had gotten some national press. Publishers were talking to us about book deals. We were starting to bring more talent on board, including our editor Neely Harris. And we’d just set up shop in our first real workspace—a former dentist’s office that had free Muzak as one of its perks. (Thinking about it now, I’m not sure the Muzak was supposed to be a perk; I think the previous tenants just forgot to stop the service.)

That night, I was at Neely’s house party, doing a terrible job of trying to mingle, when she pulled me over to meet this high school friend of hers who she warned was weird, but also hilarious and kind of a genius. And then I got the John Green experience. As he fumbled to take out a few pieces of nicotine gum—which I learned that night are maddeningly hard to free from the plastic—John proceeded to keep me captivated. He told me how Booklist had taught him to read quickly, and how he was fast becoming an expert on reviewing books about conjoined twins. He told me he wanted to write young adult books, a genre I’d never heard of, and when I excitedly asked if he meant like Roald Dahl, he politely responded no. He told me about the hippie boarding school he, and Neely, and all these other talented young people like Daniel Alarcon had gone to—where kids could take classes like “Drawing to Music,” and where instead of detentions, a student committee doled out gardening duties as punishment. He told me a hilariously inappropriate story that later ended up in his book Looking for Alaska, which I wasn’t sure was true or not, but I loved hearing anyway. He told me about being a divinity school drop-out (and then he listed other famous drop-outs, like Casanova and Michael Moore). When someone’s cell phone started ringing, he let me know it was probably his because it was a Super Mario Bros. ringtone. And he told me his philosophy on lying—that sometimes he liked to lie a little, just to keep his storytelling skills sharp.

I liked him immediately. The John Green of that night wasn’t the YA rockstar/internet phenom everyone knows now. The 2014 model is more confident, not a Nicorette chewer, a better speaker, and more likely to beat me in a footrace, among other things. But he was basically the same guy you see today—a whip-smart storyteller who couldn’t have been funnier or nicer. Neely suggested that with John’s interest in religious studies, we should ask him to write the cover story for our next issue, Saints and Sinners, which he did. And once I read his writing, I just kept booking him for projects.

Over the next few years, he continued to dazzle us. He helped me write and brainstorm the magazine’s front of book and cover stories. He pulled incredibly talented people into the fold, including Ransom Riggs and Hank Green. When Harper Collins asked us to churn out four mental_floss books in a single year, he hit every deadline. He sat in a room, with a box of Cheez-Its, and he knocked the books out. At the time, he was also writing An Abundance of Katherines, which made the feat even more impressive.

In those years, I edited John’s work for mental_floss. And while we discussed business on phone calls and admired each other’s terrible jokes, we rarely met in person. But he’s always been encouraging. Once, when I was going through a rough patch, he reminded me how good we have it. The words aren’t quite right, but he said something like, “We’re lucky. People actually take time out of their days to write us and tell us that we made their favorite something. Their favorite book. Their favorite magazine. What other line of work do you get that sort of affirmation?” It might sound vain, or corny, but it’s true. I’ve been incredibly lucky—to stumble into a job I love; to have found a fanbase that gives us so much support; to get to keep learning for a living. And of course, one of the best parts of my job is all the talented people I get to work with. From the beginning, we all expected John’s star to rise. We just knew it would happen. And when it did, we couldn’t help but root for his success. But when he was working here, teaching us how to write better and inspiring us to think bigger, it was also just nice to be in the same orbit.

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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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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iStock
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Why Your iPhone Doesn't Always Show You the 'Decline Call' Button
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iStock

When you get an incoming call to your iPhone, the options that light up your screen aren't always the same. Sometimes you have the option to decline a call, and sometimes you only see a slider that allows you to answer, without an option to send the caller straight to voicemail. Why the difference?

A while back, Business Insider tracked down the answer to this conundrum of modern communication, and the answer turns out to be fairly simple.

If you get a call while your phone is locked, you’ll see the "slide to answer" button. In order to decline the call, you have to double-tap the power button on the top of the phone.

If your phone is unlocked, however, the screen that appears during an incoming call is different. You’ll see the two buttons, "accept" or "decline."

Either way, you get the options to set a reminder to call that person back or to immediately send them a text message. ("Dad, stop calling me at work, it’s 9 a.m.!")

[h/t Business Insider]

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