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How Modern Family Almost Saved Osama bin Laden

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On May 1, 2011, President Obama spoke at the White House Correspondents’ Dinner. His poker face onstage hid a very big secret—the biggest he’d ever known. At most, a half-dozen guests knew what the president did: that seventy-nine members of three U.S. Joint Special Operations Command task forces were in the final stages of preparation for a raid in the picturesque town of Abbottabad, Pakistan. The commandos would be storming a compound that housed a man called “the Pacer” by the National Geospatial-Intelligence Agency. (Other intelligence analysts called him “Cakebread.” Some SEALs informally called the man “Bert.” As the mission’s target, he was designated “Jackpot,” though he was officially codenamed “Crankshaft.”) The target, of course, was Osama bin Laden.

That no one at the dinner leaked the secret is remarkable for several reasons. In Washington, carefully leveraged secrets can elevate one’s status in social circles. A year before, by way of WikiLeaks, the government sustained the most substantial loss of secrets in American history. And the whole purpose of the Correspondents’ Dinner is for journalists to ferret confidential information out of their dinner guests. (A few of the more egotistical journalists brought celebrities. The smarter ones invited people with security clearances.)

But there was a close call that night concerning the raid. William Daley, the White House chief of staff, was a guest of ABC News, as was actor Eric Stonestreet, who won an Emmy for his starring role as Cameron Tucker on the television comedy Modern Family. Stonestreet had apparently arranged for a tour of the White House that next day but was suddenly told that it was canceled. Over salad, Stonestreet turned to Daley and asked, “So I was wondering. Was there any reason they canceled my tour?”

George Stephanopoulos’s head swung around, and he caught Daley’s eye. “You got anything going on there, Bill?” Stephanopoulos asked. A veteran of the Clinton administration, Stephanopoulos knows how the White House works.

Daley began to sweat, by his own recollection, and blurted out an excuse. “It’s something to do with the plumbing.” He added, “You know what, Eric? Stop by Monday and I will personally give you the tour myself.”

That answer satisfied Stonestreet, and more importantly, Stephanopoulos, who returned to his original conversation. Had a journalist at the dinner pried a little harder and made a few calls, the secret might well have leaked, and front pages the next morning would have told a very different story.

Adapted from Deep State: Inside the Government Secrecy Industry, by Marc Ambinder and D.B. Grady.

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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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Name the Author Based on the Character
May 23, 2017
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