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Children Can Tell the Difference Between Abstract Art and Kids' Paintings

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Some might argue that a Jackson Pollock painting looks like something a preschool kid could do, given a canvas and some paint. But abstract art is definitely distinct from the random splatters of a child, a new study finds. In research published in the Journal of Cognition and Development, children as young as age 4 were able to distinguish between the paintings of abstract expressionists and paintings by other kids and animals with similar compositions. 

The study, conducted by a team of Boston College psychologists, involved about 130 kids between the ages of 4 and 12 years old. They were asked to evaluate 18 paintings by abstract expressionist artists paired with 18 similar paintings done by preschoolers or zoo animals (chimps, apes, monkeys, and gorillas, in this case). Some pairs were unlabeled, and some pairs were labeled with one painting marked “artist” and the other marked "monkey," "child," or "elephant." Some kids saw unlabeled paintings, some saw paintings that were correctly labeled, and others saw paintings that were incorrectly labeled (for example, a painting by a monkey labeled as being by a human artist). 

The researchers found that even the youngest kids were able to successfully discern the work of a professional artist and a painting by a kid or a chimp in the unlabeled experiment. However, they didn’t necessarily think that made the art more appealing. When looking at unlabeled paintings, the 4- to 7-year-old kids preferred the work of other kids or animals, judging them as more appealing than the artists’ paintings. 

Both age groups were more likely to choose the artists’ paintings when asked to judge quality than if they were asked to pick the painting they personally preferred. But when the paintings were correctly labeled, the 8- to 12-year-olds tended to say they preferred the work of the artists. This suggests that not only does professional abstract art have qualities that sets it apart from superficially similar work, but that even young children see a difference between what they prefer and what is considered high quality. 

[h/t BPS Research Digest]

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