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Why Do We Forget What We’re Doing the Minute We Enter a Room?

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Left your keys on the kitchen counter again? No problem. Just go and get them. Walk through the house, into the kitchen, and—what was it you needed to do again? Why are you in here? In less than 30 seconds, you’ve managed to forget the entire purpose of your errand. But don’t worry. It’s not just you, and you’re not losing your marbles. It’s called the Doorway Effect, and it’s actually a sign that your brain is in fine working order. 

Scientists used to believe that memory was like a filing cabinet. You have an experience, and it gets its own little file in your brain. Then, later, you can go back and open the file, which is unchanged and where it should be. It’s a nice, tidy image—but it’s wrong. Your brain is much more complicated and sophisticated than that. It’s more like a super-high-powered computer, with dozens of tasks and applications running at once.

A 2011 study found that the Doorway Effect is the result of several of these brain programs running simultaneously. Researchers taught 55 college students to play a computer game in which they moved through a virtual building, collecting and carrying objects from room to room. Every so often as the participants traversed the space, a picture of an object popped up on the screen. If the object shown was the one they were carrying or the one they had just put down, the participants clicked “Yes.” Sometimes these pictures appeared after the participant had walked into a room; other times they appeared while the participant was still in the middle of a room. The researchers then built a real-world version of the environment and ran the experiment again, using a box to hide the objects people were carrying so they couldn’t double-check.

The results of both trials were the same: The simple act of walking through a doorway made people forget what they were doing. And it wasn’t a matter of distance, either. The researchers asked the question (“Is this what you’re carrying?”) after people had walked a certain distance within a room, and a certain distance between rooms. Within a room, their memories remained mostly intact. But crossing a threshold was like shaking a mental Etch-a-Sketch.

The researchers concluded that their subjects’ brains perceived doorways as a kind of cut-off point. The memories and movement that carried the students through one context literally hit a wall. On the other side of that wall was new context, and a fresh landscape for memory. The participants’ mental computers were combining the tasks of spatial awareness, movement, and memory. But each task requires attention, and you can’t pay attention to everything at once. 

Is there a way to avoid the Doorway Effect? Probably, although science hasn’t found it yet. If you’ve got a trick that works, let us know in the comments.

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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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