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How Urbanites Feel About Their City Spaces

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Recently, Massachusetts-based planning and design firm Sasaki partnered with Equation Research to find out what urbanites love most about their city lives. They hoped to use the information to "shape a more satisfying and sustainable urban experience." But even if you're not a multi-purpose "architecture, interior design, planning, urban design, landscape architecture, graphic design, and civil engineering" firm, the results are pretty interesting. The survey questioned 1000 people who both live and work in Austin, Boston, Chicago, New York, San Francisco, or Washington DC; here's some of what they had to say [PDF].

People are proud of their city's history. When it comes to ascribing icon status to a building, respondents were pretty divided on what matters most. But historical value took the top priority, with 36 percent of people polled saying it's their primary consideration. Meanwhile, 30 percent think it's great architecture and 24 percent appreciate unique design. Similarly, 57 percent said they would stop on the street to admire a building with historic significance. Other notable features—public art and unique design elements (38 percent) or inviting public space (33 percent)—were also likely to attract lingering, but not as often. And when asked how their city could most improve architecturally, a majority (54 percent) thought funds should go towards renovating historical buildings to upgrade their utility while retaining character. That said, answers differed by generation, and younger people were more likely to want their city to invest in more flexible space that could be used for pop-ups and community projects.

What else do people love about city life? All the food, of course! And shopping, too. Fifty-six percent of city-dwellers polled said they enjoy consumer activities—shopping and dining out—and 45 percent get excited for programmed events, which can include outdoor concerts but also farmers' markets and food festivals. When asked what the best part about visiting another city is, the food scene took top marks with 41 percent of the vote. Similarly, 46 percent of respondents said a new restaurant is the thing most likely to incentivize them to venture to a new neighborhood in their own city. New Yorkers, however, were least likely to be enticed by a new restaurant, but maybe that's because there's good food (almost) everywhere here.

It's the buildings that make the cities, but people love the in-between spaces the best. A whopping 65% of people said that their most memorable favorite city experience occurred outside—in a park or on the street. When it comes to what kind of open space people like best, waterfronts took first place with 47 percent.

And ultimately, although they hate the traffic (41 percent say it's the biggest transportation gripe), 76 percent of the current city-dwellers reported seeing themselves staying put for at least another five years.

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iStock // Ekaterina Minaeva
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
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]