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Results Not Typical: Celebrity Secrets Behind the Advertised Weight Loss

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The Federal Trade Commission is currently reviewing new guidelines for product endorsements. Their major beef? Advertisements that show "extreme" benefits of a product with a tiny, fine-print disclaimer. The new rules will force advertisers to show the typical or average results consumers can expect after using their product. And many companies are already sweating over the impact this may have on sales. As one rep put it, "Someone who can't fit in an airline seat is not going to pick up the phone for a 10-pound weight change."

Some of the celebrity spokespersons who might find their contracts affected by the new rules include:

Jillian Barberi's "Before" Shots

Nutrisystem spokesmodel Jillian Barberi boasts of losing 41 lbs. on the plan. What the fine print fails to mention is that in her "before" photos, Jillian is pregnant. Alert viewers in the Los Angeles area spotted her wearing the same dress (in the same physical shape) on a local morning TV show while gushing about her expected baby. Once baby Ruby was born, Barberi not only went on the Nutrisystem plan, she also hired a personal trainer (according to an interview in People) to get herself back in shape.

The Osmond Way

Picture 42.pngMarie Osmond also shills for Nutrisystem. What the TV testimonials don't mention, however, is that at about the same time Marie signed up for Nutrisystem, she also joined the Choose to Move program. And then she landed a spot on Dancing with the Stars, which she admitted required six hour per day workouts for several months that left her breathless and dripping with perspiration. While the  Nutrisystem foods must have helped, the relentless exercise also contributed to her losing an amazing 40 lbs. in five months.

Jared's Subway Secret

Picture 35.pngYou know Jared Fogle from the Subway commercials. Fogle lost 245 lbs. by eating Subway sandwiches. But it wasn't just the subs that did the trick; at age 20 Jared was consuming approximately 10,000 calories per day, and his physician father warned him that he was headed for an early grave if he didn't change his lifestyle. Jared saw an ad for Subway's "7 under 6" campaign and tried a turkey sub. He liked the sandwich and continued to use Subway as a daily source of low-fat meals, but he also incorporated exercise into his daily routine. Instead of using public transportation, he walked to Subway, and he used the stairs rather than the elevator whenever possible. After he lost some initial weight he found that his energy level had increased, and he began walking an additional mile or more per day.

No Ordinary Quacks

The new regulations will also require medical professionals who endorse products (often just referred to onscreen as "Dr.  ----", with no specialty or credentials listed) to be a specialist in said field; that is, an ophthalmologist could not legally give expert advice regarding a colon cleansing product. It will also be required that celebrities who endorse a product must reveal whether or not they are getting paid for the promotion and if they have an ownership interest in said product.

Which ads will you be glad to see struck down by the new rules? Those "work at home" schemes which prey on the elderly and the unemployed? Or maybe the myriad of skin rejuvenation products that subtly suggest women will certainly be dumped for a younger model if they let their face go to seed? Of course, men are also targets of insecurity, with all those "enhancement" products being pitched"¦.   Don't be shy, voice your outrage!

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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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