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Dead Celebrities Brought Back To Sell Stuff

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Readers always write, and I love to hear from them—especially if they have an intriguing TV-related question that makes me jump up and down yelling à la Arnold Horshack "Oh! Oh! I know the answer to that!!" Of course, I also love a challenge, so when someone asks a question which I can't answer off the top of my head, it immediately sends me off on a Mission, and I can't rest until I find the answer. (Not that I have this burning desire to be a know-it-all or anything"¦) Welcome to the first installation of what we hope will become a recurring TVHolic feature: The Mailbag. If you have a sincere question that's been bugging you for years, or just something that you think will stump me, this is the place to "bring it." Now, on to this week's question:

"I just saw a commercial for Orville Redenbacher popcorn using old footage of Mr. Redenbacher and that got me thinking....Who else has posthumously pitched products (either for their own company or just in general)?"
"“Sarah

Several companies have raised celebrities from the dead in order to hawk their products, all with varying levels of success.

The trend started in 1991, when Elton John co-starred with Humphrey Bogart, Louis Armstrong and James Cagney in a Diet Coke spot. This was the first instance of deceased celebrities being completely re-created digitally, rather than simply splicing existing footage into a film. The commercial was so successful that a second one was made featuring Paula Abdul (during her initial, pre-American Idol round of stardom) alongside Cary Grant, Groucho Marx and Gene Kelly.

Coors found similar success using John Wayne in a series of spots beginning in 1997. The producers cheated a bit in these ads, though; quite often the only part of the Duke that was digitalized was his face, which was then superimposed onto the body of famed John Wayne impersonator Ermal Walden Williamson, who provided all the "action."

They're Not All Winners, Though

astaire.jpgOne such campaign that backfired was a series of commercials featuring legendary hoofer Fred Astaire "dancing" with a Dirt Devil vacuum cleaner. When the first spot (filmed with the blessing of Astaire's widow, Robin) originally aired during Super Bowl XXXI, it was a critical favorite. But once the commercials hit the airwaves in regular rotation, hard-core MGM musical fans thought replacing Ginger Rogers with a household appliance was disrespectful, and their revulsion was reflected in the company's quarterly sales report. The spots were quietly removed from circulation.

Thanks to Sarah for a great question that inspired an interesting trip down memory lane. Please feel free to send any TV-related questions you may have to kara@mentalfloss.com for use in a future Mailbag!

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iStock // Ekaterina Minaeva
technology
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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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iStock
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Scientists Think They Know How Whales Got So Big
May 24, 2017
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iStock

It can be difficult to understand how enormous the blue whale—the largest animal to ever exist—really is. The mammal can measure up to 105 feet long, have a tongue that can weigh as much as an elephant, and have a massive, golf cart–sized heart powering a 200-ton frame. But while the blue whale might currently be the Andre the Giant of the sea, it wasn’t always so imposing.

For the majority of the 30 million years that baleen whales (the blue whale is one) have occupied the Earth, the mammals usually topped off at roughly 30 feet in length. It wasn’t until about 3 million years ago that the clade of whales experienced an evolutionary growth spurt, tripling in size. And scientists haven’t had any concrete idea why, Wired reports.

A study published in the journal Proceedings of the Royal Society B might help change that. Researchers examined fossil records and studied phylogenetic models (evolutionary relationships) among baleen whales, and found some evidence that climate change may have been the catalyst for turning the large animals into behemoths.

As the ice ages wore on and oceans were receiving nutrient-rich runoff, the whales encountered an increasing number of krill—the small, shrimp-like creatures that provided a food source—resulting from upwelling waters. The more they ate, the more they grew, and their bodies adapted over time. Their mouths grew larger and their fat stores increased, helping them to fuel longer migrations to additional food-enriched areas. Today blue whales eat up to four tons of krill every day.

If climate change set the ancestors of the blue whale on the path to its enormous size today, the study invites the question of what it might do to them in the future. Changes in ocean currents or temperature could alter the amount of available nutrients to whales, cutting off their food supply. With demand for whale oil in the 1900s having already dented their numbers, scientists are hoping that further shifts in their oceanic ecosystem won’t relegate them to history.

[h/t Wired]

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