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The Quick 10: 10 Pairs of Actors Oscar-Nominated for the Same Role

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There's no shortage of Oscar trivia, so I thought we'd prepare for Sunday's awards by finishing out the week with a couple of posts on the topic. Stay tuned for tomorrow's installment.

Some roles just seem destined to win an Oscar, don't they? For example, a Best Supporting Actress Oscar has been handed out to women who have played prostitutes a staggering eight times (that would be Anne Baxter, Claire Trevor , Donna Reed, Jo Van Fleet, Dorothy Malone, Shirley Jones, Mira Sorvino and Kim Basinger). And in 1984, three of the five Best Actress nominees were nominated for playing farmers desperately trying to keep the farm going under in the face of hardships (Sally Field in Places of the Heart, Jessica Lange in Country and Sissy Spacek in The River).

Likewise, playing a certain character seems to increase your chance of taking home the statuette as well. Here are 20 people who were nominated for playing the very same role.

henryv1. Laurence Olivier and Kenneth Branagh were both nominated for their roles as Henry V in adaptations of Shakespeare's Henry V (the 1944 and 1989 versions, respectively). Coincidentally, they both also directed. And here's another bit of random trivia for you: both Laurence Olivier and the real Henry V are buried at Westminster Abbey.

2. Anthony Hopkins and Frank Langella were both nominated for playing Richard Nixon "“ Hopkins in 1995 and Langella just last year. Hopkins lost to Nicolas Cage (Leaving Las Vegas) and Langella lost to Sean Penn (Harvey Milk).

3. It's not restricted to actors playing real people, though "“ fictional characters make the list, too. Leslie Howard and Rex Harrison both received Oscar nods for portraying Professor Henry Higgins "“ Howard in Pygmalion (1938) and Harrison in the version with Audrey Hepburn that most people know, My Fair Lady (1964). Harrison won the Oscar; Howard didn't.

4. If you ever get an offer to play Vito Corleone, you'd better not refuse. (Feel free to groan at my horrible pun. I won't be offended.) Marlon Brando won for playing Don Vito in the first Godfather in 1972; Robert DeNiro won Best Supporting Actor for playing the younger version of him in The Godfather Part II just two years later.

elizabeths5. 1999 was a pretty unique year "“ it's the only time two actresses have been nominated for playing the same person in the same year, but in different movies. Cate Blanchett was nominated for Best Actress for her title role in Elizabeth, but Judi Dench also portrayed Henry VIII's daughter in Shakespeare in Love. Blanchett lost to Gwyneth Paltrow, of course, but Judi Dench took home the trophy. She later said she felt weird about taking Oscar home because she just deserved a little sliver of him since she was only onscreen for eight minutes of the entire movie.

6. And, speaking of Cate Blanchett, she has the special distinction of being the only actress to be nominated twice for playing the same person. She was again nominated for playing the Queen in Elizabeth: The Golden Age nine years after the first movie.

7. There's another trend: playing a member of the royal family seems to give you an Oscar edge, because Charles Laughton and Richard Burton were both nominated for playing the gluttonous Henry VIII. Laughton stepped into Henry's breeches in 1933 "“ in fact, it made him the first British actor to win an Oscar (granted, it was only the sixth Academy Awards ever). Burton didn't have the same success "“ he lost to John Wayne (True Grit).

8. A Star is Born is one of those movies destined for Oscars. The original 1937 version earned Janet Gaynor a nomination and the 1954 remake starring Judy Garland got her one as well. Barbra Streisand didn't get a nomination when she played the role of the young ingénue in the 1974 remake, but that may have not counted for this list anyway "“ whereas the first two movies had the lead actresses portraying thespian Vicki Lester, Streisand played a singer named Esther Hoffman. And while Babs didn't get an Oscar nom for lead actress, she did win an Academy Award for Best Original Song for this movie.

9. Kate Winslet and Gloria Stuart were nominated for playing the same person in the same movie in the same year. I bet you know what I'm talking about "“ Winslet played young Rose DeWitt in the 1997 blockbuster Titanic and Stuart portrayed the, shall we say, mature version of Rose. They were both nominated "“ Winslet for Best Actress and Stuart for Best Supporting Actress. Both lost.

10. Strangely, Winslet experienced the exact same thing at the 2001 Academy Awards, when both she and Judi Dench were nominated for playing Iris Murdoch in different time frames in the movie Iris. Again, they both lost. But we all know Winslet has an Oscar now (and apparently keeps it in her bathroom).

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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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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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