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Learning a Second Language Keeps Your Brain Young

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Parli Italiano? ¿Hablas Español? Can you speak more than one language? No matter how old you are, it’s not too late to learn. In fact, new research finally shows that learning a second (or third) language as an adult can help slow brain decline.

The benefits of bilingualism are no secret. Previous studies suggest people who regularly speak more than one language show a later onset of dementia and improved mental function. But there was always the pesky problem of correlation vs. causation: Were smarter people simply more likely to learn extra languages? Or were they smarter because they learned extra languages? A recent study from the University of Edinburgh is the strongest evidence yet that, indeed, learning a second language can improve your mental functions—even if you learn the language later in life.

The results come thanks to something called the Lothian Birth Cohort study. In 1947, 1100 11-year-old school children around Edinburgh, Scotland, were given cognitive tests. All of them spoke just one language at the time, but many went on to learn at least one other language as adults, making them (and their test scores) a gold mine for language researchers like Thomas Bak. And because “people of this generation don’t move around that much, it was possible trace them as well,” Bak tells mental_floss.

He and his team tracked down 853 of the original test subjects, now in their early 70s. One-third had learned to speak an additional language since the original test, and 65 of those became bilingual after turning 18. Some learned Gaelic, others learned French in school, or German. Others even traveled to Africa and learned African languages.

Bak gave the same cognitive tests to the original participants to compare their performance with that of their 11-year-old selves. The original scores set a baseline for measuring and predicting mental function: If they performed poorly at age 11, researchers predicted the subjects would also perform relatively poorly at age 73. If their original test scores were high, they would probably be high again at age 73. The results show that “people perform better than you would predict only on the basis of if they learn another language,” says Bak.

This is an important finding, Bak says, because for a long time it was believed that the only time to learn a second language was as a child, when your brain is still nice and sponge-y. This research says even learning it later has positive effects on mental function.

But what is it about language that is so good for our brains? Bak says the act of switching between several languages may give the brain a workout, since you have many more words and meanings to choose from before speaking. He compares it to the physical workout of swimming. “You are using most of your muscles and breathing and so on,” he says. “In being bilingual you’re activating a whole range of different mental functions.”

If you learn three, four, or even five languages, does your brain become stronger with each? Bak says this isn’t clear yet. In theory, the more languages you know, the more mental switches you’ll need to make when speaking, he says, but it’s hard to generalize about something as complicated as language. But there’s no harm in learning as many as possible.

And if you think you’re too old, just remember: our brains are designed for this. “Bilingualism might have been the original state of human communities,” Bak says. “It was more the rule than the exception. The fact we have this ability means in a way our brains are designed to do it.”

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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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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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