CLOSE
Original image

The Summer Homes of 5 Legendary Authors

Original image

Getty Images / Wikimedia Commons

What do great authors do at their summer homes? Compose our favorite beach reads.

1. AGATHA CHRISTIE - Greenway • Devon, England

Christie called it simply “the ideal house.” She bought the cream-colored mansion and its verdant flower gardens, which sweep down to the River Dart, in 1938 for a mere £6,000—about $200,000 today. She especially liked the bathroom, where she soaked in the tub and dreamed up book ideas. (She even had a ledge installed over the tub to hold paper, pencils, and apples.) On top of inspiring tons of novels, Greenway turned Christie into a ruthless flower contest junkie. The estate took home so many blue ribbons that Christie felt bad for the competition. She started her own prize—the Agatha Christie Cup—to give others a chance.

2. MARK TWAIN - Quarry Hill Farm • Elmira, NY

Getty Images / Wikimedia Commons

Twain’s stories may transport you to the banks of the Mississippi, but that’s not where he did his writing. For 20 summers, the humorist traveled to the “quietest of all quiet places”—his sister-in-law’s hilltop farm in Elmira, New York. Twain wrote inside a small, detached octagonal study resembling a steamboat’s pilothouse (above). The view of the Chemung River—which Twain called a “foretaste of heaven”—gave him the peace and quiet to write classics like Tom Sawyer, The Prince and the Pauper, and Huckleberry Finn. It’s also where Twain met John T. Lewis, a free black man who worked on the family farm. In 1877, Lewis saved two of Twain’s relatives by jumping on a runaway carriage and stopping it before it could spill over a bluff. Instantly a family hero, Lewis became one of Twain’s closest friends—and the likely inspiration for Huck’s timeless buddy Jim.

3. VIRGINIA WOOLF - Talland House • St. Ives, Cornwall

Getty Images/ Smith College

Angry waves still crash into the rocky white lighthouse that inspired Woolf to pen her modernist masterpiece, To the Lighthouse. She spent 13 of her childhood summers in St. Ives, Cornwall, in this home overlooking Porthminster Bay, a place her father called “the very toenail of England.” A prominent editor and critic, Woolf’s father was a close friend of author Henry James, who frequently visited Talland House and played with Virginia. She recalled it being the only place that made her consistently happy.

4. BEATRIX POTTER - Lingholm • Cumbria, England

Getty Images / TripAdvisor

Most remember her as the mother of Peter Rabbit and Squirrel Nutkin, but Potter’s neighbors knew her better as that-lady-who- herds-all-those-sheep. Potter first came to the summer estate in the Lakes District when she was 19, and she quickly budded into an amateur naturalist. She drew pictures of the woodland wildlife scampering in the backyard, which eventually appeared in her children’s books. (Lesser known are her drawings of, and academic writing on, fungi spores. Hey, you can’t be famous for everything.)

5. F. SCOTT FITZGERALD - Cap d’Antibes • French Riviera

Getty Images / Wikimedia Commons

Fitzgerald was rich and famous by the time he was 23. Despite all that success, he escaped to France and summered on the French Riviera, where he could “live on practically nothing a year.” His villa in Cap d’Antibes had a pool terrace, a private beach, gardens, a view of the Mediterranean Sea, and even its own nightclub. He wrote the Great Gatsby there and also met the couple that inspired him to write Tender Is the Night. (It’s said the book’s cover was inspired by the view from his terrace.) His presence also helped turn the then dirt-cheap Riviera into a pricey haven for American tourists.

This story originally appeared in mental_floss magazine. Subscribe to our print edition here, and our iPad edition here.

Original image
iStock // Ekaterina Minaeva
technology
arrow
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
Original image
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!

Original image
iStock
Animals
arrow
Scientists Think They Know How Whales Got So Big
May 24, 2017
Original image
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]

SECTIONS
BIG QUESTIONS
BIG QUESTIONS
WEATHER WATCH
BE THE CHANGE
JOB SECRETS
QUIZZES
WORLD WAR 1
SMART SHOPPING
STONES, BONES, & WRECKS
#TBT
THE PRESIDENTS
WORDS
RETROBITUARIES