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7 Taboos From a 17th-Century Coffeehouse

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In the 17th century, London coffeehouses were evolving into consortiums of progressive academics, philosophers, doctors, and lawmakers, including historical heavyweights like Isaac Newton, Jonathan Swift, and Alexander Pope. A snapshot of this scene is captured by Paul Greenwod’s 1674 A Brief Description of the Excellent Vertues of that Sober and wholesome Drink, called Coffee, and its Incomparable Effects in Preventing or Curing Most Diseases incident to Humane Bodies which documents “The RULES and ORDERS of the Coffee-House.” Here are the rules that 17th-century London’s most progressive socialites abided by when they needed a cup of joe.

1. Don’t swear.

Or, if you do have a foul mouth, you'd better have deep pockets to match.

To limit mens expence, we think not fair,
But let him forfeit Twelve-pence that shall Swear:

2. Don’t start a pity party.

Much to the poetic patron’s dismay, disgruntled lovers would have to suffer elsewhere.

No Maudlin Lovers here in Corners Mourn,

3. Don’t talk about God.

Even though most coffeehouses were located next to churches and cathedrals, religion was off limits. Politics, on the other hand, was fair game. Benjamin Franklin frequently visited many London coffeehouses, where he brushed up on politics and social theory.

But all be Brisk, and Talk, but not too much
On Sacred things, Let none Presume to touch,
Nor profane Scripture, or sawcily wrong
Affairs of State with an Irreverent Tongue:

4. Don’t be too serious.

Take what you hear lightly. The ideas you’d hear may spark a revolution or they may just be the coffee talking. Either way, it’s all in good fun.

Let Mirth be Innocent, and each Man see,
That all his Jests without Reflection be;
To keep the House more Quiet, and from Blame,

5. Don’t bet your house on it.

Bets were made on gentlemen’s terms. They should be small and light-hearted.

We Banish hence Cards, Dice, and every game:
Nor can allow of Wagers, that Exceed
Five shillings, which oft-times much Trouble Breed;
Let all that’s lost, or forfeited, be spent
In such Good Liquour as the House does vent,

6. Don’t stay too late.

Drink as much as you please, but you were encouraged to head home to attend to more important matters (writing the laws of gravity, for instance).

And Customers endeavour to their Powers,
For to observe still seasonable Howers.

7. Don’t be a stranger.

You and your wallet-straining addiction to caffeine are in good company—the best scholars of London struggled to resist a daily dose of coffee. Plus, coffeehouses were a center for community. Strangers were welcome, but regulars kept them churning out the good stuff. 

Lastly let each Man what he calls for Pay,
And so you’re welcome to come every day.

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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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