CLOSE
Original image
Thinkstock

10 Old Sayings We Need to Bring Back

Original image
Thinkstock

Before the Internet, we could not use memes of Willy Wonka or a triumphant baby to express ourselves. Instead, we used proverbs: catchy lines that encapsulate universal truths. Some were introduced to the world by witty writers, and some seemed to emerge fully formed into the collective conscious. Many of them are still with us (I’m not pulling your leg; More than you can swing a cat at), but many more have fallen out of use over the centuries. Here are 10 that should really be brought back.

1. “Bed is the poor man’s Opera.”

Source: Old Italian proverb
Meaning: The man who can’t afford expensive entertainments can still conduct the most passionate of orchestrations in his own bed.
Modern Usage: Something charming to say to your girlfriend when you’ve blown your paycheck on EVE Online Time Codes but are still hoping to get lucky.

2. “Children are certain cares, but uncertain comforts.”

Source: How the Good Wife, 1460
Meaning: You can bet you’re gonna have to change their diapers, but there’s no guarantee they’ll stick around to change yours.
Example of Modern Usage: The proper response to anyone who smiles smugly at a childless woman in her mid-thirties, points to their watch and says, “tick tick tick!”

3. “When cobwebs are plenty kisses are scarce.”

Source: Notes and Queries, 1864
Meaning: Dirty houses are not sexy.
Example of Modern Usage: Something a wife might say in bed as she shoves a body pillow between her sweat-pant clad body and her husband’s. Especially if that husband promised to use the weekend to remove all his old Maxim magazines and dusty weightlifting crap from the guest room, and then didn’t.

4. “He who would pun would pick a pocket."

Source: Alexander Pope, 1729
Meaning: If you’re of such low character the best jokes you can come up are throwbacks from the Brady Bunch Variety Hour, there is nothing you won’t stoop to.
Example of Modern Usage: You can try to silence Uncle Ron’s miserable jokes next Thanksgiving with this bon mot… but he’ll probably just answer back with, “He who would stun would pee on a socket.” And then swipe your wallet.

5. “A friend to all is a friend to none.”

Source: Wadroephe, 1623
Meaning: This is why we hate politicians. They have to morph to please so many different types of people; they appear dishonest and false.
Example of Modern Usage: Your explanation to your friends for why you voted for Nader. He’s not a friend to anyone who guiltlessly emits carbon, so you know you can trust him!

6. “Garlic makes a man wink, drink, and stink.”

Source: Nashe, 1594
Meaning: Garlic inflames your lust, lures you to drunkenness, and makes your entire body smell like over-seasoned meat.
Example of Modern Usage: A joyful Best Man’s toast at a New Jersey wedding reception. Because c’mon, who wouldn’t wish for an awesome life of wink and stink for their best friend?

7. “The gist of a lady’s letter is in her postscript.”

Source: Edgeworth, 1801
Meaning: From your grandma to your girlfriend, all the preceding paragraphs about the health of pets and the obnoxiousness of Cindy from work mean nothing compared to the stuff after the “P.S.”
Modern Usage Example: No matter how cheerful the email, if it’s followed by a P.S. that says, “Oh by the way I noticed you didn’t take the car for an oil change like you said you were going to…”, this was the purpose of the entire correspondence, and you are in peril.

8. “Bachelor’s wives and maid’s children are well taught.”

Source: Heywood, 1546
Meaning: When you don’t have a spouse or a kid, you know everything about maintaining a healthy relationship with spouses and kids.
Modern Usage Example: When your single-and-loving it! friend informs you that you really shouldn’t yell at your 6 year old for trying to force the dog and cat to kiss, and instead use the positive-reinforcement tactics she recently learned in her Intro to Psych class. Invite her to practice those tactics while you go spend an hour or two at Starbucks. Do not show her where you keep your Xanax. She has a lesson to learn.

9. “We are born crying, live complaining, and die disappointed.”

Source: Unknown
Meaning: Oh, I think you know all too well what this means.
Modern Usage Example: Anytime anyone asks you for anything, ever.

10. “Gluttony kills more than the sword.”

Source: Barclay, 1509
Meaning: Even in 1509, when you had to overtake and slay your food before consuming it, overeating was still hardening arteries, enlarging hearts, and filling graveyards.
Modern Usage Example: Thing you say to anyone who presumes to take the last piece of The Colonel’s fried chicken when it is rightfully yours. Can be accompanied with a friendly jiggle of whichever bit of their body fat you can reach. (We're not responsible for any subsequent injuries.)

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
quiz
arrow
Name the Author Based on the Character
May 23, 2017
Original image
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