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Michael Lyons

50 Collective Nouns to Bolster Your Vocabulary

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Michael Lyons

Collective nouns may seem like quirky ways to describe groups, but 500 years ago, they were your ticket to the in-crowd. Most collective nouns, or “terms of venery,” were coined during the 15th century. Many were codified in books of courtesy, like the 1486 classic Book of St. Albans. St. Albans was a handbook for medieval gentlemen, and it contained essays on hawking, hunting, and heraldry. Appended to the hunting chapter sits a list of 164 collective nouns, titled “The Compaynys of Beestys and Fowlys.” (Contrary to the title, many terms actually describe people—a biting example of ye olde satire.)

As silly as some sound today, the phrases were formal and proper descriptions. St. Albans was, after all, a vocabulary-booster, a primer designed to help gentlemen-in-training avoid the embarrassment of “some blunder at the table.” Over the next century, the book’s popularity bloomed. Similar courtesy handbooks caught on, and by the end of the 16th century, a slew of collective nouns had entered the lexicon.

Some have achieved widespread currency and acceptance, like a “flight of stairs,” “a board of trustees,” and a “school of fish.” Others, like a “murder of crows,” barely cling on. However, a handful of obscure phrases have made a comeback, thanks to James Lipton’s wonderful compendium of collective nouns, An Exaltation of Larks. Here are a few from Lipton’s book that you should add to your repertoire.

1. Business of Ferrets

2. Labor of Moles

3. Mustering of Storks

4. Shrewdness of Apes

5. Gam of Whales

6. Smack of Jellyfish

7. Host of Angels

8. Fusillade of Bullets

9. Baptism of Fire

10. Quiver of Arrows

11. Tissue of lies

12. Murder of Crows

13. Unkindness of Ravens

14. Dule of Doves

15. Clowder, Cluster, or Clutter of Cats

16. Kindle of Kittens

17. Mute of Hounds

18. Pass of Asses

19. Ostentation of Peacocks

20. Team of Ducks (when flying)

21. Paddling of Ducks (when on water)

22. Trip of Goats

23. Sloth, or Sleuth, of Bears

24. Charm of Finches

25. Hill of Beans

26. String of Ponies

27. Hand of Bananas

28. College of Cardinals

29. Shock of Corn

30. Band of Men

31. Knot of Toads

32. Wedge of Swans (when flying)

33. Parliament of Owls

34. Superfluity of Nuns

35. Abominable Sight of Monks

36. Untruth of Summoners

37. Doctrine of Doctors

38. Damning of Jurors

39. Sentence of Judges

40. Rascal of Boys

41. Gaggle of Women

42. Gaggle of Gossips

43. Impatience of Wives

44. Tabernacle of Bakers

45. Poverty of Pipers

46. Fighting of Beggars

47. Neverthriving of Jugglers

48. Herd of Harlots

49. Worship of Writers

50. Hastiness of Cooks

According to Lipton, the terms above “are authentic and authoritative. They were used, they were correct, and they are useful, correct—and available—today.” You can pick up a copy of Lipton's book here.

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iStock // Ekaterina Minaeva
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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Name the Author Based on the Character
May 23, 2017
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