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45 Wonderful Illustrations of Sea Life From 1868

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Dry land covers only a small percentage of the planet. It’s no wonder, then, that we’ve always been a little mystified about what’s happening in the oceans, where weird creatures are the rule rather than the exception. The following illustrations were found in a book published in 1868 called The Ocean World, which is a compilation of the translated works of French scientist Louis Figuier. Each illustration was drawn from a specimen in the Museum of Natural History of Paris, where weird-but-beautiful things are collected.

1. The Argonaut

2. Stylaster flabelliformis

3. Sea Anemones

4. Chrysaora gaudichaudi

5. Rhizostoma cuvieri

6. Cephea cyclophora

7. Physophora hydrostatica

8. Agalma rubra

9. Praya diphys

10. Physalia utriculus

11. Asterias rubens

12. Pentacrinus europaeus

13. Ophiocoma russei

14. Sea Urchins

15. Synapta duvernaea

16. Oysters

17. Pectinidae

18. Spondylus

19. Razorfish

20. Turritellidae

21. Conus

22. Cypraeadae

23. Voluta

24. Tritons

25. Cerithium

26. Octopus macropus

27. Octopus vulgaris

28. Pinnoctopus and Cirrotheutis

29. Gigantic Cuttlefish

30. Palinurus vulgaris

31. Corystes cassivelaunus

32. Raia batis

33. Raia clavata

34. Shark

35. Hammerhead shark

36. Orthagoriscus and Tetraodon

37. Balistes

38. Diodon pilosus

39. Trumpet Pipefish

40. Seahorse

41. Cyclopterus

42. Flying Fish

43. Frogfish

44. Stomia bea

45. Swordfish

Collected from The Ocean World: being a descriptive history of the sea and its living inhabitants, translated from La Vie et les Moeurs des Animaux, by Louis Figuier, and illustrated under the direction of Charles Bévalet from specimens in the Museum of Natural History of Paris, 1867-1868. Where applicable, binomial nomenclature has not been altered from the book's text to avoid misclassification of species.

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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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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iStock
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Why Your iPhone Doesn't Always Show You the 'Decline Call' Button
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iStock

When you get an incoming call to your iPhone, the options that light up your screen aren't always the same. Sometimes you have the option to decline a call, and sometimes you only see a slider that allows you to answer, without an option to send the caller straight to voicemail. Why the difference?

A while back, Business Insider tracked down the answer to this conundrum of modern communication, and the answer turns out to be fairly simple.

If you get a call while your phone is locked, you’ll see the "slide to answer" button. In order to decline the call, you have to double-tap the power button on the top of the phone.

If your phone is unlocked, however, the screen that appears during an incoming call is different. You’ll see the two buttons, "accept" or "decline."

Either way, you get the options to set a reminder to call that person back or to immediately send them a text message. ("Dad, stop calling me at work, it’s 9 a.m.!")

[h/t Business Insider]

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