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10 Venn and Not-quite-Venn Diagrams

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Venn diagrams are used for more than just useful stuff like science and demographics. Diagrams just for fun are still useful in that they make the concept of graphic sorting and labeling of relationships easy to understand and appreciate. A true Venn shows all possible overlaps between sets.

1. Venn Diagram

This one can be an introduction, but it's far too simplistic. There are plenty of diagrams that feature circles but are not Venn. Pie charts are the first that come to mind. Many images labeled as Venn diagrams are actually Euler diagrams, which show sets and overlaps, but do not have to show all possible overlaps, just existing overlaps. Some diagrams veer off into hard-to-label territory, but that's alright as long as we get a smile from them.

2. Senseless Venn Diagram


Jason Eppink bought the domain "" and uses it for many interesting pages, but his index page is the only one with a Venn diagram, using four ellipses. It's not senseless at all, as the overlapping fields categorize links to Eppink's creations and other sites.

3. Mythical Creatures


The post 6 Animals that Show Mother Nature's Sense of Humor took a cockeyed look at crossing one animal with another to make something completely different. Many fantastic beasts from folklore follow this trend. Jim Unwin diagrammed various mythical creatures by the parts contributed to them by real animals. View the full-size version to see how the unicorn is the overlap of a horse and a narwhal. The circle in the middle is, of course, a human. This is an example of an Euler diagram.

4. Social Networking


This diagram from slots your perfect social networking site(s)  according to your personality disorders. The diagram is available on a t-shirt. I have accounts at all those places and more, so all my idiosyncrasies are covered.

5. The Vin Diagram


It only makes sense that Vin Diesel should have his own diagram. The overlap is nothing to be proud of, but hey, do you have a diagram?

6. Valentines Day


This timely chart tells you what to do for her on Valentines Day. The vertical axis is how much money you have, and the horizontal axis is how much you care for her. This one is a bubble chart instead of a diagram, but it has circles and may be useful for the upcoming holiday.

7. Looking for Love


GraphJam has a generator anyone can use to create graphs on any subject. The potential partner diagram is obviously from someone a bit depressed about the mating game.

8. Cecilia


You'll find many diagrams more or less explaining songs at JamPhat and GraphJam. Making song diagrams is now a popular pastime and shows up in other places as well. This diagram of a Simon and Garfunkel song was seen on the TV show How I Met Your Mother.

9. Happy/Sad


Here's a Venn diagram that shows the intersection of two opposites. It doesn't sound logical, but these are human emotions, which are rarely logical. We've all held simultaneously happy and sad feelings, although the contents of the overlap are personal and will vary. The Happy/Sad diagram is available on a t-shirt.

10. Comics


Is this a Venn diagram? Jeffrey Rowland at the webcomic Overcompensating created a diagram about the trend toward comedic diagrams. A reader told him it wasn't a true Venn diagram and so he produced the diagram shown here. Then he was corrected again and told that the original was a true Venn.


How true.

See also: Fun with Venn and Euler Diagrams and Fun with Pie Charts.

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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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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]