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Nick Offerman's Twitter Account

17 Things We Learned from Nick Offerman's Latest AMA

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Nick Offerman's Twitter Account

The man otherwise known as Ron Swanson took to Reddit today to answer anything, often in his delightfully dirty way, in advance of the episode of Parks & Rec he's directing April 10. Here's what we learned about Offerman, his facial hair, and woodworking, among other things. (Beware: Some profanity below!)

1. The one thing he really doesn't like.

And that's feta cheese. Offerman does like other cheeses, though: "Gruyere, no reason necessary. Hard cheddars also set my motor to running. Estero Gold."

2. How his wife, Megan Mullally, feels about canoes.

"Her stance on canoes is, of course, seated," Offerman said. "One should not stand on canoes. She loves to paddle just like her dear old husband, and boy, howdy, does she look good doing it."

3. What 19th Century Figure he'd model his facial hair on.

It's the man for whom sideburns are named, "Union Army General Ambrose Burnside." Offerman also put in a link so you can check out the style for yourself.

4. The best advice he's ever been given.

It's a two-parter: "1) Find work that you love to do, and then find a way to get paid to do that work," Offerman said. "2) Always maintain the attitude of a student. If you think you've done learning, bitterness sets in, but if you have more to achieve every day, in any arena, that makes each morning's awakening full of potential and cheery portent."

5. There is no secret to his facial hair.

"I was lucky enough to have been born with some bracken-like whiskers," he said. "If you do not share that fortune, I suggest you cultivate an interesting hair coif or perhaps some pleasing accessories, like a driving cap." If that fails, "Sharpie makes some excellent moustache enhancing implements."

6. He has good advice for dealing with indecision.

"DON'T TREAD WATER FOR TOO LONG, LEST YOU CRAMP UP AND SINK," Offerman said. "Follow your gut, make a choice, and throw yourself into it. If you make a mistake, then you have merely afforded yourself a valuable lesson."

7. And pretty good advice for raising kids, too.

"I have not raised a child, but I believe the fact that you're asking questions and paying attention are very good signs," Offerman told one redditor who has a 4 week old baby. "Love your bairn, try to gently steer him/her towards handtools and away from CNC driven woodworking, which is basically robot craftsmanship. Make sure he/she knows to raise the grain before finish, especially in walnut. When the time is right, introduce charcoal/wood as the clear alternative to gas. Simply put: Give a shit."

8. His favorite adverb is...

"Verily."

9. Here's an Offerman-approved method for learning how to dance...

To learn how to dance, Offerman suggested the follwoing: "Ingest an adequate quantity of dance fuel (Snake Juice, where available, otherwise any potent hootch), close your eyes, and shake what Mother Nature gave you."

10. And how to get started in woodworking.

Do the following: "Read Fine Woodworking magazine, start small with a block plane and a chisel and a spokeshave. Matriculate." He also suggests "begin[ning] with some hand tools, chisel, saw, block plane. Learn to sharpen your steel and then see how it shapes the wood with such ease. Check out a set of Flexcut carving tools and just start building your fundamentals." And if you're just getting into woodworking and have never built a canoe—one of Offerman's specialties—"maybe try a breadbox first."

11. Offerman must really like Teddy Roosevelt.

He didn't explicity say so, but Offerman did quote the great man twice, offering "I wish to preach, not the doctrine of ignoble ease, but the doctrine of the strenuous life" at a Redditor's request for a quote to put in an oak frame he planned to make, and "It is hard to fail, but it is worse never to have tried to succeed" to the Redditor asking for advice about conquering indecision.

12. What he thinks we should all appreciate.

It's the simple stuff: "With all of the visual distraction constantly inundating us in the form of our devices and screens, I really derive a great deal of pleasure from watching the sun rise and set, admiring clouds as they change shape across the sky, watching tree leaves and blossoms undulate in the breeze....these treats foment an ocular-cleansing refreshment to my way of thinking."

13. The funniest Parks & Rec Castmember is...

"Pratt, easy," Offerman said, when asked which makes the rest of them crack up the most. "Lots of mad talent in the ensemble, and Amy is in a league of her own, like the league of Tina and Will Ferrell and Molly Shannon, but Pratt has the wildcard flavor to make us all shit little green apples." But when asked who was hands-down the funniest, Offerman said, "that's a tough one," before elaborating,

Amy Poehler is our champion and leader, and I would have to say she is #1 Chris Pratt is a true comic genius so he's #1.1 Aziz makes anything he says ridiculously funny and Aubrey has a delightfully wicked flavor of evil mischief so they're maybe tied at #1.15 Adam Scott is not behind the folks previously mentioned, plus he wields a mighty sword as a straight man. He's in the #1.05 region. Retta shares Aziz's propensity for simply laying out deliciously crisp one-liners, so I'd rank her in the top 6 as well.... I think that's everybody.

14. He has a lot of favorite books.

"I love a series of books that perpetually fleshes out a world," Offerman said, "like Wendell Berry's Fiction (start with The Memory of Old Jack or Nathan Coulter), The Lord of The Rings, Madeline L'engle's Wrinkle In Time series, The Horatio Hornblower series, Patrick O'Brien's 21-volume Aubrey/Maturin series, The Flashman Papers, The Sharpe series, Little House On The Prairie, The Wind-Up Bird Chronicle, Martin Amis' Dead Babies and Time's Arrow, As I Lay Dying, Michael Pollan's entire catalogue, for a start."

15. He really loves beer.

So much that he won't pick a favorite. "Solemn Oath (Naperville, IL)," Offerman said, before continuing, "I love beer too much to choose...Guinness, Lagunitas, Sierra Torpedo, Negra Modelo, Old Rasputin, Anchor Steam, guinness, Sam Smith, Newcastle, Old Speckled Hen, Pliny Old and Young, Founders Breakfast Stout, Delirium Tremens, I could go on..."

16. And he's working on a new book we're dying to read.

"Writing my first book was incredibly gratifying," Offerman said, "and now I have begun book 2, which will be a list of Great Americans, with an eye towards exploring how we continue to evolve as a civilization through civil disobedience, muckraking, and rebellious thinking."

17. He's into knitting.

Sure, woodworking is his first love, but he's also into knitting, as he revealed when he was advising a Redditor on how to get into woodworking without a shop. "With a block plane and chisels and a spokeshave, you can make smaller items in any room of the house," Offerman said. "A small lathe is also a great choice for a variety of output/not a lot of space required. Knitting is also surprisingly fun and clean!"

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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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Animals
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Scientists Think They Know How Whales Got So Big
May 24, 2017
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iStock

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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