This is important. This is important. This is important. This is important.

This is important.

(via i-am-corbin-dallas)

josephkeerys-archive:
“What We Do in the Shadows (2014) dir. Taika Waititi, Jemaine Clement
”
#parenting josephkeerys-archive:
“What We Do in the Shadows (2014) dir. Taika Waititi, Jemaine Clement
”
#parenting

josephkeerys-archive:

What We Do in the Shadows (2014) dir. Taika Waititi, Jemaine Clement

#parenting

cinemove:
“What We Do In The Shadows (2014) dir. Taika Waititi and Jemaine Clement
” cinemove:
“What We Do In The Shadows (2014) dir. Taika Waititi and Jemaine Clement
” cinemove:
“What We Do In The Shadows (2014) dir. Taika Waititi and Jemaine Clement
” cinemove:
“What We Do In The Shadows (2014) dir. Taika Waititi and Jemaine Clement
” cinemove:
“What We Do In The Shadows (2014) dir. Taika Waititi and Jemaine Clement
” cinemove:
“What We Do In The Shadows (2014) dir. Taika Waititi and Jemaine Clement
” cinemove:
“What We Do In The Shadows (2014) dir. Taika Waititi and Jemaine Clement
” cinemove:
“What We Do In The Shadows (2014) dir. Taika Waititi and Jemaine Clement
”

cinemove:

What We Do In The Shadows (2014) dir. Taika Waititi and Jemaine Clement

(via cinemove)

Dungeons and Dragons creatures, generated by neural network

lewisandquark:

The game Dungeons and Dragons has all sorts of lists of spells and abilities you can use for gameplay. I trained an algorithm called a recurrent neural network to generate more spells - like Barking Sphere, Hold Mouse, and Gland Growth. Then, with a larger set of spells in my training dataset, I trained a better neural net that generated even more - like Song of the Dave, Summon Ass, and Shield of Farts.

It turns out that in addition to spellbooks, Dungeons and Dragons also has monster manuals - books full of the names and descriptions of creatures that adventurers can encounter. Colin Fredricks, who created the RPG Sufficiently Advanced, was kind enough to send me the names of 2,205 creatures from the 2nd edition monster manual. 

As I had hoped, the neural network generated creatures that would probably be pretty awesome.

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Owlborn
Cat, Stone
Vampire Bear
Kick Spirit
Hatfright
Purple Bird
Slug, Spectral
Wolf, Chromatic
Golem, Rain
Human, Crystal
Hound, Plant
Fish, Astro-
Wolfworm
Ogre, Space
Dog, Goblin
Serpent Shark
Mommy, Greater
Giant, Dunebat
Cloud of Chaos

It also generated some creatures that you should probably run from until you figure out what they are. (Though Dome Animal might simply be a cool turtle)

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Brain, Fire
Horse (Spider, Brain
Undead Lake Man, Fire
Walfablang
Fraithwarp, Giant
Fish, Sun of
Lycanthrope, Wereladoo
Pat, Great, Space
Shadowstaffer
Spectral Woof Greepy
Jabberwont
Animal, Dome
Dwarf, Giant
Burglestar
Pigaloth
Beeple, Desert
Wendless Woll
Memeball
Marraganralleraith

There were 118 dragons in the original dataset, so of course the neural net liked generating new dragons. Some perhaps better-conceived than others.

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Dragon, Death Seep
Dragon, Purple Fang
Dragon, Curple Lard
Dragon, Dead
Big Dragon
Will O’Dragon

And it generated new unicorns!

Unicorn, Fumble
Unicorn, Bat
Unicorn, Black Willow
Unicorn, Sith Sheet

These might be possible misses, though.

Man-Can
Barber
Beet
Skull
Feast, Stone
Peg, Brown
Kurt
Durp Snake
Golf
Vampire, Putter

Enter your email here and I’ll send you a few more creatures that wouldn’t fit in the main post. Including the legendary Bung Dragon!

I’m crowdsourcing a couple more D&D-related datasets - see below!

Also, I thought it would be fun to generate D&D character names for a future project. If you go to this form (no email required), you can enter your character’s name, race, and class. Once I have enough of these, I’ll give them to the neural network and see what happens. Edit: wow, over 10,000 responses so far! (Check them out at this link) Keep them coming!

I’m also collecting character backstories! Submit as many as you like. https://goo.gl/forms/ReInNw0Tz0mwzTLO2 I will post some generated character bios as soon as I can figure out a strategy that works better than this:

There was the prince of the sun. He was raised by the arcane arts and accepted him to become a fire work and the pig of the scorpions. He was in the blood of curious by the world to be a part of the church, really with the bartender.

I love this neural network nonsense.

SkyKnit: When knitters teamed up with a neural network

lewisandquark:

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[Make Caows and Shapcho - MeganAnn]

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[Pitsilised Koekirjad Cushion Sampler Poncho - Maeve]

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[Lacy 2047 - michaela112358]

I use algorithms called neural networks to write humor. What’s fun about neural networks is they learn by example - give them a bunch of some sort of data, and they’ll try to figure out rules that let them imitate it. They power corporate finances, recognize faces, translate text, and more. I, however, like to give them silly datasets. I’ve trained neural networks to generate new paint colors, new Halloween costumes, and new candy heart messages. When the problem is tough, the results are mixed (there was that one candy heart that just said HOLE).

One of the toughest problems I’ve ever tried? Knitting patterns.

I knew almost nothing about knitting when @JohannaB@wandering.shop sent me the suggestion one day. She sent me to the Ravelry knitting site, and to its adults-only, often-indecorous LSG forum, who as you will see are amazing people. (When asked how I should describe them, one wrote “don’t forget the glitter and swearing!”)

And so, we embarked upon Operation Hilarious Knitting Disaster.

The knitters helped me crowdsource a dataset of 500 knitting patterns, ranging from hats to squids to unmentionables. JC Briar exported another 4728 patterns from the site stitch-maps.com

I gave the knitting patterns to a couple of neural networks that I collectively named “SkyKnit”. Then, not knowing if they had produced anything remotely knittable, I started posting the patterns. Here’s an early example.

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MrsNoddyNoddy wrote, “it’s difficult to explain why 6395, 71, 70, 77 is so asthma-inducingly funny.” (It seems that a 6000-plus stitch count is, as GloriaHanlon put it, “optimism”). 

As training progressed, and as I tried some higher-performance models, SkyKnit improved. Here’s a later example.

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Even at its best, SkyKnit had problems. It would sometimes repeat rows, or leave them out entirely. It could count rows fairly reliably up to about 22, but after that would start haphazardly guessing random largish numbers. SkyKnit also had trouble counting stitches, and would confidently declare at the end of certain lines that it contained 12 stitches when it was nothing of the sort.

But the knitters began knitting them. This possibly marks one of the few times in history when a computer generated code to be executed by humans.

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[Mystery lace - datasock]

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[Reverss Shawl - citikas]

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[Frost - Odonata]

The knitters didn’t follow SkyKnit’s directions exactly, as it turns out. For most of its patterns, doing them exactly as written would result in the pattern immediately unraveling (due to many dropped stitches), or turning into long whiplike tentacles (due to lots of leftover stitches). Or, to make the row counts match up with one another, they would have had to keep repeating the pattern until they’d reached a multiple of each row count - sometimes this was possible after a few repeats, while other times they would have had to make the pattern tens of thousands of stitches long. And other times, missing rows made the directions just plain impossible. 

So, the knitters just started fixing SkyKnit’s patterns.

Knitters are very good at debugging patterns, as it turns out. Not only are there a lot of knitters who are coders, but debugging is such a regular part of knitting that the complicated math becomes second nature. Notation is not always consistent, some patterns need to be adjusted for size, and some simply have mistakes. The knitters were used to taking these problems in stride. When working with one of SkyKnit’s patterns, GloriaHanlon wrote, “I’m trying not to fudge too much, basically working on the principle that the pattern was written by an elderly relative who doesn’t speak much English.”

Each pattern required a different debugging approach, and sometimes knitters would each produce their own very different-looking versions. Here are three versions of “Paw Not Pointed 2 Stitch 2″.

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[Top - ActualJellyfishMiddle - LadyAurianBottom (sock version) - ShoelessJane]

Once, knitter MeganAnn came across a stitch that didn’t even exist (something SkyKnit called ’pbk’). So she had to improvise. “I googled it and went with the first definition I got, which was ‘place bead and knit’.” The resulting pattern is “Ribbed Rib Rib” below (note bead).

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[Ribbed Rib Rib - MeganAnn]

Even debugged, the patterns were weird. Like, really, really nonhumanly weird.

“I love how organic it comes out,“ wrote Vastra. SylviaTX agreed, loving “the organic seeming randomness. Like bubbles on water or something,” 

SkyKnit’s patterns were also a pain. Michaela112358 called Row 15 of Mystery Lace (above) “a bit of a head melter”, commenting that it “lacked the rhythm that you tend to get with a normal pattern”. Maeve_ish wrote that Shetland Bird Pat “made my brain hurt so I went to bed.” ShoelessJane asked, “Okay, now who here has read Snow Crash?”

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[Winder Socks (2 versions) - TotesMyName]

“I was laughing a few days ago because I was trying to math a Skyknit pattern and my brain…froze. Like, no longer could number at all. I stared blankly at my scribbles and at the screen wondering what had happened til somehow I rebooted. Yup, Skyknit crashed my brain.” - Rayn63

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[Paw chain 2 - HMSChicago]

On the pattern SkyKnit called “Cherry and Acorns Twisted To”:

“Couple notes on the knitting experience, which while funny wasn’t terribly pleasurable: Because there’s no rhythm or symmetry to the pattern, I felt I was white-knuckling it through each line, really having to concentrate. There are also some stitch combinations that aren’t very comfortable to execute physically, YO, SSK in particular.

That said, I’m nearly tempted to add a bit of random AI lace to a project, perhaps as cuffs on a sweater or a short-row lace panel in part of a scarf, like Sylvia McFadden does in many of her shawl designs. As another person in the thread said, it would add a touch of spider-on-LSD.” -SarahScully

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[cherry and acorns twisted to - Sarah Scully]

BridgetJ’s comments on “Butnet Scarf”:

“Four repeats in to this oddball, daintily alien-looking 8-row lace pattern, and I have, improbably, begun to internalize it and get in to a rhythm like every other lace pattern.

I still have a lingering suspicion that I’m knitting a pattern that could someday communicate to an AI that I want to play a game of Global Thermonuclear War, but I suppose at least I’ll have a scarf at the end of it?” -BridgetJ

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[butnet scarf - BridgetJ]

There was also this beauty of a pattern, that SkyKnit called “Tiny Baby Whale Soto”. GloriaHanlon managed somehow to knit it and described it as “a bona fide eldritch horror. Think Slenderman meets Cthulu and you wouldn’t be far wrong.”

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[Tiny Baby Whale Soto - GloriaHanlon]

Other than being a bit afraid of Tiny Baby Whale Soto, the knitters seem happy to do the bidding of SkyKnit, brain melts and all.

“I cast on for a lovely MKAL with a designer I totally trust and became immediately suspicious because the pattern made sense. All rows increase in an orderly manner. There are no “huh?” moments. There are no maths at all…it has all been done for me. I thought I would be happy, yo. Instead, I am kind of missing the brain scrambling and I keep looking for pigs and tentacles. Go figure.” - Rayn63

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Check out the rest of the SkyKnit-generated patterns, and the glorious rainbow of weird test-knits at SkyKnit: The Collection and InfiKnit

There’s also a great article in the Atlantic that talks a bit more about the debugging. 

If you feel so inspired (and don’t mind the kind-hearted yet vigorous swearing), join the conversation on the LSG Ravelry SkyKnit thread - many of SkyKnit’s creations have not yet been test-knit at all, and others transform with every new knitter’s interpretation. Compare notes, commiserate, and do SkyKnit’s inscrutable bidding!

Heck yeah there is bonus material this week. Have some neural net-generated knitting & crochet titles. Some of them are mixed with metal band names for added creepiness. Enter your email here to get more like these:

Chicken Shrug
Snuggle Features
Cartube Party Filled Booties
Corm Fullenflops
Womp Mittens
Socks of Death
Tomb of Sweater
Shawl Ruins

Seriously I laughed so hard at the Socks of Death.

art-and-things-of-beauty:
“Portrait drawings by John Singer Sargent, (American, 1856–-1925)
”
This is my [artistic] jam. art-and-things-of-beauty:
“Portrait drawings by John Singer Sargent, (American, 1856–-1925)
”
This is my [artistic] jam. art-and-things-of-beauty:
“Portrait drawings by John Singer Sargent, (American, 1856–-1925)
”
This is my [artistic] jam. art-and-things-of-beauty:
“Portrait drawings by John Singer Sargent, (American, 1856–-1925)
”
This is my [artistic] jam. art-and-things-of-beauty:
“Portrait drawings by John Singer Sargent, (American, 1856–-1925)
”
This is my [artistic] jam. art-and-things-of-beauty:
“Portrait drawings by John Singer Sargent, (American, 1856–-1925)
”
This is my [artistic] jam. art-and-things-of-beauty:
“Portrait drawings by John Singer Sargent, (American, 1856–-1925)
”
This is my [artistic] jam. art-and-things-of-beauty:
“Portrait drawings by John Singer Sargent, (American, 1856–-1925)
”
This is my [artistic] jam. art-and-things-of-beauty:
“Portrait drawings by John Singer Sargent, (American, 1856–-1925)
”
This is my [artistic] jam. art-and-things-of-beauty:
“Portrait drawings by John Singer Sargent, (American, 1856–-1925)
”
This is my [artistic] jam.

art-and-things-of-beauty:

Portrait drawings by John Singer Sargent, (American, 1856–-1925)

This is my [artistic] jam.

(via hepburnandhepburn)

sonnet30:

hamlet’s dad: son you need to avenge me

hamlet: oh ABSOLUTELY

hamlet for the next four and a half acts:

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(via cametobrazil)

I made some Poe art. On keys. I like them and haven’t posted any art for a while. So, here you go, October.