Rabbis, pastors, and other faith leaders were arrested while protesting Attorney General Jeff Sessions’ visit to Los Angeles. (Full text article)
In the article there’s a quote from one of the police officers that he hated having to arrest religious leaders. He said that “arresting faith leaders wasn’t easy” for him.
Like… good. Maybe consider that, when your job involves arresting clergy who feel morally compelled to peacefully protest racist immigration policies, you MIGHT just be on the wrong side of justice.
If you’ve been on the internet today, you’ve probably interacted with a neural network. They’re a type of machine learning algorithm that’s used for everything from language translation to finance modeling. One of their specialties is image recognition. Several companies – including Google, Microsoft, IBM, and Facebook – have their own algorithms for labeling photos. But image recognition algorithms can make really bizarre mistakes.
It also tagged sheep in this image. I happen to know there were sheep nearby. But none actually present.
Here’s one more example. In fact, the neural network hallucinated sheep every time it saw a landscape of this type. What’s going on here?
The way neural networks learn is by looking at lots of examples. In this case, its trainers gave it lots of images that humans had labeled by hand – and lots of those images contained sheep. Starting with no knowledge at all of what it was seeing, the neural network had to make up rules about which images should be labeled “sheep”. And it looks like it hasn’t realized that “sheep” means the actual animal, not just a sort of treeless grassiness. (Similarly, it labeled the second image with “rainbow” likely because it was wet and rainy, not realizing that the band of colors is essential).
Are neural networks just hyper-vigilant, finding sheep everywhere? No, as it turns out. They only see sheep where they expect to see them. They can find sheep easily in fields and mountainsides, but as soon as sheep start showing up in weird places, it becomes obvious how much the algorithms rely on guessing and probabilities.
Bring sheep indoors, and they’re labeled as cats. Pick up a sheep (or a goat) in your arms, and they’re labeled as dogs.
Paint them orange, and they become flowers.
Put the sheep on leashes, and they’re labeled as dogs. Put them in cars, and they’re dogs or cats. If they’re in the water, they could end up being labeled as birds or even polar bears.
And if goats climb trees, they become birds. Or possibly giraffes. (It turns out that Microsoft Azure is somewhat notorious for seeing giraffes everywhere due to a rumored overabundance of giraffes in the original dataset)
The thing is, neural networks match patterns. They see patches of furlike texture, a bunch of green, and conclude that there are sheep. If they see fur and kitchen shapes, it may conclude instead that there are cats.
If life plays by the rules, image recognition works well. But as soon as people – or sheep – do something unexpected, the algorithms show their weaknesses.
Want to sneak something past a neural network? In a delightfully cyberpunk twist, surrealism might be the answer. Maybe future secret agents will dress in chicken costumes, or drive cow-spotted cars.
And you can test Microsoft Azure’s image recognition API and see for yourself that even top-notch algorithms are relying on probability and luck. Another algorithm, NeuralTalk2, is the one I mostly used for the Twitter thread.
I legitimately cannot stop laughing at these pathetic little fake geek boy sacks of shit who’ve never read a single comic book in their entire sad little lives here
Kate Kane has been openly and canonically lesbian since the first issue of the first series she ever appeared in and yet the horse-fiddling goat botherer in the above tweet seriously wants to try and claim that she “Never revealed anything that would indicate she was a lesbian”
There’s genuinely nothing more pathetic than fake geek boys pretending they know jack shit about superhero fiction
Also as a queer woman I’m happy to be “Exploited for ratings” if that means representation of openly lesbian heroes portrayed positively in tv shows
All I care about is seeing more heroes like me on television. If networks like the CW want to “exploit” that for ratings then I am more than okay with it as long as it means I get what I’m after
Wooooooow. It’s like all those straight people who don’t know Deadpool has been pansexual for years, and that Wonder Woman has been bi since the beginning.
Also, that dude asking if she’s a porn character, he totally just gave away that all he knows about her is from that Justice League XXX parody.
“How is someone’s sexuality relevant to the character”
Ah yes, Kate Kane
The first character in comics history whose sexuality was relevant to their character
Because it’s not like Batman, Superman, Spiderman, Hawkeye, Captain America, Tony Stark etc etc all had long running romantic subplots about what woman they were currently dating/wanted to date or anything
And of course there’s no way at all that Arrow and The Flash both had season-long story arcs ALL ABOUT the romantic lives of their straight male protagonists and their romantic feelings for female characters on the show, to the point that a major crossover event was based entirely around a wedding
Nope, Batwoman is the FIRST TIME EVER that a comic book characters sexuality has had ANY EFFECT AT ALL on the stories written about them according to the “Logic” of this basement dwelling professional troll whose probably already spent the money Breitbart paid them on anime love pillows and meth
“Hey guys! Batwoman is HELLA GAY!” was DC’s selling point to the public before then even launched the comic.
These are from a wonderful book called The Art Of Comforting. Check it out and learn how to be better at supporting people going through difficult things.
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