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Geek Girl in Training

@geekgirlintraining / geekgirlintraining.tumblr.com

Not sure I'm geeky enough just yet, but I'm working on it.
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spacehomos

Confess and get the fuck out

You know what? It’s funny and all, but there’s a pretty profound reminder hidden in here. 

“No need to explain why you did it.”

Because why you did it doesn’t matter. What matters is that you did it and it was bad.

God doesn’t want to hear that you thought your sexist joke was hilarious and it’s not your fault that Cindy didn’t get it! God wants to hear that you told a sexist joke, Frank, and how are you going to do better next time?!

And Cindy doesn’t really want to hear why you told that terrible joke either! She wants you to acknowledge that you did it and not do it again!

Any time any of us finds ourselves having to apologize for something we did that harmed someone else, we should pretend we’re going into this confessional.

Intent < Impact

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the wildest thing happened to me the other day i found out a male coworker is into irish music so i told him that my dad is an irish musician and would he like to come to a session and he straight up irl said to me “name 5 irish songs your dad knows”

he asked me if i play and i told him i played the fiddle when i was a teenager but havent played in years and he was like “oh cool. i play drums” as in a drum kit you know the famously folkish instrument the drum kit. bitch my name is molly o'reilly you really wanna challenge the legitimacy of my irish music involvement

i can name 5 songs with my name in them

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aiweirdness

This AI is bad at drawing but will try anyways.

There was a paper recently where a research team trained a machine learning algorithm (a GAN they called AttnGAN) to generate pictures based on written descriptions. It’s like Visual Chatbot in reverse. When it was just trained to generate pictures of birds, it did pretty well, actually. 

(Although the description didn’t specify a beak and so it just… left it out.)

But when they trained the same algorithm on a huge and highly varied dataset, it had a lot more trouble generating a picture to go with that caption. Below, I give the same caption to a version of their algorithm that has been trained to generate everything from sheep to shopping centers. Cris Valenzuela wrapped their trained model in an entertaining demo that attempts to generate a picture for any caption.

This bird is less, um, recognizable. When the GAN has to draw *anything* I ask for, there’s just too much to keep track of - the problem’s too broad, and the algorithm spreads itself too thin. It doesn’t just have trouble with birds. A GAN that’s been trained just on celebrity faces will tend to produce photorealistic portraits. But this one, however…

In fact, it does a horrifying job with humans because it can never quite seem to get the number of orifices correct.

It’s fun to ask it to draw animals though. It knows the texture of giraffes, but not quite exactly their shape. And it knows that boats are on the water, but not necessarily that they are boats.

It also (like many other image recognition algorithms) gets a bit confused about the difference between sheep and the landscapes they’re found on. Other algorithms recognize sheep in pictures of empty green fields. And this one, when asked to draw sheep…

That’s different, though, from asking it to draw *a* sheep. In that case, it knows exactly what to do. It draws the sheep, and then just to be safe it fills the entire planet with wool too.

It really likes drawing stop signs and clocks. Give it the slightest opportunity to draw one, and it will chuck those things all over the place.

Other than its horrifying humans, this algorithm can actually be pretty delightful. 

I had way too much fun generating these and ended up with way more than would fit in this one blog post. I’ve compiled a few more of my favorites. Enter your email and I’ll send you them (and if you want, you can get bonus material each time I post).

For later.

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dannypinot

Captain Janeway (voiceover): “We’ve finally located what’s left of Commander Chakotay’s shuttle… me: We’re barely in Season 4, and they’ve lost at least 1 shuttle per episode so far. Is this ship equipped with unlimited shuttles?? Answer:

You see, when you lose a shuttle, the Shuttle Fairy will come and deliver a shiny new one to you if you leave some milk and cookies out for her in the shuttle bay.

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Star Trek + Social Commentary (context in the captions)

THIS is what the original Star Trek TV series and films were about. Not just about blowing up things in space and snazzy lens flares with a side order of casual sexism -.-‘.

dude do you know how many people I have pissed off by saying the exact same thing?

Not enough people.

This what all good Sci-Fi is about.

Lets hope the new series picks up themes like this.

But hey, “no reason to be an sjw” or anything, right? 🙄 I mean, “why is this new trek pushing liberal politics!? Old trek never did!!!” 😂

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