Ever since the glorious disaster that was Cambridge Analytica and the entire political climate of 2016, Mark Zuckerberg has been making the rounds from press outlets to private meetings with Republican donors to Congressional testimonies to more private meetings with Republican donors, all with increasing frequency. But he has yet to grant an audience to the Guardian since they broke the initial story with whistleblower testimony.
So naturally, the Guardian enlisted the help of Botnick Studios to create a neural network trained on some 200,000+ words from Zuckerberg's interviews, speeches, and blogposts over the last three years. And they interviewed that instead.
Perhaps unsurprisingly, this "Zuckerbot" sounds about as convincing as the real Zuckerberg — which is to say like an eerily fabricated alien simulacrum of a human being. For example, here's how it describes the purpose of Facebook:
First, I want to thank you all for being a part of my mission. The purpose of Facebook is to bring about internet for people in the digital room. It is about advertising dollars to people who pay to be able to pay. We believe in building $8bn of voice on the platform for dads who are hungry for coffee.
And on his secret meetings with Donald Trump:
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Is anything ever secure? Is anything ever secret? Guess what? The answer is a clear maybe. Or maybe not. I am going to say quiet words in your face just like I did with him and Congress. You can’t expect me to tell you a secret that I didn’t share with him but I am confident that we are sharing the same infrastructure.
The Literary Review in the UK has given out a Bad Sex in Fiction Award since 1993. It's a coveted literary recognition indeed; even Morrissey took the prize home in 2015. While there are some valid critiques about the very existence of the thing— TD Storm at LitHub has argued that the award tends to conflate the author with the narrator, making it "entirely deaf to intent and tone and a passage’s relation to the larger narrative—I find it to be a delightful thing to read aloud with friends and family, particularly after a night of drinking.
(For some reason, my family disagrees, but whatever.)
Twitter user Yves Peirsman had the brilliant idea to take this a step further. He ran this year's nominated passages through the Write with Transformer AI Neural Network, just to see what kind of steamy computer action it would come up with:
I'm genuinely impressed that the computer was able to parse the innuendo and come up with something like "His cock was so hard that it was touching her lips," even when there were no genitals explicitly mentioned in the source passage.
This year's nominees were announced on Wednesday, November 27, with the final award given out on Monday, December 2—but when it comes to bad sex writing, we're all winners in the end. Read the rest
Donald Trump’s desperate PR attempt “speech” from this morning read kind of like the lyric sheet from some obscure Radiohead-wannabe art-rock band.
So naturally, comedian Emily Heller took it to the next level by feeding it into OpenAI’s “Talk To Transformer” Neural Network.
I assumed this was real, but I still wanted to try it out for myself. And wow, the results were not disappointing.
First up: the opening scene to a noir novel. Not quite “shooting someone in the middle of Fifth Avenue and not losing any supporters”-level, but it’s close.
So I tried again. And this time, the Neural Network came out with a straight-up Ramones song.
On my third try, the Artificial Intelligence showed a greater capacity for aspiring towards human emotions than Trump himself ever has.
And this one basically just sounds like Trump talking in his sleep during a wet dream.
As we can see from below, even the Neural Network knows that dozens of women have credibly accused the President of sexual assault.
And finally, this one that … actually just sounds like the way Trump talks on a good day.
You can try to fill-in-the-blanks on your own with OpenAI’s Talk To Transformer neural network. Whatever it is the machine spews out will still probably be more coherent and articulate than anything Trump himself has ever come up with. Read the rest
The theme of this year's Burning Man is I, Robot, which focuses "on the many forms of artificial intelligence that permeate our lives..." So, naturally, someone trained a neural network to come up with some camp names.
It spit out believable names like Spankles, Astro Sparkin, and Space Rock Screamin Camp, as well as weirder names like Corn Viral Hammers, Wiq Renames Spaghette, and Hellball Lounge. Then it went with some truly bizarre ones like Cohnie Stacefur Ass Chaos, Sir Liberains the Wreck Middle, and Awes Orpoop.
The woman behind the experiment, research scientist Janelle Shane, writes:
Thanks to an anonymous burner, I had a list of 1593 past Burning Man camps to feed to a neural network. A neural network is a kind of machine learning algorithm that learns to imitate the data it sees. My starting point was a textgen-rnn neural net that had been previously trained on metal bands and roller derby names, so it had a few ideas of its own to bring to the table. It did not disappoint.
There's a bunch more of these machine-learned camp names over at Shane's site.
Let's hope life imitates art and some Burners out there actually create one (or more) of these camps this year on the playa!
Image via simon of the playa
Thanks, Dan S.! Read the rest
Memo Akten created Gloomy Sunday, part of his Learning To See series in which he juxtaposes mundane video with how deep-trained neural networks percieve the same input. Read the rest
In her delightful blog AI Weirdness, Janelle Shane entered 18,458 unique bills introduced in Massachusetts into a neural network, which then created some rather hilarious bills, including: Read the rest
I don't know about you guys but I can't wait to catch Backwanzus, Bing the Bung, and Lil Hack this year at Coachella. I hear they're going to play all their early stuff.
What...? Botnik Studios (previously) trained its neural network on thousands of band names to generate a completely fake Coachella 2018 lineup?
Oh, yeah, I totally knew that. Read the rest
Single image super-resolution (SISR) is an emerging technology that uses automated texture synthesis to enhance dithered and blurry photos to nearly pristine resolution. This example from EnhanceNet-PAT shows one type. There's even a free website called Let's Enhance where you can up-res your own images. Read the rest
In a first, an artificial intelligence named Libratus has bested top-tier players at no-limit Texas Hold 'em. This is especially notable because imperfect information games are notoriously challenging to program. Read the rest
Today we do something weird, in honor of the end of the second season of Flash Forward! Instead of coming up with a future and then finding experts to talk about it, I asked an AI to write a future for us. And the AI apparently wants us to talk about space travel, witches, and the occult.
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In this episode we feed all the past Flash Forward episodes to a neural network, and ask it to write a script for us. And that script is full of space travel, Mars conspiracy theories, future witches, and a whole lot of theories about cutting someone’s hands off.
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Since Cory posted about the Deep Dream image recognition algorithm last month (and Rob earlier today) it's inspired an explosion of iterations like Roelof Pieters' DeepDreamed Fear & Loathing in Las Vegas. Read the rest