But, as Jan Koum has shown, that’s the classic good-is-the-enemy-of-great type of thinking. WhatsApp blew up because it

Growing up in the nineties and the noughties, I loved Pokemon. Pokemon Red was my first and favourite game, and I easily spent hundreds of hours playing it as a kid despite being too dumb to actually beat it. When I wasn’t trying to catch ’em all, I would make up my own little monsters and draw them with all the artistic talent a five year old could muster. Despite this obsession, I had a few qualms with the games. Like, how does one Pokemon suddenly evolve into another; shouldn’t it be a gradual process as they get stronger? And why is it that when you breed two completely different Pokemon together the child is identical to the mother, rather than a freakish combination of both parents? And beyond that, why were there only 151 Pokemon? Fast forward 20 years and that Pokemon nerd found a solution to these problems, in the form of Generative Adversarial Networks (GANs).

In very brief, GANs consist of two networks: a generator which makes the fake images, and a discriminator which tries to discern real from fake images. The two compete in an arms race, both improving over time, with the end goal of having a generator that makes images so real-looking that the discriminator (and you!) has no way to tell which are real and which aren’t.

Last, consider your context. Browsing pornography on a work computer or while using a work-provided VPN—even while quarantined at home—can land you in serious trouble. It’s also not a good idea to involve other people in your private fantasies without their express consent and in an appropriate way. Basically, don’t slide into random DMs or be creepy with your colleagues, and be respectful to the sex workers whose content you partake.

Markuson points out that any website could be dangerous, so use the same scrutiny that you would for a pornographic site. “Users should check if the URL of the website begins with HTTPS and has a padlock icon next to it. If it’s just HTTP, the site is not secure.”

Generative Adversarial Networks, for the uninitiated, are a type of neural network first proposed in 2014 that have revolutionized creative AI. Before their invention, neural network-based methods for image generation resulted in blurry, low-quality pictures, but with the advent of GANs, high-quality high-res image generation was suddenly possible.

The AEGAN architecture (described here), although slower to train than a standard DCGAN, made for much faster convergence. After only 30 epochs across the ~1600 sprites, the output was distinctly pokemon-shaped.

It’s also important to keep a cool head even when handling hot content. “Many consumers of pornography exercise poor judgement while browsing because they’re in an excited state. Biology takes over, and users overlook risks they’d normally pay attention to,” said Shavell. The checkered past of pornographic sites can also set a dangerous expectation that customers should expect some level of shadiness. Shavell recommends being extra cautious, and to listen to warnings from your computer or browser if it detects something untoward.

Here’s a handful of the unfortunate creatures my GAN spit into existence (if you’re on mobile and they look blurry, check them out here instead. All sprites by the author):

In April, I proposed the AutoEncoding Generative Adversarial Network architecture (medium, arxiv), a generalization of CycleGAN, which combines two GANs and two autoencoders. Recently, I thought to myself, “what would happen if I used the AEGAN technique to generate video game sprites using Pokemon as training data?” Let me tell you, some questions are better left unasked.

Despite their obvious deformities, many of these abominations have distinct body segments (arms, legs, heads) and they all have vibrant, diverse colours. Some even have eyes!

Last, consider your context. Browsing pornography on a work computer or while using a work-provided VPN—even while quarantined at home—can land you in serious trouble. It’s also not a good idea to involve other people in your private fantasies without their express consent and in an appropriate way. Basically, don’t slide into random DMs or be creepy with your colleagues, and be respectful to the sex workers whose content you partake.

I’ll be the first to admit that these sprites aren’t exactly game-ready. Still, while working on this project I found a number of tricks that greatly improved the quality of the output, and I’d like to share them here in case you’re interested in applying them yourself (and have access to a bigger dataset…). But before we get to that, here are a few more of my favourite little freaks:

In the games, Pokemon go through two or three distinct forms. Going from one form to the next is an abrupt process, and I always found it disappointing that we can’t watch a Charmander gradually transform into a Charizard as it grows stronger. But, using this AEGAN, we can!

Shavell also warned against using logins for pornographic sites that might be shared on forums or elsewhere. “These simply tend to be teasers to lure people to the worst sort of scam-sites.”

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article, you might like my free newsletter here — I’ll email you (very occasionally!) when there’s a new post. You might also you might enjoy Exponent, the podcast I co-host with Ben Thompson of Stratechery. We talk about this article on episode 190.