In late winter of 1975, a scrap of paper started appearing on bulletin boards around the San Francisco Peninsula. “Are you building your own computer?” it asked. “Or some other digital black-magic box? If so, you might like to come to a gathering.”

The invite drew 32 people to a Menlo Park, California, garage for the first meeting of the Homebrew Computer Club, a community of hobbyists intrigued by the potential of a newly affordable component called the microprocessor. One was a young engineer named Steve Wozniak, who later brought a friend named Steve Jobs into the club. “It was a demonstration that individuals could make technological progress and that it doesn’t all have to happen at big companies and universities,” says Len Shustek, a retired entrepreneur who was also in the garage that first night. “Now the same thing is happening for artificial intelligence.”

December 2018. Subscribe to WIRED. Axis of Strength

Since 2012, computers have become dramatically better at understanding speech and images, thanks to a once obscure technology called artificial neural networks. True mastery of this AI technique requires powerful computers, years of research experience, and a yen for deep math. If you have all those things, congratulations: Chances are you’re already a well-remunerated employee of Amazon, Facebook, Google, or the other select few giants vying to shape the world with their massively complicated AI strategies.

Yet the battle for AI supremacy also has littered the ground with tools and spare parts that anyone can pick up. To draw in top-flight scientists and app developers, tech giants have released some of their in-house AI-building toolkits for free, along with some of their research. Hackers and hobbyists are now playing with nearly the same technology that’s driving Silicon Valley’s wildest dreams. “High school students can now do things that the best researchers in the world could not have done a few years ago,” says Andrew Ng, an AI researcher and entrepreneur who has led big projects at Google and China’s Baidu.

People like Ng have big hopes for the amateur AI explosion: They want it to spread the technology’s potential far from Silicon Valley, physically and culturally, to see what happens when tech outsiders “train” neural networks according to their own priorities and ways of seeing the world. Ng likes to imagine that one day a person in India might use what they learn in online videos about AI to make their local water safer to drink.

Of course, not every DIY neural network will be quite so G-rated. Late last year, a Reddit account posted a pornographic video that seemed to star Wonder Woman’s Gal Gadot. The clip circulated around Reddit’s seamier corners and beyond to adult-video sites. But attentive viewers noticed that Gadot’s face occasionally flickered or slipped on her head like a loose mask. The poster explained that the clip was fake, created by training a neural network to generate images of Gadot’s face that matched the expressions of the video’s original star. They then released the code and methodology online so anyone could make similar “deepfake” clips of their own.

So the age of homebrew AI may not be all sweetness and light. Nor will it be all darkness and porn. Mostly, its expressions will be marvelous in their specificity. Meet some of the pioneers showing what happens when the masses can teach computers new tricks.

Self-taught coder Robbie Barrat tapped into the power of AI for art’s sake—generating hip hop rhymes and designing off-kilter fashion. Peter Prato

I’mma Let This Neural Network Finish My Lyrics

When Robbie Barrat was in middle school in rural West Virginia, he started scavenging old computers from a local recycling center, ripping them apart, and putting them back together again. Then he taught himself to code on his family’s farm. He took up AI in high school after he got into an argument with friends over whether computers could be creative. Barrat’s retort was to teach a neural net to rap by training it on the lyrics of Kanye West. (Sample couplet: “I’mma need a fix, girl you was celebrating / Mayonnaise colored Benz I get my engine revving.”) At school, Barrat’s friends loved it, but some adults were shocked. “The teacher got a little bit upset because the neural network was extremely profane,” he says.

This AI-generated nude portrait resulted in "surreal blobs of flesh," says Robbie Barrat of his project. "Is this how machines see people?" Robbie Barrat

That foul-mouthed AI system proved to be Barrat’s ticket off the farm. His grades weren’t good enough to get into the schools where he’d hoped to study math or computer science. But the project helped him land an internship with a self-driving-car project in the heart of Silicon Valley. From there he moved to Stanford University, where he now works in a biomedical lab, trying to develop neural networks that can identify molecules with medicinal potential. But training neural networks to make art is still his passion.

These days, in his spare time, Barrat uses video clips and photos from fashion shows to produce AI-generated images of models wearing new outfits. The results are smeary, glitch-­ridden, and weird—ever thought you’d like pants with a bag wrapped around the lower leg, or a sweater with a giant pouch hanging from one side?—but Barrat is working with a designer to translate them into real clothes. He can’t wait to try them on.

Now a freshman in computer science at the University of Georgia, Shaza Mehdi trained a neural network to identify plant diseases on sight. Irina Rozovsky

Diagnosing Botanical Ailments? There’s an App for That

The rosebushes in Shaza Mehdi’s front yard are beautiful but prone to sickness. One day last year, Mehdi, a fan of Star Trek, asked herself why her phone couldn’t function like a tricorder to diagnose the plants’ afflictions. “How would a computer be able to know?” wondered the high school senior from Lawrenceville, Georgia. Soon she, together with a friend named Nile Ravenell, was tinkering with neural networks between going to class, getting her nails done, and hanging out at the Waffle House near her school.