ThisCatDoesNotExist – Pain In The Bud

After a few days of patiently waiting, we finally have a winner in our unofficial contest from earlier this week.

Reader Romulo Pietrangeli got it right: None of the cats pictured in our April 13 post are real felines.

All nine images were created by the machine learning algorithm that powers the site This Cat Does Not Exist, a riff on the original This Person Does Not Exist, a site that uses generative adversarial networks (GANS) to create stunningly realistic images of people on the fly.

(Above: All six images above are computer-generated using the same technology behind ThisCatDoesNotExist.)

Phillip Wang, the 33-year-old software engineer behind both sites (and a few others using the same tech and concept), explained to Inverse in an earlier interview why he created ThisPersonDoesNotExist.

“I’m basically at the point in my life where I’m going to concede that super-intelligence will be real and I need to devote my remaining life to [it],” Wang said. “The reaction speaks to how much people are in the dark about A.I. and its potential.”

Because the internet is ruled by cats, it was only a matter of time before a feline-generating version of the human-creating algorithm was brought online.

(Above: More artificially-generated cats. Artefacts in the images can sometimes give away the fact that they’re fake, such as the third image in the second row, where part of the cat’s fur is transparent.)

A CNN article from 2019 explains how GAN technology works:

In order to generate such images, StyleGAN makes use of a machine-learning method known as a GAN, or generative adversarial network. GANs consist of two neural networks — which are algorithms modeled on the neurons in a brain — facing off against each other to produce real-looking images of everything from human faces to impressionist paintings. One of the neural networks generates images (of, say, a woman’s face), while the other tries to determine whether that image is a fake or a real face.

Wang, who said his software “dreams up a new face every two seconds,” told CNN he hoped his creations would spark conversation and get people to think critically about what they see in front of them. It looks like he’s achieved his goal.

Christopher Schmidt, a Google engineer who used the same technology to create fake home and rental interiors, agreed.

“Maybe we should all just think an extra couple of seconds before assuming something is real,” Schmidt told CNN.

Pietrangeli, for his part, says he can tell the difference: “All of the animal images,” he wrote, “lacked ‘aura.'”

There’s a new tool that uses algorithmic artificial intelligence to create random images of cats, and the results are virtually indistinguishable from the real thing.

Can you tell which cats are real and which ones are computer-generated? (Kindly share your answers in the comments, numbering them from left to right. The person with the best score gets bragging rights!)

We’ll follow up with the answers after everyone’s had a day to make their guesses or informed choices, as it were.

The algorithm was created by a process called machine learning, which you’ve probably heard at some point even if you haven’t sought out information about artificial intelligence.

In simple terms, machine learning means the creators fed massive amounts of data — millions of photos of cats — to the software algorithm. The algorithm analyzes the data and learns how patterns in the data create accurate images of felines.

Crucially, the algorithm never learns what a cat actually is. It doesn’t know a cat is an animal in the real world. It doesn’t know what the real world is, and it doesn’t know what animals are. All it knows is that data, organized a certain way, produces images that look like the photos it’s been fed.

That’s a key difference because, while we have made huge strides with machine learning, that’s not the kind of artificial intelligence the Elon Musks of the world freak out about when they smoke pot and watch The Matrix. We’ll never have to worry about our cat-generating algorithms rising up and eliminating humanity. 🙂

Artificial general intelligence — or AGI — is the potentially dangerous form of AI, but that’s a whole other piece of business: It involves recreating consciousness and the mind on a machine substrate.

We can’t even define consciousness and we know shockingly little about how the brain works, so that’s not happening any time soon. And even if we could it off, there’s a growing body of evidence supporting the concept of embodied cognition. That’s the idea that the mind cannot be separate from the brain, and the brain cannot be separate from the body, as well as a recognition that everything from pain signals to gut flora has an effect on our cognitive routines.

The bottom line: “AI” can get pretty good at making pictures of cats, but it’s not taking over the world any time soon.