This AI is like Google Image Search For Imaginary Pictures


In case you were wondering, the image above is “an intricate drawing of eternity”. But this is not the work of a human artist; it’s the creation of BigSleep, the latest stunning example of generative artificial intelligence (AI) in action.

Much like a visual version of the GPT-3 text-generating AI model, BigSleep is able to take any text prompt and visualize an image suitable for words. It could be something esoteric like eternity, or it could be a bowl of cherries or a beautiful house (the latter can be seen below.) Think of it like a Google Images search – only for images that never existed before.

How BigSleep works

“At a high level, BigSleep works by combining two neural networks: BigGAN and CLIP,” 23-year-old BigSleep creator Ryan Murdock, a cognitive neuroscience student at the University of Utah, told Digital Trends.

The first of these, BigGAN, is a system created by Google that takes random noise into account and produces images. BigGAN is a generative adversarial network: a pair of dueling neural networks that perform what Murdock calls an “antagonistic tussle” between an image-generating network and a discriminator network. Over time, the interaction between the generator and the discriminator results in improvements to both neural networks.

Pretty house
A “beautiful house”, according to BigSleep. I mean, it’s not wrong. BigSleep

CLIP, on the other hand, is a neural network created by OpenAI that learned to match images and descriptions. Give CLIP text and images, and it will attempt to determine how well they match and score them accordingly.

Combining the two, Murdock explained that BigSleep searches BigGAN outputs for images that maximize CLIP’s rating. It then slowly adjusts the noise input to the BigGAN generator until CLIP indicates that the images produced match the description. Generating an image corresponding to a prompt takes about three minutes in total.

“BigSleep is important because it can generate a wide variety of concepts and objects quite well at 512 x 512 pixel resolution,” Murdock said. “Previous work has produced impressive results, but to my knowledge much of it has been limited to lower resolution images and more everyday objects.”

AI generating images

BigSleep isn’t the first time AI has been used to generate images. Its name recalls DeepDream, an AI created by Google engineer Alex Mordvintsev that creates psychedelic images using classification models. A GAN-based system was also used to create the AI ​​painting that sold at auction in 2018 for a whopping $432,500. However, it is certainly a fascinating step forward.

To try BigSleep for yourself, Murdock suggested checking out his Google Colab notebook about the project. There’s a bit of a learning curve involving using the Colab GUI and a few other steps, but it’s free. Other ways to test it should also open up in the coming weeks. If you’re interested, you can also visit r/MediaSynthesis, where users post some of the best images they’ve generated with the system so far.

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Michael C. Garrison