3/18/2024 0 Comments Text message cliff art![]() “It's really just been an incredible time of discovery,” says David Holz, CEO of AI art startup Midjourney, of the past year. “Most startling is the realization of how much further the technology can still go. In September, OpenAI made its own tool available to anyone. And several companies made AI image generators similar in power to DALL-E 2 available to anyone to use. In June 2022, an independent project inspired by OpenAI’s work, now known as Craiyon, became an online sensation as users competed to produce ever-more surreal or comical images. When this kind of system is trained on material scraped from the web it generally learns to produce sexual imagery and picks up historical biases in how it depicts people of different races and genders.īut it didn’t take long for image generators to become widely available. OpenAI’s image generators were originally made available only to select people, in part out of concern they would be abused. That’s when Ian Goodfellow, then a student at the University of Montreal, came up with a new approach to generative models called generative adversarial networks (GANs). Generative models have been used in statistics for decades, but last year's AI image-making bonanza has its roots in an invention from 2014. The commercial potential of so-called generative AI has sparked excitement among tech investors. As well as making images, this approach can be used to write text, compose music, or answer questions. At the core is what’s called a “generative model,” which learns the properties of a collection of data and can then create new data that statistically fits in with the original collection. Algorithms that have digested huge numbers of images and associated text from the web can generate new images from text provided by a user. Image-making AI tools flip this image-labeling trick on its head. This is how Apple Photos and Google Photos can automatically organize pictures of pets taken on a smartphone. In particular, about 10 years ago researchers found that feeding algorithms called neural networks huge numbers of images with associated labels enabled them to label previously unseen images with high accuracy. The image-generation technology capturing the attention of entrepreneurs and artists is built on decades of advances in AI. The clips aren't flawless, but comparing them with examples from the years of research leading up to 2022’s AI art explosion provides a visual timeline of a technology maturing rapidly from lab experiment to product prototype. Researchers continue to refine the technology. WIRED recently got to experiment with one of the first AI tools capable of generating video, developed by researchers at Meta. That rapid progress set entrepreneurs racing to build products and companies around AI image generators. The quality of illustrations, photographs, and paintings that can be made that way improved remarkably. Some commercial artists are experimenting with the technology-although not all like it-and stock photo services are preparing to offer AI generated images. ![]() In the space of a few months last year, several powerful tools for creating art with AI just by typing in a few words became widely available. It used to be widely thought that creative work would be one of the last things to be automated.
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