A system trained on images from the web may, for instance, be more likely to show one gender over another in particular roles, reflecting deep-seated social biases. The constant flow of DALL-E Mini content also helped the company iron out technical issues, Delangue says, with users flagging problems such as sexually explicit results or biases in the output. But he does not see this as limiting his creativity because DALL-E 2 is still a research project. “Sometimes I forget that there are guardrails, and I have to be reminded with warnings from the app” that state his access could be revoked.
Stevenson says he has run into restrictions programmed in by OpenAI to prevent creation of certain content. “It allows for you to take more risks with your ideas and try out more complicated designs because it supports many iterations.” “I feel like I’m learning a whole new way of creating,” he says. Neither is publicly available.ĭon Allen Stevenson III, one artist with access to OpenAI’s more powerful DALL-E 2, has been using it to riff on ideas and speed up the creation of new artwork, including augmented reality content such as Snapchat filters that turn a person into a cartoon lobster or a Bored Ape-style illustration. This May, Google announced a research system called Imagen that it said is capable of generating images of a quality level similar to DALL-E 2 last week it announced another called Parti, which uses a different technical approach. OpenAI has only provided access to DALL-E and DALL-E 2 to selected users, including artists and computer scientists who are asked to abide by strict rules, an approach the company says will allow it to “learn about the technology’s capabilities and limitations.” Other companies are building their own image-generating tools at a striking pace. The company says it mitigates the risk of misuse by filtering the system’s training data and restricting keywords that could produce undesirable output. OpenAI has said that DALL-E 2 could be more problematic than the original system because it can generate much more convincing images.
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This successor to the original is capable of producing images that resemble photographs and illustrations that look as if they were made by a professional artist. Advances in machine learning could enable many valuable uses for AI-generated imagery, but also malicious use cases such as spreading lies or hate. Even so, users have shared images from prompts that include war crimes, school shootings, and the World Trade Center attack.ĪI-powered image manipulation, including spoof imagery of real people termed deepfakes, has become a concern for AI researchers, lawmakers, and nonprofits that work on online harassment. The system was not trained on explicit content, and it is designed to block certain keywords. Some of those creative prompts have taken DALL-E Mini in questionable directions, however. “It’s really hard to serve these models at scale they had to fix everything.” In recent weeks, DALL-E Mini has been serving up around 50,000 images a day. “Our engineers didn’t sleep for the first night,” says Clément Delangue, CEO of Hugging Face, on a video call from his home in Miami.
Behold its renditions of “ Thanos looking for his mom at Walmart,” “ drunk shirtless guys wandering around Mordor,” “ CCTV camera footage of Darth Vader breakdancing,” and “ a hamster Godzilla in a sombrero attacking Tokyo.”Īs more people created and shared DALL-E Mini images on Twitter and Reddit, and more new users arrived, Hugging Face saw its servers overwhelmed with traffic. But after some recent improvements and a few viral tweets, its ability to crudely sketch all manner of surreal, hilarious, and even nightmarish visions suddenly became meme magic. The outwardly simple app, which generates nine images in response to any typed text prompt, was launched nearly a year ago by an independent developer. On June 6, Hugging Face, a company that hosts open source artificial intelligence projects, saw traffic to an AI image-generation tool called DALL-E Mini skyrocket.
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