Now anyone can sign up to use the AI image service.
Over the last few months, OpenAI’s artificial intelligence-powered image generation service DALL-E has been making headlines thanks to its uncanny ability to generate all kinds of images from nothing but a text prompt. DALL-E’s skill in creating images from scratch has drummed up both interest and controversy, but starting this week, it stands to generate a lot more of both as access to it grows.
OpenAI announced this week that they have officially ended their waitlist policy for the use of DALL-E 2. Previously, anyone wishing to use the service, which is currently in a beta period, needed to sign up for the waitlist and wait their turn, but now anyone can sign up and use it freely.
“More than 1.5 million users are now actively creating over 2 million images a day with DALL-E — from artists and creative directors to authors and architects — with about 100,000 users sharing their creations and feedback in our Discord community,” OpenAI wrote in a blog post. “Learning from real-world use has allowed us to improve our safety systems, making wider availability possible today.”
DALL-E will continue to use its credit-based pricing system for generating images. To be specific, users receive a set number of credits that can be used to generate images, and they need to pay if they want to make more.
OpenAI’s image generator DALL-E is available for anyone to use immediately https://t.co/d6L6NuYmmM pic.twitter.com/7hL3DJ2vAv
— The Verge (@verge) September 28, 2022
One of the sticking points for analysts of this technology has been the potential for harmful, dangerous imagery, but OpenAI has made preventing those kinds of images from generating a priority. “In the past months, we have made our filters more robust at rejecting attempts to generate sexual, violent and other content that violates our content policy, and building new detection and response techniques to stop misuse,” the company wrote. “Responsibly scaling a system as powerful and complex as DALL-E — while learning about all the creative ways it can be used and misused — has required an iterative deployment approach.”