Why You Should Be Using AI Art Tools Like OpenAI's New Dall-E 3

Thanks to artificial intelligence (AI), your next art project could be much easier. 

OpenAI has launched Dall-E 3, the next version of its text-to-image AI tool. Users can enter a request for an image and adjust the prompt by interacting with ChatGPT. It's one of a growing number of AI-driven apps for making art. 

"AI augments users' creative intuition," Ben James, the CEO of Atlas, a 3D AI art platform, told Lifewire in an email interview. "An artist typically focuses on a singular or limited set of design experiments because of a project's time and budget constraints. AI cuts down on production times for artists, designers, and developers, and does so in a way that keeps creativity at the forefront, enabling a more diverse set of artistic development across all styles—from hyper-realistic to abstract."

Easier and Safer

DALL-E's claim to fame is that it transforms text prompts into images. However, DALL-E 2 had its limitations, frequently overlooking precise wording. According to OpenAI researchers, the most recent version is much better at understanding context.

Another new feature of DALL-E 3 is that it works together with ChatGPT. Users don't have to make their own detailed prompts for DALL-E 3. They can just ask ChatGPT to do it, and the chatbot will create a paragraph for DALL-E 3.

For safety, OpenAI said that DALL-E 3, like DALL-E 2, has filters to prevent it from creating violent, sexual, or hateful content. OpenAI also said it has teamed up with experts to find and lessen possible risks like harmful biases or creating propaganda and misinformation.

"We're also researching the best ways to help people identify when an image was created with AI," the company wrote on its website. "We're experimenting with a provenance classifier—a new internal tool that can help us identify whether or not an image was generated by DALL-E 3—and hope to use this tool to better understand the ways generated images might be used."

The AI Art Revolution

AI is increasingly making its mark in the world of art, creating pieces that can rival human-made creations. AI-generated art employs algorithms and machine learning to generate visual artwork, music, poetry, and more, often producing results that are indistinguishable from works created by human artists. One of the most notable examples is the use of Generative Adversarial Networks (GANs) to create realistic images, including portraits, landscapes, and abstract art.

AI-generated art is also raising ethical and legal questions. The US Copyright Office Review Board recently decided that an AI-generated image called "Théâtre d'Opéra Spatial," which won first place at the 2022 Colorado State Fair Art Competition, could not be copyrighted. The judges said that works made by non-humans can't have copyright protection.

The generative AI industry is rapidly developing, Sergei Belousov, the lead AI / ML research engineer at AI ARTA, said in an email.

"Prompts are now recognized, understood, and processed better and more precisely. Besides, there are several prompt-generating tools now that facilitate the text-to-image work, helping the users transform text requests into AI-approachable prompts," he added. "Many AI image generators provide internal services assisting users with entering their prompts, suggesting ready-to-go drafts or necessary wording to attribute specific styles."

The best AI art tools are those being created with a clear aesthetic focus, such as fine-tuned AI models based on an artist's own work, James said. 

"Within the 2D art space, open source models such as Stable Diffusion are the best tools, and Atlas' technology enables this in 3D," he added. 

AI art generation is highly dependent on computing power, noted tech marketing expert Namanh Hoang in an email. When it first began growing in popularity, even with some of the most powerful computing servers, AI art generation services built on the Stable Diffusion framework could only generate images at a relatively low resolution of 512x512 pixels. 

"Still, as computing power improved, we now see images rendered two to three times larger than before and at half the speed," he added. "Additionally, people are becoming more proficient at understanding how to write better prompts to achieve the results they want."