AI-generated images are making their way into various creative fields, from popular video games to museum displays. This trend is possible due to a range of innovative generative AI technologies that empower computers to produce lifelike visuals.
But on the other hand, this trend has stirred up some controversy by posing a threat to creative jobs and artistic freedoms. Critics argue that these tools might infringe on existing copyrighted works, raising ethical concerns and potential legal issues. So, what’s the deal with AI-generated art, and how does it actually operate? Let’s dive into the details.
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AI-generated art explained
AI-generated art encompasses digital artwork made with the assistance of artificial intelligence, whether entirely or partially. Thanks to recent advancements, tools like Midjourney, Stable Diffusion, and DALL-E allow anyone to delve into AI art creation. The entry barrier is lower compared to traditional art forms. Nevertheless, achieving optimal results still demands a certain level of creativity, as we’ll delve into later in this article.
Just a couple of years back, computers could only whip up pretty basic art from scratch. But then, enter generative AI, and everything flipped. It enabled computers to recreate super detailed stuff, like hair and grass, for the very first time. The outcomes are so mind-blowing that even the pros might have a hard time spotting if what they’re seeing is entirely synthetic and digital.
AI-generated art isn’t just about standalone pieces. It’s also making its mark selectively. Smartphone manufacturers have hopped on the bandwagon by incorporating generative AI features into their photo editing apps. For instance, on recent Pixel phones, Magic Editor lets you shift subjects in a scene, and Samsung’s Galaxy AI can stretch images beyond their original size. Similarly, Photoshop’s Generative Fill feature can introduce new elements into existing photos.
Generative Fill is a fresh AI feature in Photoshop that can craft entirely new visuals using a straightforward text prompt. Plus, in certain situations, like when you’re looking to expand an original image, you don’t even have to input a prompt. If you’re savvy with Photoshop, you’ve probably heard of the Context-Aware Fill tool. It’s handy for removing unwanted stuff like people or power lines in photos, but it relies on somewhat guessy methods to fill in the background. Now, enter Generative Fill – this uses machine learning and nails down incredibly convincing results.
So, Photoshop’s Generative Fill gets its juice from Adobe Firefly, a bunch of machine learning models trained on millions of Adobe’s own stock images and other public domain content. Basically, you won’t have to stress about AI tossing someone else’s copyrighted material into your photos. But hold your horses, Adobe isn’t dishing out commercial rights to its AI creations just yet.
In just a few short years since its introduction, AI art has proven its worth in the business world. Numerous video game developers, advertisers, and fashion brands have either embraced or dabbled in this technology. The advantages are evident: when compared to humans, artificial art can significantly accelerate development timelines and dramatically reduce costs.
How is AI art created?
AI image generators work by using algorithms powered by artificial intelligence. These algorithms sift through countless text-image pairs across various categories. Throughout this training phase, the algorithm grasps how to identify patterns in images and establish connections between captions and images. While this is a time-consuming process, it doesn’t demand much human supervision.
Over the years, researchers have devised various machine learning methods to uncover connections between text and images. Yet, if you look at the top-notch AI image generators today, many are driven by diffusion models. These models inject random Gaussian noise into images within their training dataset. Afterward, they try to reverse the process to recreate the original image. Gradually, the AI model gets the hang of generating completely new art from a realm of visual chaos.
Modern AI image generators not only use diffusion models but also team them up with a hefty language model. If that rings a bell, it’s the same tech that powers contemporary chatbots like ChatGPT. This essentially enables the machine to understand prompts based on text.
It’s important to mention that all the technical stuff happens in the background. To create AI-generated art, you just type a few words into an online tool like Midjourney or Meta Imagine and see what comes out. In a matter of seconds, you’ll have a selection of images to pick from. But here’s the catch: the quality of these results entirely hinges on what you input—a vague or poorly described prompt won’t get you stellar outcomes.
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Tools used for creating AI art
You might think big players like Adobe, Meta, and Google would dominate the AI art scene, but surprisingly, smaller startups and even open-source projects are stealing the spotlight, at least for now. Let’s check out the top AI art generators and what sets each one apart:
Midjourney stands out from the rest on this list because, unlike most others, it’s not supported by a big tech giant. However, it’s still considered one of the top AI image generators, known for cranking out incredibly realistic artwork.
DALL-E, built on the same basic structure as ChatGPT, gave us an early peek into AI-generated art in 2021. While it faced some competition from Midjourney for a while, the latest release, DALL-E 3, puts it back in the game competitively.
Meta Imagine, a relatively fresh addition to the image creation scene, taps into millions of publicly shared images from Facebook and Instagram. Unlike Midjourney and DALL-E, it’s free to use, though it comes with a small watermark. Leveraging its social media-centered training data, it impressively crafts art featuring human subjects with a high degree of accuracy.
Stable Diffusion has a major plus—it’s free and open source, so you can run it on your own powerful hardware. However, in our face-off between Midjourney and Stable Diffusion, the latter didn’t always measure up. The catch is that Stable Diffusion has a bit of a learning curve and demands spot-on prompts for optimal results.
Besides these specialized AI image generators, many new smartphones come equipped with features that integrate AI art. And in the next few months, we can expect similar features to be added to everyday apps like PowerPoint.
