AI art is a form of digital art where the primary input involves entering a series of prompts into a generator tool to get the desired result.
It differs from other types of digital art where artists may scan or draw using a tablet and can include a number of techniques including digital drawings, photos and videos. This type of art can be fully realized using a digital medium, or by editing physical artworks.
AI art generators refers to the programs that create AI art and includes both text-to-image prompts and image-to-image where an existing image is modified. AI art output is generated by the program’s training whereby existing art is used to help an AI art generator distinguish between styles and techniques.The AI art generator will use what it learned to make new images or paintings based on those styles. It combines the patterns it learned with its own creativity to make unique artwork.
Midjourney is one of the most popular tools for art generation, and one of the easiest for beginners. Unlike for text generation, elaborate prompts aren’t necessarily better for image generation. Your style keyword may refer to a genre, art movement, technique, artist or specific work.
AI art generators take a text prompt and, as best they can, turn it into a matching image. Since your prompt can be anything, the first thing all these apps have to do is attempt to understand what you're asking. To do this, the AI algorithms are trained on hundreds of thousands, millions, or even billions of image-text pairs. This allows them to learn the difference between dogs and cats, Vermeers and Picassos, and everything else. Different art generators have different levels of understanding of complex text, depending on the size of their training database, and some models are trained for specific purposes or only using licensed content, which affects the kinds of things they can generate.
The next step for the AI is to actually render the resulting image. There are two leading kinds of models:
Diffusion models, like Stable Diffusion, DALL·E 2, Midjourney, and CLIP-Guided Diffusion, which work by starting with a random field of noise, and then editing it in a series of steps to match its understanding of the prompt.
Generative Adversarial Networks (GANs), like VQGAN-CLIP, BigGAN, and StyleGAN, which have been around for a few years longer.
Both kinds of models can produce great, realistic results, though diffusion models are generally better at producing weird or wild images.
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