Generative AI has come a long way, with modern systems now capable of creating incredibly realistic images, However, a significant limitation of text-to-image AI models has been their struggle to generate legible text, logos, calligraphy, or fonts. Enter DeepFloyd IF, a game-changing model that's set to revolutionize the world of generative AI art.
Developed by research group DeepFloyd, backed by Stability AI, DeepFloyd IF is a text-to-image model that "smartly" incorporates text into images. Trained on a dataset of over a billion images and texts, the model requires a GPU with at least 16GB of RAM to function. The open-source model is currently licensed for non-commercial use, likely due to the legal challenges surrounding generative AI art models.
NightCafe, a generative art platform, was granted early access to DeepFloyd IF. In an interview with TechCrunch, NightCafe CEO Angus Russell discussed the model's key differentiators and the potential impact on generative AI.
DeepFloyd IF's design was heavily influenced by Google's unreleased Imagen model. Unlike competitors such as OpenAI's DALL-E 2 and Stable Diffusion, DeepFloyd IF employs a modular architecture that stacks multiple processes together to generate images. It uses a unique multi-step diffusion process, working directly with pixels.
One of the model's most significant advancements is its ability to understand and represent prompts as a vector, a basic data structure, using a large language model. This feature enables DeepFloyd IF to comprehend complex prompts, spatial relationships, and generate legible, correctly spelled text in multiple languages.
DeepFloyd IF's prowess in generating text within images is expected to unleash a wave of new generative art possibilities, including logo design, web design, posters, billboards, and even memes. It may also lead to better results in creating hands and text in other languages.
While DeepFloyd IF is a significant leap forward in text-to-image models, it's not without flaws. Issues like potential biases, stereotyping, and harmful use cases, such as generating inappropriate content, are shared concerns among generative AI models. However, the DeepFloyd team has acknowledged these challenges and implemented custom filters to eliminate unsuitable content from the training data.
As DeepFloyd IF gains traction, its transformative impact on the world of generative AI art will become increasingly evident, unlocking a realm of creative possibilities for artists and enthusiasts alike.
