In 2021, OpenAI achieved a breakthrough with the introduction of DALL-E. Using a dataset of text-image pairs, the 12 billion parameter DALL-E variant of GPT-3 was trained to produce images from textual descriptions. The innovative tool can perform a wide range of tasks, including anthropomorphizing objects and animals, connecting seemingly unrelated ideas, creating language, and altering pre-existing visual effects.

By introducing a new feature called Outpainting, OpenAI has extended the already existing DALL-E. By adding visual components that maintain the same aesthetic to an image beyond its original boundaries, or simply by using a natural language description, this new tool encourages people to use more of their creativity.

Inpainting is a feature of DALLE’s editing feature that allows modifications to be made to a created or uploaded image. To preserve the context of the original image, repainting takes into account the existing visual characteristics of the image, including but not limited to shadows, reflections, and textures. Users can now expand this original image by creating large-scale images in any aspect ratio thanks to repainting.

More than a million people are currently using the innovative DALL-E program, which uses artificial intelligence to create unique visualizations and artwork based on natural language descriptions. With the new Outpainting feature, artists have already created impressive works that have helped the OpenAI team to better understand its capabilities. The Outpainting feature is now available to all DALL-E users in the desktop version.

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Khushboo Gupta is a Consultant Intern at MarktechPost. She is currently pursuing a Bachelor of Technology degree from the Indian Institute of Technology (IIT), Goa. She is passionate about the fields of machine learning, natural language processing and web development. She likes to learn more about the technical field by participating in several challenges.



Heard about DALL·E? Check this new Feature ‘Outpainting’ just added on it which adds Visual Elements simply by using a Natural Language Description

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