Artificial Intelligence

DALL.E Mini Loves Women in Saree but Creators Can’t Explain Why

Veda

DALL·E mini, an OpenAI program that generates hyper-realistic art and images from text input.

Artificial intelligence has changed the world, solving highly complex mathematical questions and allowing the internet to create images of Yoda and Godzilla playing poker together. DALL·E mini was developed by artificial intelligence artist Boris Dayma and inspired by DALL·E 2, an OpenAI program that generates hyper-realistic art and images from text input. DALL·E mini is an AI model that generates images from any prompt you give! Enter your prompt. Run. Created by Boris Dayma et al. 2021-2022. It is a text-to-image AI software that creates images from your written prompts. DALL·E mini generated portraits of brown-skinned women wearing saris, a type of attire common in South Asia.

DALL.E Mini:

DALL·E is a 12-billion parameter version of GPT-3 trained to generate images from text descriptions, using a dataset of text-image pairs. Dall-E mini takes its name from OpenAI's software Dall-E 2. The team behind this mini version is attempting to replicate OpenAI's results through an open-source model. And it is the creator of these artworks, is a neural network that can take a text phrase and transform it into an image.

DALL·E mini takes thousands of times the blank command input to figure out whether it was just a coincidence. It was trained by looking at millions of images on the internet along with accompanying text and it learned to create pictures of things. The kind of technology that powers DALL·E makes it easier to create fake images.

DALL·E mini is now a viral internet phenomenon. The images it produces aren't nearly as clear as those from DALL·E 2 and have notable distortion and blurring. This software, while impressive, is by no means flawless and can often struggle to produce a perfect image, and in particular, seems to struggle with faces. The new Dall-E mini has no restrictions. While the team has given a disclaimer about biases and imagery.  

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