PyTorch Conference 2024

At roboMUA we're leading the charge in building predictive AI models for diverse skin shades with the use of Convolutional Neural Networks (CNNs), and harnessing the power of Generative Adversarial Networks (GANs) specifically for generating realistic images of black hairstyles. Our session showcases PyTorch's versatility in both predictive and generative tasks, offering a comprehensive approach to inclusive AI. For predictive AI models, we leverage PyTorch's flexible framework to develop CNNs. Through innovative techniques in feature engineering and model architecture design, we demonstrate how PyTorch enables accurate prediction across 100 skin shades. Simultaneously, we showcase the transformative potential of GANs in the realm of black hairstyles. By training GANs on a curated dataset of diverse hair textures and styles, we illustrate how PyTorch facilitates the generation of lifelike images that celebrate the beauty and diversity of black hair. Attendees will gain insights into the data preprocessing, model training, and evaluation processes and and learn how PyTorch empowers developers to build inclusive solutions.