Generative Artificial Intelligence
Generative Artificial Intelligence (GenAI) focuses on creating new data samples—text, images, code, etc.—from existing datasets using deep learning models. Current research emphasizes diverse applications, including drug discovery, education, and industrial processes, with a focus on model architectures like transformers, diffusion models, and generative adversarial networks (GANs). The field's significance lies in its potential to automate complex tasks, accelerate scientific discovery, and reshape various industries, while also raising important ethical considerations regarding bias, data privacy, and the responsible use of AI.
Papers
Peering into the Mind of Language Models: An Approach for Attribution in Contextual Question Answering
Anirudh Phukan, Shwetha Somasundaram, Apoorv Saxena, Koustava Goswami, Balaji Vasan Srinivasan
Generative AI Enhances Team Performance and Reduces Need for Traditional Teams
Ning Li, Huaikang Zhou, Kris Mikel-Hong