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
April 15, 2024
April 14, 2024
April 13, 2024
April 10, 2024
April 4, 2024
April 2, 2024
April 1, 2024
March 31, 2024
March 30, 2024
Generative AI Models for Different Steps in Architectural Design: A Literature Review
Chengyuan Li, Tianyu Zhang, Xusheng Du, Ye Zhang, Haoran Xie
Exploring Unseen Environments with Robots using Large Language and Vision Models through a Procedurally Generated 3D Scene Representation
Arjun P S, Andrew Melnik, Gora Chand Nandi
March 29, 2024
March 28, 2024
March 26, 2024
March 22, 2024
March 19, 2024
March 18, 2024
March 15, 2024