Synthetic Reality

Synthetic reality research focuses on creating realistic digital environments and data using AI, primarily to address data scarcity in fields like autonomous driving and surgery. Current efforts leverage generative adversarial networks (GANs), diffusion models, and reinforcement learning techniques like asymmetric self-play to generate high-fidelity images, 3D models, and even entire simulated worlds, often incorporating constraints for real-world applicability. This work is significant because it enables training and testing of AI systems in safe, controlled environments, improving performance and accelerating progress in various domains while also raising important questions about the detection of synthetic media in the context of digital forensics.