Many industrial sectors rely on well-trained employees that are able to operate complex machinery. In this work, we demonstrate an AI-powered immersive assistance system that supports users in performing complex tasks in industrial environments. Specifically, our system leverages a VR environment that resembles a juice mixer setup. This digital twin of a physical setup simulates complex industrial machinery used to mix preparations or liquids (e.g., similar to the pharmaceutical industry) and includes various containers, sensors, pumps, and flow controllers. This setup demonstrates our system's capabilities in a controlled environment while acting as a proof-of-concept for broader industrial applications. The core components of our multimodal AI assistant are a large language model and a speech-to-text model that process a video and audio recording of an expert performing the task in a VR environment. The video and speech input extracted from the expert's video enables it to provide step-by-step guidance to support users in executing complex tasks. This demonstration showcases the potential of our AI-powered assistant to reduce cognitive load, increase productivity, and enhance safety in industrial environments.
EXR: An Interactive Immersive EHR Visualization in Extended Reality
Georgia Institute of Technology（佐治亚理工学院）；Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech & Emory University（佐治亚理工学院生物医学工程系及埃默里大学）；Shriners Hospitals for Children, Headquarters, Tampa, FL（夏普斯儿童医院，总部，佛罗里达州坦帕）；Shriners Hospitals for Children, Philadelphia, PA（夏普斯儿童医院，费城，宾夕法尼亚州）
"Always Nice and Confident, Sometimes Wrong": Developer's Experiences Engaging Large Language Models (LLMs) Versus Human-Powered Q&A Platforms for Coding Support
