The Digital Twin Consortium (DTC) announced that its members are developing and deploying Multi-Agent GenAI Systems (MAGS) that are redefining the boundaries of how product, service and process design can be realized, born from efficiency and optimization. Use cases include automotive, infrastructure and manufacturing where MAGS is used to significantly increase productivity, streamline operations and maximize efficiency.
Digital twins provide an advanced level of automation using GEN AI, not only by integrating co-pilots, but now by using MAGS to perform multiple tasks that either operate independently, self-organize, optimize, and are organized—whether with a traditional human in the loop or without it for human-supervised decision-making that is free from common repetitive routine activities.
MAGS consist of several interacting GenAI-based agents that perform different tasks, often in parallel. MAGS can now provide decentralized, autonomous, self-organizing and self-optimizing capabilities. Through mutual interaction and interaction with the environment, agents can independently achieve individual or collective goals through reflection, memorization, and continuous improvement.
With Gen AI, each agent can perceive its environment, including multiple modalities, make decisions and act independently, while coordinating and communicating with other agents that may or may not be organized/directed. Key attributes of digital twin-based MAGS include interaction, coordination and control, memorization, reflection, and execution.
The Digital Twin Consortium is the authority on digital twins. It brings together industry, government and academia to achieve consistency in the vocabulary, architecture, security and interoperability of digital twin technology. It is developing digital twin technology in many industries, from aerospace to natural resources.
More information about the Digital Twin Consortium can be found at www.digitaltwinconsortium.org.
Source: www.cad.cz
