The era of physical AI, where embodied AIs powered by world foundation models can understand and interact with industrial facilities based on real-time production data, sensor inputs, and reasoning, is around the corner. 

This new era will transform heavy industries and bring more intelligence, automation, and autonomy to millions of factories, warehouses, and industrial facilities around the world.

Physics-based industrial digital twins bridge the physical and digital worlds and are the key to realizing this opportunity. Different types of digital twins can improve predictive maintenance and reduce production line downtime and can support decision-making in supply chain operations. 

Virtual facilities, connected to physical assets via the Internet of Things and sensor data, serve as the birthplace and proving ground for intelligent facilities. Virtual environments supported by machine learning and 3D models enable the simulation of multi-robot fleets. These fleets, composed of autonomous mobile robots (AMR) and general-purpose humanoid robots, will increasingly fill critical labor gaps and work alongside human workers.

Multiple AI agents may be deployed throughout a facility to help automate processes, assist operators, and ensure worker safety. These AI agents can also provide visibility and insights to analyze how multi-robot fleets and facility workers interact from a holistic viewpoint versus focusing on the performance of singular pieces of equipment or processes.

Artificial intelligence and digital twins are foundational to industrial AI initiatives happening across manufacturing and the industrial sector today. 

Digital twin technology is enabling manufacturers to design, simulate, operate, and optimize physical assets and processes—entirely virtually. This delivers many benefits, including:

Improved communication and decisions: During facility design, construction, and commissioning, visualizations from digital twins support collaboration among project stakeholders and allow teams to make quicker and more informed decisions.

Simulation of ideal layouts: Teams can connect virtual representations to simulation tools to simulate complex scenarios and optimize facility designs for optimal production and material flow, ergonomics, and safety.

Optimization of operations: By integrating digital twins with real-time production data, teams can identify, analyze, and resolve operational issues in real time. They can also delve into the past to root cause issues with enhanced spatial context from virtual models. 

Testing and validation of AI models: AI developers use virtual replicas to test and validate vision language models (VLMs), generative AI, and AI agents to accelerate the adoption of industrial AI and enable new workflows and efficiencies from planning to operations. Visual AI agents connected to live cameras and digital twins can provide valuable outside-in insights on robot-human interactions throughout a facility to enhance safety and productivity.