Physics-informed AI to Accelerate Autonomous Industrial Operations
Geminus is at the forefront of revolutionizing industrial operations through its innovative approach to AI. By integrating physics-based simulations with deep learning, Geminus enables real-time decision-making, significantly reducing the time and resources typically required for achieving return on investment (ROI). This unique combination addresses the limitations of traditional data-driven AI and computationally intensive physics simulations.
Key Features
- Autonomous Systems: Geminus offers self-optimizing and self-healing capabilities that maximize productivity and minimize emissions.
- Model Predictive Control: Evergreen, purpose-built AI models facilitate widespread automation.
- Dynamic System Digital Twins: Fully explorable AI models provide instant what-if scenarios and control recommendations.
Use Cases
Geminus's technology is particularly beneficial in industries where real-time operational decisions are critical. For instance, in energy transition initiatives, Geminus helps accelerate the path to net-zero solutions by optimizing productivity and emissions in complex systems.
Advanced Techniques
- Physics-Informed Models: By using the system’s physics for training, Geminus achieves far better predictions than models relying solely on process data.
- Sparse Data Techniques: These advancements compress the time to value for AI from months or years to just weeks.
Trustworthiness
Geminus models are built on first principles training sources and feature uncertainty quantification, ensuring explainable and trustworthy recommendations.
Partnerships
Geminus collaborates with industry leaders like SLB to transform the energy industry, offering solutions that bridge today’s processes with tomorrow’s net-zero goals.
In summary, Geminus is not just another AI tool; it's a game-changer in the industrial AI landscape, offering a unique blend of physics and machine learning to drive rapid and efficient industrial autonomy.
