GenAI Adoption Strategies for Leaders

The data fabric is a new way to manage and integrate data that promises to unlock the power of data in ways that shatter the limits of previous generations of technology such as data warehouses and data lakes.

Data in its raw form is highly variable in data quality. Sometimes it is well formed and clean. Other times it is sparse and uneven.

The data fabric captures and represent data in all its rich complexity for us to understand what the data means, and deliver it where needed.

Most often engineers utilize 3D models and engineering simulations to develop processes and products; however, it is impossible to translate these models into texts for large language models (LLMs) in order to provide more precise and pertinent responses.

Simply put, the solution lies in Geometric Deep Learning techniques.

Digital twins, which are virtual replicas of physical objects or processes, benefit from GenAI.

Professionals can learn how to enhance digital twins using generative models, enabling better predictive maintenance, optimization, and decision-making.

Learn how digital twin combines the power of real-time data streamed from operating assets and near-real-time high-fidelity system simulations for accurately informed decision making on the fly.

Seamlessly connected through the digital thread, the digital twin provides a holistic view of processes and products from conception till EoL (End of Life). This allows for Remaining Useful Life (RUL) calculations, prescriptive analytics for field assets as well as a platform to provide closed-loop feedback to the operators, product and process designers.

The use cases and customer successes in the adoption of GenAI technologies in the engineering functions and enterprise-wide will be highlighted. The discussion will focus on the economic advantages that early adopters have attained.