Introduction
Nuclear vitality ranks among the many world’s most regulated industries. AI and particularly generative AI have created sufficient impression that thought leaders rank it amongst different transformative “basic objective applied sciences” equivalent to electrical energy and the steam engine. Harnessing AI to reimagine nuclear operations throughout the business means extra carbon-free nuclear vitality for electrical grids and knowledge facilities, which the Worldwide Power Company estimates demand to double by 2026. In September 2024, Westinghouse unveiled its HiVE™ AI system, powered by its fine-tuned bertha™ generative AI mannequin, remodeling how clients collaborate with Westinghouse.
Constructing a Higher Knowledge Administration Answer
Westinghouse’s digital transformation began greater than 5 years in the past with a deep bench of information and nuclear specialists and over 70 years’ price of cleaned and contextualized industrial knowledge distinctive to the nuclear world. Nevertheless, the workforce wanted to enhance the corporate’s knowledge infrastructure if it wished to understand its AI ambitions. The present on-premises analytics database lacked some vital scalability options and choices. With no scalable cloud resolution, the information workforce struggled with a scarcity of computing assets, an lack of ability to quickly experiment with large quantities of information, and restrictions on safely sharing knowledge throughout purposes.
To construct a world-class, nuclear-specific AI functionality, Westinghouse wanted a greater resolution. Westinghouse determined to construct on the Databricks Knowledge Intelligence Platform, a transfer that may show essential in its mission to drive innovation. The nuclear business has all the time been deeply dedicated to security and lowering threat, with each element inspected and controlled. Managing and securing crucial nuclear knowledge just isn’t negotiable. With this in thoughts, Westinghouse got down to design a knowledge spine that would host AI purposes for among the most trusted utilities on the planet. Databricks was the best companion to assist Westinghouse obtain this purpose.
As Westinghouse got down to design a knowledge spine so safe and strong that it may host AI purposes for among the most trusted utilities on the planet, it turned to Databricks. The Databricks workforce rapidly turned a “guiding gentle” for Westinghouse, offering essential help because the Westinghouse infrastructure workforce took the lead in configuring our methods to fulfill the nuclear business’s strict regulatory necessities. Westinghouse was in a position to leverage Databricks’ state-of-the-art governance with Unity Catalog. It was constructed based on greatest practices outlined within the Databricks AI Safety Framework (DASF), complementing Microsoft’s strong safety requirements. These foundations bolster the credibility of Westinghouse’s knowledge administration practices and provides its clients peace of thoughts, which is crucial in an business the place belief and reliability are paramount.
When it got here time to modernize how the information was organized, the Databricks skilled providers workforce delivered. Collectively, Westinghouse and Databricks created a scalable and multi-tiered analytics surroundings, full with an ML Ops course of that streamlines all the machine studying lifecycle. This basis additionally featured a sturdy prototyping surroundings, together with devoted workspaces, for testing and deploying AI fashions, all backed by a safe and dependable knowledge lakehouse structure.
The brand new infrastructure instantly saved tons of of hours yearly for the Digital Optimization Companies enterprise unit and allowed the Westinghouse workforce to reinvest of their product strains to incorporate AI for customer-facing purposes and providers.
To make this imaginative and prescient a actuality, Westinghouse had to make sure that its knowledge was correctly ready, managed, and ruled. That’s the place Databricks’ highly effective applied sciences, together with Auto Loader, Photon engine, and Lakeflow Jobs, actually shined. Then, when Westinghouse wanted real-time insights into its knowledge high quality and pipeline efficiency, they tapped into options like Lakehouse Monitoring and Expectations. Now, with Unity Catalog (UC) governing its knowledge, Westinghouse has full visibility into its knowledge’s journey, from supply to vacation spot. Within the nuclear business, every thing revolves round security and belief. As Westinghouse continues to develop pioneering new AI options, Databricks providers reinforce the belief Westinghouse earns for managing knowledge securely and reliably.
Accelerating AI in a Complicated Business
On September 4, 2024, Westinghouse launched its HiVE™ nuclear particular AI system and its bertha™ generative AI mannequin to the world. Not solely has the Westinghouse workforce quickly superior its AI capabilities utilizing the Databricks Knowledge Intelligence Platform, however it may well now create future AI merchandise and options restricted solely by creativeness.
To help in growing bertha™, Westinghouse leveraged the Databricks Mosaic AI Agent Framework, to quickly consider varied foundational fashions and GenAI methods. Utilizing Databricks Experiments and MLFlow, Westinghouse performed fast experimentation to find out the very best fashions, whereas logging statistics to judge efficiency. This method enabled Westinghouse to speed up the event of its customized Generative AI resolution.
Westinghouse can now leverage its superior knowledge infrastructure to create options throughout the nuclear business. For instance, giant industrial amenities talk and retailer huge portions of information. With an structure constructed on Databricks, Westinghouse maintains an AI resolution to extract, cleanse, and retailer machine knowledge from over 200 nuclear amenities worldwide. One other instance consists of an AI software designed to course of video knowledge in real-time inside Stress Water and Boiling Water Reactors with the potential to detect particles not less than 90% higher than guide inspections and save as much as 25% on inspection prices.
Lastly, one other nice instance consists of leveraging the bertha™ generative AI mannequin to generate licensing knowledge and documentation dramatically sooner. Historically, it may well take months to manually compile new nuclear web site licenses or environmental assessments. It is a essential step in streamlining nuclear growth.
The Databricks infrastructure has freed knowledge and nuclear specialists to deal with nuclear innovation. Because of this, the Westinghouse knowledge scientists delivered 4 proofs of idea in December 2024, two production-grade methods within the first quarter of 2025, and helped generate 45 distinct innovation concepts within the first two months of 2025.
Conclusion
The Westinghouse-configured Databricks Knowledge Intelligence Platform removes large obstacles to attaining Westinghouse’s AI ambitions. Now, Westinghouse can scale compute, quickly and safely experiment with mass quantities of manufacturing knowledge, and share info securely throughout purposes. Westinghouse HiVE™ nuclear-specific AI system clients admire the facility of auditability, enter and output transparency, real-time knowledge processing, and operational analytics. The Westinghouse groups worth the unbelievable and adaptable partnership with Databricks to create a novel platform that positions it for continued pioneering AI innovation.
“With Databricks all the time offering the most recent options that hit the market, Westinghouse is ready to frequently incorporate new AI capabilities for our clients.”
— Catherine Stanley, Knowledge, Digital, and AI Supervisor at Westinghouse
