Introduction
Nuclear power ranks among the many world’s most regulated industries. AI and particularly generative AI have created sufficient affect that thought leaders rank it amongst different transformative “common objective applied sciences” akin to electrical energy and the steam engine. Harnessing AI to reimagine nuclear operations throughout the business means extra carbon-free nuclear power for electrical grids and information facilities, which the Worldwide Vitality 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 Information Administration Resolution
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’ value of cleaned and contextualized industrial information distinctive to the nuclear world. Nonetheless, the crew wanted to enhance the corporate’s information infrastructure if it needed to comprehend its AI ambitions. The present on-premises analytics database lacked some vital scalability options and choices. With no scalable cloud resolution, the info crew struggled with a scarcity of computing assets, an incapacity to quickly experiment with huge quantities of information, and restrictions on safely sharing information throughout purposes.
To construct a world-class, nuclear-specific AI functionality, Westinghouse wanted a greater resolution. Westinghouse determined to construct on the Databricks Information Intelligence Platform, a transfer that may show essential in its mission to drive innovation. The nuclear business has at all times been deeply dedicated to security and lowering danger, with each element inspected and controlled. Managing and securing essential nuclear information will not be negotiable. With this in thoughts, Westinghouse got down to design a knowledge spine that might host AI purposes for a number of the most trusted utilities on this planet. Databricks was the best accomplice to assist Westinghouse obtain this aim.
As Westinghouse got down to design a knowledge spine so safe and strong that it may host AI purposes for a number of the most trusted utilities on this planet, it turned to Databricks. The Databricks crew shortly turned a “guiding mild” for Westinghouse, offering essential help because the Westinghouse infrastructure crew took the lead in configuring our programs 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 in accordance with finest practices outlined within the Databricks AI Safety Framework (DASF), complementing Microsoft’s strong safety requirements. These foundations bolster the credibility of Westinghouse’s information administration practices and provides its clients peace of thoughts, which is important in an business the place belief and reliability are paramount.
When it got here time to modernize how the info was organized, the Databricks skilled companies crew delivered. Collectively, Westinghouse and Databricks created a scalable and multi-tiered analytics surroundings, full with an ML Ops course of that streamlines your complete 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 information lakehouse structure.
The brand new infrastructure instantly saved a whole bunch of hours yearly for the Digital Optimization Companies enterprise unit and allowed the Westinghouse crew to reinvest of their product strains to incorporate AI for customer-facing purposes and companies.
To make this imaginative and prescient a actuality, Westinghouse had to make sure that its information 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 information high quality and pipeline efficiency, they tapped into options like Lakehouse Monitoring and Expectations. Now, with Unity Catalog (UC) governing its information, Westinghouse has full visibility into its information’s journey, from supply to vacation spot. Within the nuclear business, every little thing revolves round security and belief. As Westinghouse continues to develop pioneering new AI options, Databricks companies reinforce the belief Westinghouse earns for managing information 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 crew quickly superior its AI capabilities utilizing the Databricks Information Intelligence Platform, however it may possibly 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 programs. Utilizing Databricks Experiments and MLFlow, Westinghouse carried out speedy experimentation to find out one of the best fashions, whereas logging statistics to guage efficiency. This method enabled Westinghouse to speed up the event of its customized Generative AI resolution.
Westinghouse can now leverage its superior information 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 information from over 200 nuclear amenities worldwide. One other instance consists of an AI utility designed to course of video information 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 information and documentation dramatically quicker. Historically, it may possibly take months to manually compile new nuclear web site licenses or environmental assessments. This can be a essential step in streamlining nuclear improvement.
The Databricks infrastructure has freed information and nuclear specialists to give attention to nuclear innovation. Because of this, the Westinghouse information scientists delivered 4 proofs of idea in December 2024, two production-grade programs 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 Information Intelligence Platform removes enormous boundaries to attaining Westinghouse’s AI ambitions. Now, Westinghouse can scale compute, quickly and safely experiment with mass quantities of manufacturing information, and share data securely throughout purposes. Westinghouse HiVE™ nuclear-specific AI system clients respect the ability of auditability, enter and output transparency, real-time information 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 at all times offering the newest options that hit the market, Westinghouse is ready to frequently incorporate new AI capabilities for our clients.”
— Catherine Stanley, Information, Digital, and AI Supervisor at Westinghouse
