Introduction
Nuclear power 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 “normal objective applied sciences” resembling 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 knowledge 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 prospects collaborate with Westinghouse.
Constructing a Higher Knowledge Administration Resolution
Westinghouse’s digital transformation began greater than 5 years in the past with a deep bench of knowledge and nuclear specialists and over 70 years’ value of cleaned and contextualized industrial knowledge distinctive to the nuclear world. Nonetheless, the staff wanted to enhance the corporate’s knowledge infrastructure if it needed to appreciate its AI ambitions. The prevailing on-premises analytics database lacked some vital scalability options and choices. With out a scalable cloud answer, the information staff struggled with an absence of computing assets, an lack of ability to quickly experiment with large quantities of knowledge, and restrictions on safely sharing knowledge throughout functions.
To construct a world-class, nuclear-specific AI functionality, Westinghouse wanted a greater answer. Westinghouse determined to construct on the Databricks Knowledge Intelligence Platform, a transfer that might 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 vital nuclear knowledge just isn’t negotiable. With this in thoughts, Westinghouse got down to design an information spine that would host AI functions for a few of the most trusted utilities on this planet. Databricks was the best companion to assist Westinghouse obtain this purpose.
As Westinghouse got down to design an information spine so safe and sturdy that it might host AI functions for a few of the most trusted utilities on this planet, it turned to Databricks. The Databricks staff rapidly turned a “guiding mild” for Westinghouse, offering essential help because the Westinghouse infrastructure staff took the lead in configuring our methods to satisfy 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 greatest practices outlined within the Databricks AI Safety Framework (DASF), complementing Microsoft’s sturdy safety requirements. These foundations bolster the credibility of Westinghouse’s knowledge administration practices and provides its prospects 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 information was organized, the Databricks skilled companies staff delivered. Collectively, Westinghouse and Databricks created a scalable and multi-tiered analytics atmosphere, full with an ML Ops course of that streamlines the whole machine studying lifecycle. This basis additionally featured a sturdy prototyping atmosphere, 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 a whole lot of hours yearly for the Digital Optimization Providers enterprise unit and allowed the Westinghouse staff to reinvest of their product strains to incorporate AI for customer-facing functions and companies.
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 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 knowledge securely and reliably.
Accelerating AI in a Complicated Trade
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 staff quickly superior its AI capabilities utilizing the Databricks Knowledge Intelligence Platform, however it may now create future AI merchandise and options restricted solely by creativeness.
To help in creating 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 speedy experimentation to find out one of the best fashions, whereas logging statistics to judge efficiency. This method enabled Westinghouse to speed up the event of its customized Generative AI answer.
Westinghouse can now leverage its superior knowledge infrastructure to create options throughout the nuclear business. For instance, giant industrial amenities talk and retailer monumental portions of knowledge. With an structure constructed on Databricks, Westinghouse maintains an AI answer to extract, cleanse, and retailer machine knowledge from over 200 nuclear amenities worldwide. One other instance contains 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 no less than 90% higher than guide inspections and save as much as 25% on inspection prices.
Lastly, one other nice instance contains leveraging the bertha™ generative AI mannequin to generate licensing knowledge and documentation dramatically sooner. Historically, it may take months to manually compile new nuclear website licenses or environmental assessments. It is a essential step in streamlining nuclear growth.
The Databricks infrastructure has freed knowledge and nuclear specialists to concentrate on 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 big boundaries to reaching Westinghouse’s AI ambitions. Now, Westinghouse can scale compute, quickly and safely experiment with mass quantities of manufacturing knowledge, and share data securely throughout functions. Westinghouse HiVE™ nuclear-specific AI system prospects respect 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 singular platform that positions it for continued pioneering AI innovation.
“With Databricks at all times offering the most recent options that hit the market, Westinghouse is ready to regularly incorporate new AI capabilities for our prospects.”
— Catherine Stanley, Knowledge, Digital, and AI Supervisor at Westinghouse
