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Shell, C3 AI, Baker Hughes, and Microsoft announced the launch of the Open AI Energy Initiative™ (OAI), a first-of-its-kind open ecosystem of artificial intelligence (AI)-based solutions for the energy and process industries. The OAI provides a framework for energy operators, service providers, equipment providers, and independent software vendors for energy services to offer interoperable solutions, including AI and physics-based models, monitoring, diagnostics, prescriptive actions, and services, powered by the BHC3™ AI Suite and Microsoft Azure.
“This initiative is about combining the efforts of global leaders to accelerate the digital transformation of the energy industry to new, safe, and secure energy and to ensure climate security,” said C3 AI CEO Thomas M. Siebel.
The first set of OAI solutions provided by Shell and Baker Hughes are focused on reliability and designed to improve uptime and performance of energy assets and processes. These reliability solutions will serve as extensions to the current BHC3 Reliability application, an AI-based application that provides reliability, process, and maintenance engineers with AI-enabled insights to predict process and equipment performance risks for the energy industry. The application leverages the BHC3 AI Suite’s ability to integrate enterprise-scale data from disparate data sources and train AI reliability models that cover full plant operations while taking full advantage of Azure, Microsoft’s scalable, enterprise-class cloud infrastructure.
The OAI augments BHC3 Applications with partner-led, domain-specific solutions that accelerate deployment of AI-based reliability solutions to unlock significant economic value across the energy industry while helping to make energy production cleaner, safer, and more efficient. The initial OAI reliability solutions offered by Shell and Baker Hughes enable interoperability between BHC3 Reliability, OAI modules, and existing industry solutions for such applications. Solutions available today include proven and tested equipment- and process-specific modules with pre-trained AI models, codified subject matter expertise, low-latency data connectors, thermodynamic and operating parameter libraries, global health monitoring services, deep diagnostics, failure prevention recommendations, and prescriptive actions.