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Empowering Aerospace Workforce with Expert Knowledge on Amazon Q and Amazon Bedrock through GenAI

Navigating the Generational Workforce Challenge in Aerospace With AI-Based Solutions

The aerospace industry faces a unique challenge in today’s workforce environment. With a significant number of subject matter experts (SMEs) retiring and a competitive labor market, aerospace companies are struggling to maintain the knowledge base necessary for their operations. The post-COVID recovery has led to record production rates, requiring the sharing of specialized domain knowledge across more workers. Traditional methods of capturing and transferring this knowledge, such as manuals and bulletins, are no longer sufficient to meet the demands of a rapidly evolving industry.

Generative AI, a modern form of machine learning, offers a solution to this workforce challenge. By using AI technology to quickly digest, summarize, and answer complex questions from large technical document libraries, aerospace companies can accelerate their workforce development and ensure the continuity of expert knowledge within their organizations. AWS, with its broad range of AI/ML services and extensive experience in developing AI technologies, is uniquely positioned to help aerospace companies address this challenge.

One way to leverage generative AI in aerospace is through the use of Amazon Q, a service that provides fast, relevant answers to pressing questions by drawing on information from various data sources. By deploying a Q&A chatbot that accesses technical documents and provides expert-level guidance to technical staff, companies can streamline tasks, accelerate decision-making, and improve overall productivity. Amazon Bedrock Knowledge Bases offer a more flexible and customizable approach for generative AI developers, allowing them to build solutions tailored to their specific needs.

The RAG architecture, which combines a large language model with a customer-specific document database, helps ensure the accuracy and security of generative AI responses. By using this architecture, aerospace companies can trace the reasoning of their models back to source documents, keep their applications up to date with evolving knowledge bases, and securely manage access to proprietary information.

In conclusion, generative AI holds great promise for the aerospace industry, providing a powerful tool for addressing workforce challenges and improving productivity. By leveraging AWS AI/ML services like Amazon Q and Amazon Bedrock, aerospace companies can build customized generative AI solutions that meet their specific needs and help them stay competitive in a rapidly evolving market. With the right technology and expertise, aerospace companies can overcome the generational workforce challenge and ensure the continuity of expert knowledge within their organizations.

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