Generative AI in naval engineering: Small, proprietary data sets limit adoption

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The discipline title of naval architecture and marine engineering (NAME) may only be a couple of hundred years old, but the origins date back thousands of years to ancient civilizations where humans were building boats to explore and carry out commerce. Various people, including Archimedes, Bouguer, and Chapman, have formalized the theories, science, and methods of the concepts of buoyancy, stability, and ship design.

The Intersection of Generative AI and Engineering

The surge of generative AI can harness tremendous potential for the engineering realm. It can also come with its challenges, as enterprises and engineers alike figure out the impact of AI on their roles, business strategies, data, solutions, and product development. What does the future roadmap look like for bringing generative AI into the software fold? ZDNET decodes from all angles.

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While the current generation of naval architects, including myself, may have drawn ship's lines by hand with pencils, splines, and ducks in their college courses, current design processes include advanced computer applications that incorporate machine learning. 

The lines of a vessel provide the hull form that is used to evaluate the design and build of the vessel. At the time when pencils and splines were used, the lines were developed through trial and error as smoothness was evaluated visually and sheets of paper were strewn with eraser fragments. There is software today that aids in hull lines development instantly and builds on algorithms developed through historical data collection and validation.

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