Problems encountered when applying artificial intelligence (AI) techniques to the diagnosis of electronic equipment are identified, and an approach to building a useful AI diagnostic tool is given. An outline of the system architecture, which will support the more sophisticated and data-intensive needs associated with automation, is given. Improvements to existing development tools for AI diagnostic capabilities are also described.
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