Artificial Intelligence Research at General Electric

General Electric is engaged in a broad range of research and development activities in artificial intelligence, with the dual objectives of improving the productivity of its internal operations and of enhancing future products and services in its aerospace, industrial, aircraft engine, commercial, and service sectors Many of the applications projected for AI within GE will require significant advances in the state of the art in advanced inference, formal logic, and architectures for real-time systems New software tools for creating expert systems are needed to expedite the construction of knowledge bases. Further, new application domains such as computer-aided design (CAD), computer-aided manufacturing (CAM), and image understanding based on formal logic require novel concepts in knowledge representation and inference beyond the capabilities of current production rule systems Fundamental research in art,ificial intelligence is concentrated at Corporate Research and Development (CR&D), with advanced development and applications pursued in parallel efforts by operating departments The fundamental research and advanced applications activities are strongly coupled, providing research teams with opportunities for field evaluations of new concepts and systems. This article summarizes current research projects at CR&D and gives an overview of applications within the Company. providing assistance in selection of the most effective passive and active sensors at acceptable cost. The requirements of this domain exceed the capabilities of current production rule systems; consequently, approximately half of the research program in artificial intelligence is focused on extending the capabilities of current reasoning systems and on more powerful and efficient tools for knowledge representation. Reasoning with Incomplete and Uncertain Information To date, expert systems have shown most frequent success in diagnostic applications or on problems with similarly constrained data and results. Problem domains with less constraint such as military advisory systems will require more advanced reasoning techniques because the input data will have the following characteristics: 0 Uncertain, incomplete, potentially erroneous, and time-