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The main purpose of this article is to describe potential benefits andapplications of the SP theory, a unique attempt to simplify and integrate ideasacross artificial intelligence, mainstream computing and human cognition, withinformation compression as a unifying theme. The theory, including a concept ofmultiple alignment, combines conceptual simplicity with descriptive andexplanatory power in several areas including representation of knowledge,natural language processing, pattern recognition, several kinds of reasoning,the storage and retrieval of information, planning and problem solving,unsupervised learning, information compression, and human perception andcognition. In the SP machine -- an expression of the SP theory which iscurrently realised in the form of computer models -- there is potential for anoverall simplification of computing systems, including software. As a theorywith a broad base of support, the SP theory promises useful insights in manyareas and the integration of structures and functions, both within a given areaand amongst different areas. There are potential benefits in natural languageprocessing (with potential for the understanding and translation of naturallanguages), the need for a versatile intelligence in autonomous robots,computer vision, intelligent databases, maintaining multiple versions ofdocuments or web pages, software engineering, criminal investigations, themanagement of big data and gaining benefits from it, the semantic web, medicaldiagnosis, the detection of computer viruses, the economical transmission ofdata, and data fusion. Further development of these ideas would be facilitatedby the creation of a high-parallel, web-based, open-source version of the SPmachine, with a good user interface. This would provide a means for researchersto explore what can be done with the system and to refine it.

Simplification and integration in computing and cognition: the SP theory and the multiple alignment concept