Biochemistry provides inspiration for a new kind of AI
01 June 2021
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This paper, by Dr Gerry Wolff, explores a promising foundation for the development of human-like broad AI, which has the potential to solve 19 problems that can currently be found in AI research.
The paper is about the origin, development, and benefits of the SP System (SPS), which means the SP Theory of Intelligence and its realisation in the SP Computer Model (SPCM). The SPS is radically different from deep neural networks (DNNs), with many advantages compared with DNNs. As will be described, the SPS provides a promising foundation for the development of human-like broad AI. The SPS was inspired in part by: evidence for the importance of information compression in human learning, perception, and cognition; and the concept of ‘multiple sequence alignment’ in biochemistry. That latter concept led to the development of the powerful concept of SP-multiple-alignment, a concept which is largely responsible for the intelligence-related versatility of the SPS.
The main advantages of the SPS are: 1) The clear potential of the SPS to solve 19 problems in AI research; 2) Versatility of the SPS in aspects of intelligence, including unsupervised learning, and several forms of reasoning; 3) Versatility of the SPS in the representation and processing of knowledge; 4) Seamless integration of diverse aspects of intelligence and diverse forms of knowledge, in any combination, a kind of integration that appears to be necessary in any artificial system that aspires to the fluidity and adaptability of the human mind; 5) Several other potential benefits and applications of the SPS. It is envisaged that the SPCM will provide the basis for the development of a first version of the SP Machine, with high levels of parallel processing and a user-friendly user interface. All software in the SP Machine would be open-source so that clones of the SP Machine may be created anywhere by individuals or groups, to facilitate further research and development of the SP System.
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