Abstract
In the present era of artificial intelligence (AI) enabled solutions, the world is observing a tremendous influx in machine learning (ML) approaches across various application domains like healthcare, industry, document analysis, audio-video processing, etc. All existing machine learning approaches claim for intelligent solutions, but till date the learning is guided by the human wisdom i.e. all the proposed machine intelligence algorithms are data centric and infer knowledge without understanding the scenarios. The wisdom is an ability to take wise decisions based on the inferred knowledge to satisfy W5HH principle which outlines the series of answers to the questions such as why, what, who, when, where, how and how much, in a given context. This paper discusses the scope of machine wisdom (artificial wisdom)over conventional machine learning strategies along with its significance and how it can be achieved.
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Nagabhushan, P., Sonbhadra, S.K., Punn, N.S., Agarwal, S. (2021). Towards Machine Learning to Machine Wisdom: A Potential Quest. In: Srirama, S.N., Lin, J.CW., Bhatnagar, R., Agarwal, S., Reddy, P.K. (eds) Big Data Analytics. BDA 2021. Lecture Notes in Computer Science(), vol 13147. Springer, Cham. https://doi.org/10.1007/978-3-030-93620-4_19
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