Soft computing is a collection of artificial intelligence (AI) computing techniques that gives devices human-like problem-solving capabilities. It includes the basics of neural networks, fuzzy logic and genetic algorithms. The soft computing theory and techniques were introduced in the 1980s. The term was coined by Lofti A. Zadeh, a mathematician, computer scientist, electrical engineer, AI researcher, and professor emeritus of computer science at the University of California, Berkeley.

About Soft Computing

Unlike traditional computing (using physical data centers to store digital assets and run complete networks for daily operations) soft computing helps people solve more complex real-life problems. Unlike hard computing, soft computing does not tolerate imprecisions, uncertainties, partial truths and approximations. The latter is more accurate than any other kind of computing. It uses the human mind as a role model.