Difference between AI and Soft Computing

Both AI (Artificial Intelligence) and Soft Computing use data driven, flexible and nonsystematic tools to solve the problems. The most basic difference between AI and soft computer is that the AI is used to develop intelligent systems, whereas soft computing is used to solve real problems.

In this article, we will discuss the important differences between AI and Soft Computing. But before that, let's start with some basics so that it becomes easier to understand the differences between them.

What is AI?

AI or Artificial Intelligence is a science which deals with making machine intelligence. According to John McCarthy, the father of artificial intelligence, it is the science and engineering of making intelligent machines or intelligent computer programs. Thus, AI is a technology for making a computer or computer embedded device to think intelligently like a human. It utilizes image processing, cognitive science, neural systems, machine learning, etc.

AI enables machines to behave in a similar manner as human behaves in varying situations. It tries to solve human like problems like gaming, natural language processing, expert systems, vision systems, etc.

What is Soft Computing?

Soft computing is a computing model evolved to solve non-linear issues. It helps to solve issues where human intelligence is needed to solve. Probabilistic models, fuzzy logic, neural networks, evolutionary algorithms are parts of soft computing.

Soft computing uses flexible, non-rigid tools like fuzzy logic, statistical tools or neural networks to solve current computing, scientific, engineering and economic problems. More specifically, soft computing is used to solve those problems that cannot be solved using mathematical equations and algorithms. Soft computing is a newer technology that focus on solving problems.

Difference between AI and Soft Computing

The following are some of the important differences between AI and Soft Computing −

Factor	AI (Artificial Intelligence)	Soft Computing
Concept	Artificial Intelligence targets to make machines intelligent.	Soft computing deals with issues with tolerance levels like uncertainty, imprecision, partial truth, etc.
Branches	AI has the following major branches. Cognitive Computing Computer Vision Machine Learning Neural Networks Deep Learning Natural Language Processing	Soft computing has the following major branches. Probabilistic Models Multivalued and Fuzzy Logics Neural Networks Evolutionary Algorithms
Applications	AI applications are countless. AI is used in healthcare, finance, automotive, data security to analyze complex data.	Soft computing is used in engineering disciplines like data mining, automotive, etc.
Aim	AI aims at making machines intelligent.	Soft computing deals with imprecision and probabilities.
Input	AI needs the appropriate data to analyze and act.	Soft computing can handle ambiguous and noisy data.

Conclusion

The most significant difference between AI and Soft Computing that you should note here is that Artificial Intelligence targets to make the machines intelligent, whereas Soft Computing deals with issues related to tolerance levels such as uncertainty, imprecision, partial truth, etc.