Difference Between AI and CI

➧Artificial Intelligence vs Computational Intelligence

We have witnessed nothing sort of a revolution in the history of mankind as artificial intelligence (AI) becomes mainstream in our everyday life and augmenting human capabilities to solve some of the complex problems that troubled us for a really long time. What was once a distant dream of the future is now the future of mankind! We are at a stage where human intelligence and machine intelligence coexist at the onset of a data revolution. Artificial Intelligence aims at emulating human intelligence on machines to make them think and behave like humans. The human brain has evolved for thousands of years to its current state. However, traditional AI was not enough to serve the increasing demands of machine learning. The shortcomings of AI opened up new avenues for the non-conventional models which eventually have rise to a new discipline called computational intelligence (CI). The development of CI techniques follows a different path than that of the AI. Let’s take a brief look at the new computational model called the CI and how it is compared to the classical AI approach.

What is Artificial Intelligence?

Artificial Intelligence, commonly abbreviated as AI, is the study of intelligent behavior and how to make machines do things at which humans are doing better. AI is one of the technological breakthroughs of this digital era which aims at emulating human intelligence on machines to make them think and behave like human beings. AI is based on the idea that human intelligence could be replicated in computer programs. Although, the idea of creating intelligent machines – ones that are as smart as or smarter than human beings – is not new but it became part of modern science with the rise of digital computers and proliferation of the internet.

What is Computational Intelligence?

Computational Intelligence, also referred to as CI, refers to a computationally intelligent system that is characterized with the capability of computational adaptation, fault tolerance, and high computation speed. It is the study of adaptive mechanisms to enable or facilitate intelligent behavior in complex and changing environments. Computational adaptation means the ability of a system to adapt to the changes in its input and output instances. The adaptive mechanisms include the following AI paradigms that exhibit an ability to learn or adapt to new environments: swarm intelligence (SI), artificial neural networks (ANN), evolutionary computation (EC), artificial immune systems (AIS), and fuzzy systems (FS)