Find out the difference between Cognitive Computing & AI

By NIIT Editorial

Published on 14/01/2022

7 minutes

Understanding the distinction between artificial intelligence (AI) and cognitive computing is crucial to comprehend the future of work. To those who are not in the technology business, AI and Cognitive Computing are commonly used interchangeably. Both suggest that computers are now in charge of job activities that humans formerly performed. Indeed, there is a significant distinction between AI and Cognitive Computing. Though both technologies represent the next great thing in supercomputing, they have different meanings when put to practical use.

What Is Artificial Intelligence?

Artificial intelligence, often known as machine intelligence, refers to intelligence exhibited by machines instead of natural intelligence demonstrated by humans and other animals. Artificial intelligence (AI) is the computer emulation of human intelligence processes. Learning from continually changing data, understanding data, and self-correction systems to make judgments are examples of these processes. Sensing, learning, and digesting the information from the environment are all part of human intelligence. As a result, AI entails:

● Stimulating human senses

● Stimulating learning and processing

● Stimulating human responses.

According to AI researchers, Artificial intelligence allows a machine to provide augmented intellect, surpassing human understanding and accuracy, as well as agility and strength. Problem-solving, natural language processing, game-playing, image processing, speech recognition, automated programming, and robotics are all applications of AI.

What Is Cognitive Computing?

On the other hand, cognitive computing is difficult to characterize precisely. Cognitive computing, according to tech experts, is computing that is focused on enhanced thinking and comprehension. Unique technologies that do specific tasks that aid human intellect are referred to as cognitive computing. We've been working with intelligent decision support systems since the early days of the internet boom. These decision support systems employ better data and a better algorithm to analyze enormous amounts of information, thanks to recent technological developments. As a result, cognitive computing is:

● Understanding and mimicking logic

● Simulating and comprehending human behavior

● Creating better human judgments at work by utilizing cognitive computing solutions

It might work similarly to human cognition, which is capable of making high-level judgments under challenging situations. Rather than pure data or sensor streams, cognitive computing can manage conceptual data. Speech recognition, sentiment analysis, face recognition system, risk evaluation, and fraud detection are some of the cognitive computing applications.

What Are The Distinctions?

The main distinction between artificial intelligence and cognitive computing is that artificial intelligence can cope with massive amounts of data and perform extensive analyses. At the same time, humans retain total control over the decision-making process. To address complicated issues, AI augments human reasoning. Its main goal is to portray reality and deliver accurate findings correctly. To address complicated issues, cognitive computing relies on simulating human behavior and cognition. Cognitive computing aims to mimic how people solve issues, whereas AI strives to develop new ways to solve problems that may be better than humans.

The goal of AI is to solve a problem using the best algorithm available rather than to emulate human intellect and processes. Human decision-making is not the responsibility of cognitive computing. They merely provide more information to help people make judgments. AI is in charge of making judgments on its own, reducing the need for people. Thus, cognitive computing helps people make better decisions by giving them the last say while using technology. On the other hand, AI runs on the notion that robots can make better decisions on behalf of humans. They have identical intentions but different inclinations when it comes to connecting with humans organically.

Conclusion

In the actual world, Cognitive Computing applications are frequently distinct from applications of AI. In data-intensive businesses like finance, marketing, government, and healthcare, cognitive computing is critical. In service-oriented businesses like healthcare, manufacturing, and customer support, AI is critical.

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