Topics In Demand
Notification
New

No notification found.

How Does Cognitive Computing Differ From AI?
How Does Cognitive Computing Differ From AI?

April 24, 2023

AI

563

0

Distinguishing Between Cognitive Computing and AI

 

Artificial intelligence (AI), machine learning, and cognitive computing have been groundbreaking technological discoveries in recent years. Most of the time these technologies are assumed to be the same; however, they have unique functionalities.

 

Cognitive Computing is often mistaken as Artificial Intelligence. Both are fundamentally different. Cognition is the ability of the human brain to observe, perceive, learn, and record information from the external world. 

 

We know that machines can store and retrieve information but is it possible for typical machines to learn and understand such information? Well, this is where the computational ability of machines is utilized to integrate with cognitive science to achieve a computerized model of the human brain. This method of technology is called Cognitive Computing or Cognitive AI.

 

Before comparing Cognitive AI and AI, let’s learn about how they work.

 

How Does Cognitive Computing Work?

 

Cognitive Computing performs individual tasks that facilitate human intelligence. It makes use of machine learning algorithms, neural networks, visual recognition, and natural language processing to accomplish human-like tasks. 

 

Cognitive Computing analyzes large amounts of structured & unstructured data and aims to simulate human behavior and reasoning to assist in decision-making.

 

Visual recognition is used to study patterns and identify objects in images or videos. Natural language Processing is the ability to understand, analyze and draw insights from human languages. A common example of NLP is suggestions of the next words in the Google search engine and Gmail. 



 

The cognitive computing systems must be adaptive, interactive, iterative&stateful, and contextual to work at their fullest potential.

 

How Does AI Work? 

 

AI is developed to match human intelligence and make decisions based on learning data. It learns from large datasets combined with fast-processing machine learning and deep learning algorithms.

 

Machine learning builds analytical models of data and draws underlying insights from raw data without being explicitly programmed whereas; Deep learning uses interconnected neural networks that function like neurons in the human brain. Neural networks analyze complex datasets and find associations between different data variables.

 

Cognitive Computing vs Artificial Intelligence - The Key Differences 

The underlying technologies in Cognitive Computing and Artificial intelligence are similar but their functionalities are different. Let's compare both and learn the differences between them:-

 

  • AI automates human tasks with its intelligent decision-making system whereas; Cognitive AI augments human intelligence by perceiving and memorizing to suggest smart decisions.

 

  • AI algorithms generate accurate results based on algorithms without human intervention whereas; results of cognitive computing project ambiguity and are based on the human thought process. 

 

  • AI adopts real-world scenarios but cognitive AI replicates human behavior.

 

  • Cognitive computing considers contradictory and uncertain situations before giving suggestions but AI focuses on achieving any task through a logical approach. 

 

  • AI is utilized in speech recognition, image processing, video analytics, and chatbots; on the other hand, Cognitive AI plays a significant role in functions such as sentiment analysis, fraud detection, and risk analysis.



 

Final Thoughts

Today Cognitive Computing applications have been diversified in numerous fields such as healthcare, pharmaceuticals, finance, and retail. Unlike artificial intelligence, Cognitive AI involves natural intelligence and machine intelligence.

 

 


That the contents of third-party articles/blogs published here on the website, and the interpretation of all information in the article/blogs such as data, maps, numbers, opinions etc. displayed in the article/blogs and views or the opinions expressed within the content are solely of the author's; and do not reflect the opinions and beliefs of NASSCOM or its affiliates in any manner. NASSCOM does not take any liability w.r.t. content in any manner and will not be liable in any manner whatsoever for any kind of liability arising out of any act, error or omission. The contents of third-party article/blogs published, are provided solely as convenience; and the presence of these articles/blogs should not, under any circumstances, be considered as an endorsement of the contents by NASSCOM in any manner; and if you chose to access these articles/blogs , you do so at your own risk.


© Copyright nasscom. All Rights Reserved.