Artificial Intelligence’s Adaptive Intelligence and Cognitive Computing: Revolutionizing Problem-Solving

3 min readJan 30, 2024

Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life.

In the ever-evolving landscape of technology, Artificial Intelligence (AI) has emerged as a force which has reshaped the way we approach problem solving. At the very front of this revolution is Cognitive computing.

Understanding Cognitive Computing

In the most basic terms Cognitive Computing is an attempt to have computers mimic the way human brain works. In order to accomplish this, cognitive computing uses artificial intelligence (AI) and other underlying technologies:

Expert systems.
Neural networks.
Machine learning.
Deep learning.
Natural language processing (NLP).
Speech recognition.
Object recognition.
Robotics.

Cognitive Computing Systems are adaptive and capable of evolving overtime. This helps machines to solve real life scenario problems.

Systems used in the cognitive sciences combine data from various sources while weighing context and conflicting evidence to suggest the best possible answers. To achieve this, cognitive systems include self-learning technologies that use data mining, pattern recognition and NLP to mimic human intelligence.

Adaptive Intelligence

At the very core of Cognitive Computing lies Adaptive Intelligence. This is the ability of AI systems to learn from experience and adapt to new information. Traditional algorithms follow predetermined rules, but Adaptive Intelligence allows machines to continuously evolve.

Examples of Real-World Use Cases of Cognitive Computing:

IBM Watson has been utilized in the healthcare industry to analyze medical records and find insights to improve diagnoses and treatment plans.

Contrary to the fear of machines replacing humans, Cognitive Computing emphasizes a collaborative approach. The goal is to provide humans with a powerful tool which as assist them with their decisions and help them improve their decision-making capabilities.

Imagine a data analyst working alongside a Cognitive Computing system that sifts through vast datasets, uncovering hidden patterns and trends. This partnership accelerates the problem-solving process, enabling humans to focus on higher-order tasks that require creativity and critical thinking.

Difference between AI and Cognitive Computing

The basic use case of Artificial Intelligence is to implement the best algorithm for solving a problem. However, cognitive computing goes further to mimic human wisdom and intelligence by studying a series of factors. Cognitive computing varies widely from Artificial Intelligence in terms of concept.

Cognitive Computing Learns and Imitates Human Thought Process
Unlike AI systems that only attend to a given problem, cognitive computing can learn from the data and patterns to suggest human relevant actions depending on their understanding. When it comes to AI, the system takes complete control and uses a pre-defined algorithm to avoid a certain scenario or take the necessary steps.
However, cognitive computing can be applied to different fields where it performs the role of an assistant rather than the one completing a task.
Cognitive Computing Does Not Throw Human Out of the Picture
Cognitive computing enables users to analyze data faster and more accurately without worrying about being wrong. Its main aim is to assist humans with their decision-making. Unlike AI, it doesn’t completely disregard humans.

Deloitte refers to cognitive computing as “more encompassing than the traditional, narrow view of AI, AI has been primarily used to describe technologies capable of performing tasks normally requiring human intelligence”

Whereas they define cognitive computing as “We see cognitive computing as being defined by machine intelligence which is a collection of algorithmic capabilities than can augment employee performance, automate increasingly complex workloads, and develop cognitive agents that simulate both human thinking and engagement.”

As we embark on this journey of Cognitive Computing, ethical considerations take center stage

The Future of Cognitive Computing

In conclusion, Cognitive Computing is not just a technological evolution, it’s the fusion of adaptive intelligence and problem-solving capabilities which opens the doors to possibilities we once deemed were fantastical.

The future promises a landscape where Cognitive Computing plays a leading role in unravelling complex challenges, pushing the boundaries of what we thought achievable. It’s a journey where humans and machines dance together. The symphony of Cognitive Computing is just beginning, and its crescendo will undoubtedly shape the destiny of problem-solving in ways yet to be fully realized.