Since the beginning of computing, Artificial Intelligence has always been the end target. With modern cognitive computing models, we seem to be getting closer and closer to that goal every day. Due to the amalgamation of cognitive science. Also, based on the fundamental principle of simulating the cycle of human thought, cognitive AI computing applications have far-reaching impacts on our private lives industries such as medicine, banking, and more. The benefits of cognitive technology are well and a step further than conventional AI systems.
While the basic use case of artificial intelligence is to apply the best algorithm for solving a problem. Cognitive computing tries to mimic human intelligence and logical abilities by evaluating a set of variables. The cognitive computing process uses a mixture of artificial intelligence, machine learning, neural networks, sentiment analysis. More on, natural language processing, and contextual awareness to solve everyday problems as human beings do. The ability of computer systems to do that means we are making a thing that will be as intelligent as humans. Thus help humans in their daily roles. Let’s see how our world is and will become a better place due to Cognitive AI.
However, before diving into the benefits that cognitive AI has provided us, we need to understand the concept in its entirety.
What Is Artificial Intelligence?
Simply put, AI is the simulation of human intelligence processes by machines. These machines can partake in processes such as learning from constantly changing data, practicing reasoning to make sense of the data. Also, using self-correction mechanisms to make decisions.
Human intelligence is our ability to ‘sense’ the environment, learning from it and then processing the information from the environment. Since AI learns like human intelligence. It does so through simulating the process of learning and processing through deep learning or machine learning. It showcases the responses through robotics for instance.
At the end of the day, AI revolves around the idea of creating synergies and enabling performance that is unmatched.
What Is Cognitive Computing?
Think of them as smart ‘decision support systems that have been a part of our lives ever since the internet came into being. These refer to individual technologies that perform particular tasks that facilitate human intelligence. While also enabling them to achieve objectives that they would have otherwise been unable to.
Making the most of recent technology breakthroughs. These decision support systems use data to churn up improved algorithms. This helps them to introduce improved analysis of rather vast stores of information.
In simpler terms, cognitive computing refers to:
1) Understanding and simulating reasoning
2) Understanding and simulating human behavior
With cognitive computing, you see applications such as speech recognition, sentiment analysis, face detection, fraud detection, and risk assessment come into use. All applications that we’ve now begun to interact with on a rather regular basis.
At the end of the day, cognitive computing systems help us to make better human decisions at work. Enable us to reach objectives that would’ve otherwise seemed difficult to achieve.
How Cognitive Computing Works?
Think of cognitive computing systems as a place where information arrives from many different sources. Which is then weighed under the context and measured against any conflicting evidence before it is churned out in the form of an effective suggestion.
Over time, cognitive systems learn to refine their methods of identification and the way they process data. This helps them become capable of not only anticipating new problems. Also modeling possible solutions to the problems.
Cognitive Computing Attributes
Cognitive computing systems must have a range of attributes that enable them to do the work effectively:
1) Adaptive
They must be flexible enough to understand any information changes. These systems must also be able to internalize dynamic data in real-time. Also, make any adjustments as data/environments change.
2) Interactive
Human-computer interaction is crucial for cognitive systems to operate properly. So users must have the ability to interact with cognitive machines and define their needs as they change along the way. This interaction is not just with humans. Also extends to interaction with processors, devices, and any other cloud platforms.
3) Iterative
If the problem lacks data that needs to suggest a solution. These systems must have the ability to identify problems/roadblocks by asking questions. Or pulling in additional data in an attempt to ensure that they have access to everything that they might need. The systems will most likely do this by creating a database with information that they’ve received before. And use any similar situational data to solve problems.
4) Contextual
Cognitive systems will deal with multi-faceted data. So they need to understand and identify contextual data i.e. time, location, requirements, user profiles, etc. Since each data set will have to be interpreted individually in line with the context that it’s operating in.
Now that the concept of both artificial intelligence and cognitive computing is clear. Let’s look at the differences between the two – because sometimes they can both seem quite similar.
AI Vs Cognitive Computing
Artificial intelligence augments human thinking in an attempt to solve complex problems. By focusing on trying to accurately reflect reality and provide accurate results. AI works to solve problems with the best possible algorithm that it can devise. It tries to conjure up new and effective ways to solving problems. Takes responsibility for making these decisions on their own, thereby minimizing the role of humans.
On the other hand, cognitive computing tries to mimic human behavior/reasoning when coming up with solutions to complex problems. It replicates how humans would solve problems. But does not actually assume responsibility for making the decision. Instead, it supplements information for humans. So that they can make their own decisions, albeit, informed.
Applications Of Cognitive AI
Before embarking on the rather “big picture” for applications of Cognitive AI. Let us look at the common applications of Cognitive AI which will help us understand the various sub-sectors where cognitive AI is making its mark.
Smart IoT
The Internet of Things is home to devices and a plethora of data, and it needs something to connect it all. Cognitive AI is that very thing.
AI-enabled cybersecurity
No, we’re not talking about the terminator here. With AI, you can enhance situational awareness for potential attacks. Also, use data security encryption to keep data secure. Through this, all data can be ‘locked’ and kept securely through an AI-enabled mechanism.
Cognitive Analytics in Healthcare
Through the integration of human-like reasoning software functions. This technology can perform deductive and inductive analysis for life-sciences applications. In other words, Cognitive AI could provide healthcare workers with a tool to aid them when dealing with patients and individual cases.
Intent-based NLP
Cognitive AI can help businesses improve their analytical abilities in the realms of management and decision-making. Through the usage of this, any future application development of AI can perform logical reasoning. Also, analysis to churn out the particular kind of data that they’re on the lookout for.
Better Cities
With the rapid development that we were chasing. Most of our cities grew exponentially, causing commutation, transportation, water, roads, drainage, and other systems of our cities to run into several issues. To avoid these, we need to manage and track the processes so that hamper the progress of a simple citizen. By making sense of data from traffic cameras, mapping the busiest locations, and rerouting traffic. Cognitive technology can help rescue commuters. Cognitive computing could also assist with traffic management by analyzing social and customer behavior. Considering the aging infrastructure of a city. Analytics will help policymakers determine what, when, where, and how to operate. Or replace such decaying equipment with a smarter city plan, before it affects too many people.
Business Efficiencies
Cognitive computing can identify emerging trends, spot new business opportunities. Take real-time accountability for important process-centered issues. A cognitive computing system can automate procedures, reduce errors, and adapt according to changing circumstances by analyzing a vast amount of data. While this prepares companies to build an appropriate response to uncontrollable circumstances. It helps create effective business processes at the same time. By introducing robotic process automation (RPA), existing systems can improve customer interactions. Because cognitive computing allows only appropriate, meaningful information. Customers will get valuable data. It improves customer experience and thus makes customers happy and much more engaged.
Society Efficient
Nothing hinders the efficiency of someone like poor health, and cognitive technology can help the human race battle some of the most daunting diseases in the world by combining decades of clinical research and patient data with cognitive analytics. It helps physicians to better identify potential risk factors for their patients and place them on a specific health profile for the best treatment plan. For medical practitioners, it provides better diagnostic and medicinal procedures. As for researchers, this technology can reveal trends leading to new, more successful pharmaceutical products. The outcome is an efficient and productive society that is doing its work to the best and more of its abilities.
What Lies Ahead?
Being such a comprehensive and flexible technology, there are immense future possibilities and avenues for cognitive AI in our lives’ business and private segments. Through currently deployed systems, the strength and benefits of cognitive computing are already in use for financial and healthcare realms. In the future, such a system will help humans become more productive than ever before, delegate tedious research, and concentrate on creative work.
