Unpacking Cognitive AI and Computing, its Workings, and Real-World Applications

Introduction

Hi everyone! Welcome to our post about cognitive artificial intelligence. Before we begin the delve into the topic, let's have a look at today's agenda. 

• So first we will see what is cognitive computing
• And then we will talk about how cognitive computing works. 
• Moving on we will also see what are the differences between cognitive computing and artificial intelligence 
• And then we will also take a use case to understand cognitive AI better. 
• And finally, we will talk about the different applications of cognitive AI 

A cognitive computer or system learn at scale reasons with purpose and interacts with humans naturally rather than being explicitly programmed.

These systems learn and reason from their interactions with human beings and their experiences with their environment, cognitive computing overlaps with artificial intelligence and involves similar technologies to power cognitive applications. 

What is Cognitive Computing? 

So cognitive computing refers to individual technologies that perform specific tasks to facilitate human intelligence. Basically, these are smart decision support systems that we have been working with since the beginning of the internet boom. 

So with recent breakthroughs in technology, these support systems simply use better data better algorithms in order to get a better analysis of a huge amount of information. Not just that you can also refer to cognitive computing as understanding and simulating reasoning, understanding and simulating human behavior. 

Using cognitive computing systems helps in making better human decisions at work. Some of the applications of cognitive computing includes speech recognition, sentiment analysis, face detection, risk assessment and Etc. We'll talk about these in details later. 

How Cognitive AI Works 

So now that you know, what is cognitive computing. Let's move on and see how cognitive AI works. So cognitive computing systems synthesize data from various information sources while weighing context and conflicting evidence to suggest suitable answers to achieve this cognitive systems include self-learning technologies using data mining, pattern recognition and natural language processing to understand the way the human brain works.

Now using computer systems to solve problems that are supposed to be done by humans require huge structured and unstructured data, with time cognitive systems learn to refine the way they identify patterns and the way they process data to become capable of anticipating new problems and model possible solutions. To achieve these capabilities, cognitive computing systems must have some key attributes.

Adaptive 

First of all, it should be adaptive: Cognitive systems must be flexible enough to understand the changes in the information also the systems must be able to digest dynamic data in real time and make adjustments as the data and environment change.

Interactive 

Then another attribute is being interactive: So human computer interaction is a critical component in cognitive systems users must be able to interact with cognitive machines and Define their needs as those needs change. The technology is must also be able to interact with other processors devices and cloud platforms.

Iterative and Stateful

The next one is iterative and stateful: These systems must be able to identify problems by asking questions or pulling in additional data. If the problem is incomplete the systems do this by maintaining information about similar situations that have previously occurred. 

Contextual 

The next attribute is being contextual: Cognitive systems must understand to identify and mind contextual data such as syntax, time, location domain requirements, a specific users profile, tasks or goals. They may draw on multiple sources of information including structured and unstructured data and visual auditory or sensor data. 

Difference Between Cognitive Computing and Artificial Intelligence 

Now cognitive computing is also referred to as subset of artificial intelligence. There are various similarities and differences between the two. So now let's move on and understand the difference between cognitive computing and artificial intelligence.

The technologies behind cognitive Computing are very similar to the technologies behind AI. These include the machine learning, deep learning, NLP, neural networks and Etc, but they do have various differences as well.  

Cognitive Computing focuses on mimicking human behavior and reasoning to solve complex problems. Whereas AI augments human thinking to solve complex problems. It focuses on providing accurate results while cognitive Computing simulates human thought processes to find solutions to complex problems. AI finds patterns to learn or reveal hidden information and find solutions. 

Cognitive Computing also simply supplement information for humans to make decisions. Whereas AI is responsible for making decisions on their own minimizing the role of humans.

And finally, cognitive Computing is used in sectors like customer service, healthcare industries. Whereas AI is mostly used in finance, security, healthcare, retail manufacturing Etc. 

Examples of Cognitive AIs

So now that you have an idea about Cognitive Computing and artificial intelligence combined together, known as the cognitive AI. Let's understand this in a better way with an example. So let's take this use case now cognitive Computing and AI are Technologies that rely on data to make decisions, but there are nuances between the two terms which can be found within their purposes and applications. 

So let us imagine a scenario where a person is deciding on a career change and AI assistant will automatically assess the job seeker skills find a relevant job where his skills match the position, negotiate pay and benefits and at the closing stage. It will inform the person that a decision has been made on his behalf. Whereas a cognitive assessment suggests potential career paths to the job seeker besides furnishing the person with important details like additional education requirements salary comparison data and open job positions.

However, in this case, the final decision must be still taken by the job seeker. Now based on this scenario, we can say that cognitive Computing helps us make smart decisions on our own leveraging machines. Whereas AI is rooted in the idea that machines can make better decisions on our behalf. So these were some of the differences between cognitive Computing and artificial intelligence. 

Applications of Cognitive AI

Now, let's move ahead and talk about some of the applications of cognitive AI in details and see how together it makes some smart technology and makes it simpler for us. 

Smart IoT

So talking about applications, we have the smart IoT. So this includes connecting and optimizing devices data and the IoT, but assuming we get more sensors and devices. The real key is what's going to connect them.

AI Enabled Cybersecurity 

Then we have the AI enabled cyber security so we can fight the cyber attacks with the use of data security encryption and enhanced situational awareness powered by AI. This will provide a document data and network lacking using smart distributed data secured by an AI key. 

Content AI

Then we also have the content AI: So a solution powered by cognitive intelligence continuously learns and reasons and can simultaneously integrate location, time of day, user habits, semantic, intensity, intent, sentiment, social media, contextual awareness and other personal attributes. 

Cognitive Analytics and Healthcare 

The technology implements human-like reasoning software functions that perform deductive, inductive and abductive analysis for life sciences applications. And finally, we have the intent based NLP. So cognitive intelligence can help a business become more analytical in their approach to management and decision-making now, this will work as the next step from machine learning and the future applications of AI will incline towards using this for performing logical reasoning and analysis.

So these are some of the common applications of cognitive AI and also how it is going to change the world of technology and with this we have come to the end of today's post and I hope you have understood how this cognitive computing system is a subset of artificial intelligence and how together both of these can do wonders. 

Conclusion 

Now, don't forget to let us know about your opinion in the comment section below till then. Thank you and happy learning. I hope you have enjoyed reading to this post. Please be kind enough to share it and you can comment any of your doubts and queries and we will reply them at the earliest, do look out for more posts in our content gallery and follow to Blueguard to learn more.

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