Introduction to Cognitive Intelligence
Machine Learning, Cognitive Intelligence, and Artificial Intelligence have gained immense popularity over the years. Machines or systems that use these technologies have algorithms and greater computing power that helps us to easily solve problems. Machine Learning, Cognitive Intelligence, and Artificial Intelligence may change the way businesses operate and how they make decisions.
Most intelligence machines are able to reason and process natural language on the basis of statistical, logical, and operational methods. However, the abilities of the intelligence machines will depend on the features of their algorithm. The cognitive abilities of these intelligent machines will help you with the autonomous processing of large amounts of data. In addition, it will assist you to make better business decisions.
As a result, these machines will help businesses considerably reduce the chances of human error. By offering better and efficient solutions to several business tasks, these intelligent machines allow businesses to boost productivity and offer a better experience to customers.
Artificial Intelligence Will Be An Important Part Of Business’ Investments
Artificial Intelligence is a popular and emerging trend that has already captured the attention of several large and small-scale businesses. It is evident that AI is going to be an integral part of several companies’ research and investment. Businesses who are trying to optimize their day-to-day operations and the ones who wish to make better decisions with reduced human errors should consider using intelligent machines.
Over the last few years, we were able to see several data-driven companies heavily relying on analytics to make smart and informed business decisions. Most of these companies have already invested in software developed based on the concept of machine learning to get a better understanding of customer behavior and other important business metrics.
The Increasing Popularity Of Cognitive Intelligence
Cognitive intelligence can be defined as a new and innovative type of commercial AI, which is capable of meeting the growing demands of complex human and machine interactions. It is crucial to note that cognitive intelligence is here not to replace big data or machine learning. Instead, it has been introduced to keep track of and monitor how traditional AI fills gaps, processes data, and identifies misinterpretations.
In simple words, the primary goal of cognitive intelligence is to perform complex tasks without human supervision, process unfamiliar input quickly, and adjust the response accordingly. Now, let us take a quick look at cognitive intelligence’s business applications.
Smart Internet of Things (IoT)
Optimizing and connecting devices, data, and the Internet of Things (IoT) will be one of the major business applications of cognitive intelligence. Cognitive IoT can be defined as an environment or network, where everything and everyone is connected. It is evident that the concept of the Cognitive Internet of Things will be able to achieve intelligence and considerably improve performance.
Cognitive AI will be able to offer situational awareness to several devices and make them all work together to resolve issues. Let us consider an oil rig that has thousands of sensors. The rig that is in the ocean will need a connection to offer data, but most rigs lack access to faster internet connections, which means you can’t use cloud service AI. In such a case, the Cognitive Internet of Things can help you easily overcome the issue.
If artificial intelligence becomes complex or sophisticated, then it may result in more cybersecurity attacks. In fact, several sources claim that such a situation may even result in a huge surge in the number of cyberattacks. The increased number of cyberattacks will result in more social engineering attacks and the explosion of several network penetrations.
It is crucial to remember that artificial intelligence becoming sophisticated will also increase the chance of computer virus attacks. Fortunately, we will be able to prevent the chance of this by using enhanced situational awareness and data security encryption. This will in turn offer data, document, and network locking with the help of smartly distributed data, which is secured by an Artificial Intelligence key.
Next Generation Search
Most of us use Google every day to search for products, read the news, check sports updates, and for more. There is no denying the fact that the search engine giant, Google does an excellent job of displaying results to each search term we enter. In fact, we get results that are filtered from approximately billions of different web pages.
That said, the results that Google shows us doesn’t always help us resolve issues or answer our query. Google makes use of an algorithm that ranks web pages based on keywords and other factors. The need of the future is for a search engine that offers relevant and highly accurate results. It is safe to assume that an AI will be soon used to achieve the above-mentioned results.
Content marketing is a powerful and effective strategy that is used by several companies to attract more customers to their offerings. Most businesses that are investing in content marketing have a writer or group of writers who created unique and relevant content on a regular basis. Think about a future, where the content requirements of your business are handled by an AI.
One of the few companies that have been trying to understand the content marketing business is Atomic Research. The company has been trying to measure the language characteristics in content with their AI-powered platform. The platform also helps the company to analyze the audience’s reading behavior, which will help the company to customize its content even more.
It might come as a huge surprise to many readers when they hear that a novel, which was written by an AI-program, made it into the first phase of content in Japan. The novel failed to get the character description right and it didn’t win the contest, but this gives us an idea on AI could have a huge impact on content marketing too in the future.
A cognitive system or computer reason with purpose learns at scale and naturally interacts with humans. Instead of being explicitly programmed to perform processes or do things, cognitive systems learn from experiences and human interactions.
The concept of cognitive computing actually overlaps with AI and it also uses similar kinds of technologies to power cognitive apps. If you are new to the concept of cognitive computing, here are a few things you should know about it.
What Is Cognitive Computing
The term cognitive computing actually refers to individual technologies, which perform certain tasks for facilitating human intelligence. Several companies and businesses have been actively working with smart decision support systems ever since the introduction of internet services. However, the latest advancements in the field of technology have allowed these support systems to use better algorithms and data to offer a better analysis of large amounts of data or information.
It goes without saying that businesses who use cognitive systems will be able to make better business decisions. Some of the most common applications of cognitive computing are fraud detection, risk assessment, face detection, sentiment analysis, and speech recognition. Now, let us take a quick glimpse into how cognitive AI really works.
How Does Cognitive Computing Work?
Cognitive computing systems serve the crucial purpose of synthesizing data from different sources. The best thing about these systems is that they weigh in factors like context and conflicting evidence to offer the best solutions. Cognitive systems achieve this by including self-learning techniques with the help of pattern recognition, natural language processing, and data mining to understand how the human brain works.
The use of computer systems to solve problems that are usually solved by humans requires large amounts of unstructured and structured data. Cognitive systems gradually refine the way they detect problems and the way they process data. This in turn makes the systems capable of anticipating new issues and coming up with suitable solutions.
Key Attributes Of Cognitive Computing Systems
Cognitive systems must have these key attributes if they want to achieve this. For instance, cognitive systems should possess the ability to understand the change in data or information. In addition to that, these systems must be capable of digesting dynamic data in real-time and make necessary changes as the environment and data change.
Another critical component in cognitive computing systems is HCI or Human-Computer Interactions. Users should be able to interact with the systems and define requirements. It is important to note that the technologies must be able to interact with cloud platforms, devices, and processors.
AI and cognitive computing are technologies that make use of data for making decisions. Let us consider a scenario, where someone is looking for a career change. An AI assistant will help the candidate find a job that matches his skills, negotiate pay, and it will notify the candidate that a decision has been made for him.
On the other hand, a cognitive assistant will list a number of potential career choices for the candidate along with relevant job details like salary, education requirements, and more. Finally, the decision has to be made by the candidate itself when he or she is using a cognitive assistant.