Cognitive computing is a trend over the last few years. This technology is developing at a very fast pace helping businesses to manage and processes an enormous flow of information.
In banking, manufacturing, marketing, customer service, and for research in various fields of science and medicine it is eagerly adopted. However, companies often wonder about the difference between such technologies as cognitive computing and artificial intelligence, and which technology to integrate to maximize their benefits.
Cognitive computing: definition and major benefits
The main task of cognitive computing is to give people an opportunity to work with unstructured data conveniently.
Advancement in AI is giving birth to more and more systems that do not simply follow a given algorithm, but take into account many external factors when working with a huge amount of data; these systems have an ability for self-learning, analyzing human behavior, and using the results of past calculations and external factors. One of these systems is cognitive computing.
Its major benefits are:
- Adaptive: it tracks changes in the information environment, including changes in goals and objectives. Also, it considers unpredictable factors when analyzing information and processing dynamic data providing results in real-time.
- Interactive: it’s user-friendly and convenient to use. Cognitive computing software provides clear and processed information that helps companies to make rational decisions. These systems are easily integrated with other devices, and cloud services.
- Self-learning: cognitive systems remember previous calculations and refer to this information when necessary.
- Contextual: cognitive systems can understand, identify, highlight and make decisions based on contextual information such as value, time, location, user profile, purpose, process, and goal. It resorts to multiple sources of information, including structured and unstructured data, as well as information from IoT devices (if necessary).
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How can your business benefit from it?
Cognitive computing can be implemented in various spheres of business. It allows companies to detect performance issues in their infrastructure, customer service, and other departments. As a result, the productivity of employees and the efficiency of entire departments are increased.
Cognitive technology can be useful for businesses in many ways, including the following:
- Engagement: it boosts individualized services for users and customers by understanding aspects of each customer.
- Expertise: it audits a wide range of the company’s operations, including financial issues. As a result, the company carries out an individual approach to each client.
- Products and services: it helps companies to constantly improve their services by showing the weaknesses that could be improved.
- Science discovery: cognitive technologies are highly adopted in scientific research. Pharmaceutical companies always resort to AI services for drug discovery. For example, it helps them to get implicit data, find molecules with given properties, predict the properties of molecules and synthesize them.
- Decision-making: By identifying more and more dependencies in any information, and working with that data, the system can improve decision-making in a single company or its division.
Today most cognitive computing technologies are cloud-based and offer tools for a variety of business areas. They are easily integrated into existing solutions of the enterprise or company.
Some of the avid examples are:
- Call center services with realistic customer support that uses linguistic recognition and natural language processing technologies (NLP).
- Marketing: software for processing unstructured data, making predictions, graphs, and business recommendations, and increasing business profitability. For example, by processing customer behavior and preferences, the software gives recommendations that can be used to implement effective marketing campaigns.
- Risk management: risk management requires multiple methods of calculation; cognitive technology can provide calculations of all areas of business development, giving an estimate of the profitability of companies.
Understanding the difference between AI and cognitive computing
You may still be wondering isn’t AI and cognitive computing the same thing?
- AI is a broader concept while cognitive computing is a part of artificial intelligence technology.
- AI and cognitive computing use different approaches to make data-driven decisions.
- AI technologies are mainly focused on problem-solving tasks while cognitive computing acts as a supplement to make more informed decisions (for example, AI and cognitive computing must deal with large data sets).
- Then, after analyzing all the data, AI will suggest the best way to solve the problem, while cognitive computing will extract valuable information to support decision-making.
- Thus, it could be said that AI could make better decisions on behalf of humans, while with cognitive technology it is humans who make the final decision.
That makes them closely related. Although they are similar in conception, both technologies have different tasks and principles of work.
Wrapping up
Both technologies use machine learning algorithms, such as natural language processing, to enhance the ability to perform tasks.
In isolation, AI technologies only process huge amounts of data and give you predictions based on this data.
However, one of the fundamental tasks of cognitive computing is sentiment analysis and the ability to understand the context and all the nuances of user behavior. Today, it can recognize basic human emotional expressions from biometrics, gestures, tone of voice, and behavior.
In the future, the combination of these two technologies may revolutionize the way companies make strategically important decisions in complex situations.
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