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    What is Cognitive Computing – Use Cases, Differences from AI

    What is Cognitive Computing – Use Cases, Differences from AI

    Tracy Watson


    7 min read

    what is cognitive computing

    Ever since the computer was first invented, computer scientists tried to program it to mimic human behavior. The origins of the computer date back to the 1960s, and the technology to make this dream happen simply did not exist back then. However, in the twenty-first century, this vision is finally coming to fruition thanks to cognitive computing. In this article, we will take a closer look at cognitive computing as well as its practical applications.

    Cognitive Computing Definition

    Cognitive computing enables machines to actually think and learn the same way that humans do. This involves using self-learning algorithms that rely on various processes that all come together and allows the computers to simulate the way a person’s brain works. While computers have been better than human beings at things like calculations and other complex processes for quite some time now, they have struggled to complete simple tasks such as recognizing objects or regular speech.

    An excellent example of cognitive computing is IBM’s Watson. It became famous for winning Jeopardy and defeating all of the previous winners. Systems like Watson are trained by exposing it to a lot of data, and the cognitive software will improve as the technology matures.

    Cognitive computing vs. Artificial intelligence

    In case you are wondering how this differs from AI, you have to take a look at the goals of each technology. Cognitive computing does not want to replace humans completely but rather help them perform certain tasks. It tries to create a machine that thinks like a human being. This is different from AI, which just tries to use the best algorithm to solve a particular problem.

     What you get with cognitive computing include:

    • Enhanced analysis and plans – Cognitive systems can assemble all of the necessary information, analyze it, and provide you with answers or recommendations on how to solve certain problems.
    • The machines shoulder the analysis burden – You no longer have to analyze data to look for patterns and identify potential opportunities yourself. The cognitive system can do this for you by analyzing large quantities of data in a short period of time.
    • Better customer service – The chatbot that will communicate with customers can find the information they are looking for quickly and provide only contextual information.

    Disadvantages include:

    • Security – While the system will have access to a large amount of data, this can pose certain security challenges. There need to be better mechanisms in place to identify suspicious activity.
    • Adoption – Whenever a new technology emerges, there are some inherent adoption issues. Therefore, there needs to be more of a collaboration between all of the stakeholders to streamline the process.
    • Long development cycles – Currently, the development of cognitive intelligence is focused on scenario-based applications. Not only does this increase the development cycle, but it prevents the technology from becoming implemented across industries.

    Now that we know some of the pluses and minuses of cognitive computing let’s take a look at what it is capable of.

    cognitive software

    What is this Technology Capable of?

    There are a lot of cognitive computing use cases that vary across industries. For example, if we continue with the topic of Watson mentioned above, this technology can be used in the medical field to help analyze the vast amount of information and make recommendations. It can also help doctors diagnose patients by scanning X-rays and identifying whether or not certain diseases or other issues are present. Not only will this improve accuracy and patient care, but it will also help take some of the workloads off the shoulders of doctors who can focus more on working with patients.

    Some cognitive computing is used today in cars that help us navigate on the road. For example, object recognition technology can alert us if we are coming dangerously close to another vehicle or even hit the breaks for us if we become distracted. You can expect such technology to become even more popular as self-driving cars become increasingly available.

    What Can We Expect to See in the Near Future?

    Cognitive computing has taken the tech industry by storm, and it is easy to see why. The upside of the technology is huge, especially since it can automate a lot of the manual processes that we have now. There are a lot of possibilities for the B2B and B2C segments because it allows companies to manage their business activities with greater efficiency and spot opportunities where nobody ever bothered to look.

    cognitive computing definition

    We can expect the obstacles mentioned above to be resolved as the technology matures and becomes more advanced, and we can expect to start seeing a mass transition to adopt cognitive computing in businesses across industries. Therefore, it is a good idea to start investing in future tech solutions to solve some of the problems that you have today, so you will have an advantage over your competitors who are just starting to adopt cognitive computing.

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