Cognitive Computing

What is cognitive computing?

Cognitive computing refers to the use of reasoning, language processing, machine learning, and human capabilities that help regular computing better solve problems and analyze data. By learning patterns and behaviors and becoming more intelligent, a computer system can tackle complex decision-making processes. 

Features of cognitive computing

A cognitive computing technology platform uses machine learning and pattern recognition to adapt and make sense of information, even unstructured information like natural speech. To achieve those capabilities, cognitive computing typically provides the following attributes, which were developed by the Cognitive Computing Consortium in 2014:

Adaptive Learning: Cognitive systems need to accommodate an influx of rapidly changing information and data that helps to fulfill an evolving set of goals. The platforms process dynamic data in real-time and adjust to satisfy the surrounding environment and data needs.

Interactive: Human-computer interaction (HCI) is an essential part of cognitive machines. Users interact with cognitive systems and set parameters, even as those parameters change. The technology interacts with other devices, processors, and cloud platforms.

Iterative and stateful: Cognitive computing systems identifies problems by posing questions or pulling in supplementary data if a fixed query is incomplete or vague. The technology makes this possible by storing information about related situations and potential scenarios.

Contextual: Cognitive computing systems must identify, understand, and mine contextual data, such as time, syntax, domain, location, requirements, or a specific user’s tasks, profile, or goals. They may draw on multiple sources of information, including auditory, visual, or sensor data as well as structured or unstructured data.


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How is cognitive computing used

Cognitive computing uses technologies like signal processing and machine learning to facilitate interaction with humans. Think about the last time you chatted with a customer support bot or gave a command to a personal digital assistant like Siri or Alexa. They’re helpful, but often pre-programmed responses limit the interaction. They are unable to read emotions or give complex responses like HAL from the movie 2001: A Space Odyssey. That level of functionality may be available in the future. 

However, the field of cognitive computing is progressing fast, with new applications in the business and education fields, and even the healthcare industry. IBM’s Watson for Oncology uses natural language processing and advanced cognitive algorithms that doctors can employ to determine the best treatments for cancer patients. Outdoor clothing company North Face recently used Watson to develop a customized online shopping experience. The software uses cognitive computing solutions to help customers curate their search and find the most relevant recommendations.

What value does cognitive computing provide?

One useful feature of cognitive computing is its ability to extract useful information from complex data. With almost every company encountering an increasing amount of data to stay competitive, BI platforms like Sisense are more important than ever. These platforms use cognitive computing technologies to produce data analytics that are easier to interpret by non-technical employees. Sisense’s tools utilize features like natural language processing (NLP) to communicate insights in conversational language. This reduces accidental misinterpretations and provides everyone with an objective analysis of the facts within the data.

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Disadvantages of Cognitive Computing

The limitations of cognitive computing necessitate caution when incorporating this technology into its various and widespread applications. These can include security risks, as these systems handle large amounts of data and may be vulnerable to breaches. Another challenge is the lengthy development time that a highly complex technology needs to get off the ground. This may make it harder for companies with smaller development teams to develop applications with integrated cognitive computing processes. 

In summary

There’s no question that cognitive computing will transform the world in dramatic ways in the coming years. The possibilities and applications are immense, from improving the customer experience to making manufacturing processes more efficient to making our streets safer.  Harnessing the power of cognitive computing can mean huge steps forward for businesses, schools, the environment, and quality of life for everyone.

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