What is Cognitive Computing?
Cognitive Computing can be termed as individual technologies that perform specific tasks to facilitate human intelligence. Therefore, these are intelligent decision assistance systems that have been working with since the beginning of the internet boom. With latest trends in technology, these assistance systems simply use better data, better algorithms in order to get a better analysis of a huge amount of information.
Flexible System:Cognitive systems must be flexible enough to understand the changes in the information. Therefore, the systems must be able to absorb dynamic data in real-time and make necessary changes as the data and environment change.
Collective System:Human and system interaction is a vital component in cognitive systems. Developer must be capable to communicate with cognitive machines and define their needs as those needs change. The system should also be agreed to communicate with other processors, devices and cloud platforms.
Constant and repetition system:These systems are responsible for identifying issues by asking questions or pulling in additional data if the problem is incomplete. This can be done by recording information about identical situations that have lastly occurred.
Sensitive System:This system should recognize, identify and mine contextual data, such as syntax, time, location, domain, requirements, a specific user’s profile, tasks or goals. This process focuses on multiple sources of information, including structured and unstructured data and visual, auditory or sensor data.
Applications of Cognitive AI
IoT Devices:This system deals with connecting and optimizing devices, data and the IoT. By assuming we get more sensors and devices, the real point is what is going to connect them.
AI-Enabled Cyber security:We can prevent the cyber-attacks with the help of data security encryption and enhanced situational awareness powered by AI. This system will supply a document, data, and network locking using smart distributed data secured by an AI key.
Aspect & Surface AI:AI based on cognitive intelligence continuously study and reasons and it can simultaneously integrate location, time of day, user habits, semantic intensity, intent, sentiment, social media, contextual awareness, and other personal attributes.
Healthcare under cognitive AI:This technology uses human-like reasoning software functions that perform derivable, experimental and restoration analysis for life sciences applications.
Purpose-Based NLP: This system can assists a business become more analytical in their approach to take effective management and decision making. This can be referred as the next step from machine learning and the future applications of AI will incline towards using this for performing logical reasoning and analysis.