What is Cognitive Computing?Cognitive means relating to the mental process involved in knowing, learning, and understanding things. Cognitive Computing refers to an individual technologies that acts specifically to support human intelligence. When internet has been at it's initial stage, that time itself smart decision support systems have been established and with recent breakthroughs in the technological advancements, data are used in exceptional manner with better algorithms to have better analysis of the ample amount of data and information.
We can refer to Cognitive Computing as :-
Understanding and simulating reasoning
Understanding and simulating human behavior
By making use of cognitive computing system better decisions can be made by humans while working. Taking an instance, the applications of cognitive computing comprises of speech recognition, sentiment analysis, face detection, risk assessment, and fraud detection.
How Cognitive Computing AI actually works :-
Cognitive Computing works on the principle that data is assessed as per information sources while weighing context and conflicting evidence to suggest suitable answers. This can be done by indulging self-learning technologies using data mining, pattern recognition, and natural language processing (NLP) to understand the way the human brain works. Solving problems by using various algorithms along with structured and unstructured data that matches the human's intelligence. With improved technology, cognitive systems has learned the refining of methods of identifying and solving complex and multi faceted troubles.
To achieve these capabilities, cognitive computing systems must have some key attributes.
Key Attributes
Adaptive: Cognitive systems must be flexible enough to understand the changes in the information.
Interactive: Human-computer interaction (HCI) is a important component in cognitive systems.
Iterative and stateful: Also, these systems must be able to identify problems by asking questions or pulling in additional data if the problem is incomplete.
Contextual: Cognitive systems must understand, identify data, such as time, location, domain, requirements, a specific user’s profile, tasks or goals.
Cognitive Computing vs AI
The technologies behind Cognitive Computing are similar to the technologies behind AI. These include machine learning, deep learning, NLP, neural networks, etc. But they have various differences as well.
Applications of Cognitive AI
Smart IoT: This includes turning online and every minute data can be captured which helps in connecting and optimizing devices, data and the IoT. Deeper we dig, more proficient it will be.
AI-Enabled Cybersecurity: Thus way we can fight the cyber-attacks with the use of data security encryption and enhanced situational awareness powered by AI. Data interpretation, documentation and distribution among the network helps in absolute surveillance and tracing.
Content AI: AI offers tremendous scope of improvement in the learning new skills, hobbies, it keeps the records of our improvement and satisfaction can be achieved. Social media, chatting apps, and several other applications are giving unbounded platform for growing and evolving.
Cognitive Analytics in Healthcare: The technology implements human-like reasoning software functions that perform deductive, inductive and abductive analysis for life sciences applications.
Intent-Based NLP: Cognitive prudence is supporting the entrepreneurs in setting up the business become more analytical in their approach to management and decision making. ChatGPT is acting like a technical guruji and fruit bearer for the young entrepreneurs. This will be a machine learning and application based cognitive Computing modeling.
Cognitive Computing Artificial Intelligence
Cognitive Computing works by mimicking human behavior and reasoning to solve complex problems. AI augments human thinking and stimulates the human thoughts to solve complex and critical problems. Accuracy and precision results are the priority. AI studies the patterns and sequence to unhide the information and thus results can be drawn to much unsolved mysteries which is fruitful to humans in formation of final decisions. We are using it in sectors like customer service, health care, industries, etc. It is mostly used in finance, security, healthcare, retail, manufacturing, etc.
For example, when an individual is searching for a job. AI will be assessing the job seekers' skills, location, requirements and finds a suitable position that matches that individual needs and keep on suggesting the best options and thus delight of that individual can be met.
Quoting AI, on our machine Stenter at textile industries, where online monitoring of the consumption can be quoted and graphical representation helps in making suitable changes while running the process so that fuel consumption can be controlled.
AI is rooted in the idea that machines can make better decisions on our behalf.
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