Cognitive Computing, a subfield of Artificial Intelligence, simulates human thought processes in machines using self-learning algorithms through data mining, pattern recognition, and Natural Language Processing. These artificial environments rely on Deep Learning algorithms and neural networks to process information by comparing it to a teaching set of data. By mimicking human thought processes, computers help people make better and easier decisions. Given these machine-human interactions, Cognitive Computing can also be described as Augmented Intelligence.
Cognitive Computing Use Cases include:
- Delivering actionable sporting tips to athletes during a game or competition.
- Providing better knowledge about diseases and the course of treatment for patients.
- Advising investment strategists on leveraging information to make decisions buying or selling in a marketplace.
- Enabling blind or visually impaired people to navigate around physical space.
- Responding to the emotional tone from an audience to a change of clothing color.
Other Definitions of Cognitive Computing Include:
- “A mashup of cognitive science—the study of the human brain and how it functions—and computer science.” (Bernard Marr, Forbes)
- “Systems that learn at scale, reason with purpose and interact with humans naturally.” (Peter Sommer, IBM)
- “Technology platforms that, broadly speaking, are based on the scientific disciplines of Artificial Intelligence and Signal Processing.” (International Conference on Cognitive Computing)
Businesses Use Cognitive Computing to:
- Do Augmented Analytics.
- Identify trends and patterns to deliver actionable recommendations.
- Understand human language and interact with customers and workers more naturally.
- Assess risks in real time.
- Produce accurate results (if the data sets are good).
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