Cognitive computing is a technology approach that enables humans to collaborate with machines. If you look at cognitive computing as an analog to the human brain, you need to analyze in context all types of data, from structured data in databases to unstructured data in text, images, voice, sensors, and video. These are machines that operate at a different level than traditional IT systems because they analyze and learn from this data. A cognitive system has three fundamental principles as described below:
- Learn—A cognitive system learns. The system leverages data to make inferences about a domain, a topic, a person, or an issue based on training and observations from all varieties, volumes, and velocity of data.
- Model—To learn, the system needs to create a model or representation of a domain (which includes internal and potentially external data) and assumptions that dictate what learning algorithms are used. Understanding the context of how the data fits into the model is key to a cognitive system.
- Generate hypotheses—A cognitive system assumes that there is not a single correct answer. The most appropriate answer is based on the data itself. Therefore, a cognitive system is probabilistic. A hypothesis is a candidate explanation for some of the data already understood. A cognitive system uses the data to train, test, or score a hypothesis.
This chapter explores the foundations of what makes a system cognitive and how this ...