Figure 1.3 Showing the evolution of Cognitive Computing [13].
In today’s world with a lot of sensors around a lot of data is being generated all the time in many forms. The evolution of cognitive computing is to make a sense in this multifaceted world with this large volume of data. The older technologies have been developed to make sense with the structured data and machines, software is also developed to deal with such type of data and gathering information from the structured data. The growth of social site and apps have impacted the growth in the unstructured and semi-structured data and these older technologies are no more a way to handle these types of data and the cognitive computing helps in gathering the information from all types of data Unstructured, Semi-structured, and Structured data. Without the handling of these different types of data, a lot of information can be missed and the cognitive computing is going to help the humans to collaborate with the machines so that a maximum gain can be extracted from them. In the past also we have seen the technology had transformed the industries and also the human way of living from the last decades. Transactional processing had started in the 1950s had brought a lot of transformation in government operations and also in business transactions, giving a lot of efficient ways to deal with the operations. During that time the data was limited and major data is structured data and tools are developed to handle this type of data and many mining tools are developed to extract the information from that data. A large amount of data cannot be handled by the traditional tools and methods, so we need a mixture of traditional methods with traditional technical models with the innovations to solve the niggling problems.
1.4 Difference Between Cognitive Computing and Artificial Intelligence
Although it was stated that the foundation for cognitive computing is artificial intelligence there is a lot of difference between the two.
The basic use of artificial intelligence is to solve the problem by implementing the best algorithm, but cognitive computing is entirely different from artificial intelligence as cognitive computing adds the reasoning, intelligence to the machine and also analyzes different factors to solve the problem.
Artificial Intelligence mimics the human intelligence in machines. This process comprises making the machines learn constantly with the changing data, making sense of the information, and taking decisions including the self-corrections whenever needed.
Human beings use the senses to gather information about the surrounding environment and process that information using the brain to know about the environment. In this context, we can define that artificial intelligence can also include replicating the human senses such as hearing, smelling, touching, seeing, and tasting. It also includes simulating the learning process and this is made possible in the machines using machine learning and deep learning. Last but not least is human responses achieved through the robotics [18].
The cognitive computing is used to understand and simulate the reasoning and human behavior. Cognitive Computing assists humans to take better decisions in their respective fields. Their applications are fraud detection, face and emotion detection, sentiment analysis, risk analysis, and speech recognition [17].
The main focus of cognitive computing includes
1 To solve complex problems by mimicking human behavior and reasoning.
2 Trying to replicate the humans in solving the problems
3 Assists the human in taking decisions and do not replace humans at all.
Artificial Intelligence focus includes
1 To solve complex problems it augments human thinking, it tries to provide accurate results.
2 It tries to find new methods to solve problems which can potentially be superior to humans
3 The main intent of AI is to solve the problem utilizing the best algorithm and not simply mimicking the human brain.
4 The human role is minimized in taking the decisions and artificial intelligence takes over the responsibility.
The main advantage that needs to be highlighted is that Cognitive Computing does not pose any threat to humans. Cognitive computing helps in assisting human beings in taking better decisions in their tasks, endowing human beings with high precision in analyzing the things, same time having everything under their control. In the case of the health care system, cognitive computing assists the specialists in the diagnosis of the disease using the data and advanced analytics, by which it helps to take quality decisions by the doctors [10]. In Figure 1.4 we can see the growth of Cognitive Computing in various continents. In Figure 1.5 we can see the growth of revenue in the various locations of the world.
Figure 1.4 Global cognitive market [17].
Figure 1.5 Global cognitive market revenue, by geography [17].
1.5 The Elements of a Cognitive System
Several different elements constitute the cognitive system, starting from hardware and operational prototypes to modern machine learning algorithms and applications. Figure 1.6 gives a general design for building a cognitive system.
1.5.1 Infrastructure and Deployment Modalities
The system needs to meet the demands of the industries as they continuously grow and the infrastructure should be flexible to carry on the applications required for the industry. A large amount of data is required to be processed and managed; this data consists of both public and private data. Cloud infrastructure services are required and constant support should be given, providing a highly parallel and distributed computing environment.
Figure 1.6 The general design of a cognitive system [11].
1.5.2 Data Access, Metadata, and Management Services
Data is the most important point where cognitive computing revolves around, so the data collection, accession, and maintaining it must have a very important role. A lot of essential services are required for adding the data and also using it. To ingest the data utmost care should be taken to check the source from which the data is originated. As a result, there is a requirement that data should be classified based on the origin of data, as it is required to check the data source was trusted