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Artificial Intelligence Essay Sample

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Artificial Intelligence Essay Sample

Artificial Intelligence (AI) is the branch of computer science, which concentrates on the intelligence of machines, and involves applying the principles of reasoning, knowledge planning, learning, communication, perception, and controlling objects to emulate the human brain. The most recognizable AI application is robotics from Hollywood cinema, and includes films such as; I Robot, Transformers, Wall-e, WarGames, A.I., The Terminator, Robocop, Iron Man, and Star Wars to name a few, which is fictional not an actual representation of AI. Robotics applications is only one of three aspects of AI, which also includes Cognitive Science applications, and Natural Interface applications, however, the area businesses are finding the most useful is the Cognitive Science applications (Murugavel, 2014). Cognitive Science Applications

The Cognitive Science area of AI concentrates on how the human brain functions, and the way it thinks and learn. The research on how humans process information is then transformed into various computer-based applications, which includes Expert Systems, Neural Networks, Genetic Algorithms, Intelligent Agents, and Virtual Reality (Murugavel, 2014). Expert Systems

Expert systems use a combination of knowledge-base and software components, which uses stored knowledge to form a conclusion, and then delivers the answer to users’ requests. Expert systems and knowledge-based information systems are the most common AI application used in businesses. Expert systems uses specific areas of knowledge, which emulates an expert consultant to users, and also provides details on how it arrived at its’ conclusion. Figure 1 shows the components of expert systems, and the flow of knowledge (Murugavel, 2014).

Figure 1: (Murugavel, 2014)
Expert systems application categories include;
Decision Management – Systems that examine situations, and provide recommendations based on knowledge given during the discover process (Murugavel, 2014). Examples include; Loan Portfolio Analysis

Employee Performance Evaluation
Insurance Underwriting
Demographic Forecasts
Diagnostic/Troubleshooting – Systems that identify possible causes from reported symptoms and history (Murugavel, 2014). Examples include; Equipment Calibration
Help Desk Operations
Software Debugging
Medical Diagnosis
Design/Configuration – Systems that use existing constraints to help configure equipment components (Murugavel, 2014). Examples include; Computer Option Installation
Communication Networks
Selection/Classification – Systems that help users select options from large or complex sets of alternative (Murugavel, 2014). Examples include; Material Selection
Delinquent Account Identification
Information Classification
Suspect Identification
Process Monitoring/Control – Systems that monitors and controls processes or procedures (Murugavel, 2014). Examples include; Machine Control
Inventory Control
Production Monitoring
Chemical Testing
Neural Networks
Neural networks emulate the human brain’s neurons, which is a mesh-like network of interconnected processing components. This allows the system to
process numerous pieces of information at the same time, and can learn to understand patterns within the processes, which it can use to solve related problems on its own. Examples include; Military Weapons Systems

Voice Recognition
Check Signature Verification
Manufacturing Quality Control
Image Processing
Credit Risk Assessment
Investment Forecasting
Data Mining
(Murugavel, 2014)
Genetic Algorithms
Genetic algorithms use Darwinian’s survival of the fittest, randomizing, and mathematical functions to emulate evolutionary processes, which provide more accurate solutions to problems. Genetic algorithms are optimal for problems with an infinite number of solutions, and in a matter of minutes can produce the best solution for the problem. Genetic algorithm software uses predetermined set of process rules, which identifies what combination processing steps is relevant to the given problem. The process steps include; mutation, crossover, and selection to reach the best possible solution (Murugavel, 2014). Intelligent Agents

Intelligent agents is software that helps fulfil end-users or processes requests, which uses built-in and learned knowledge base on a person or process to make decisions and complete tasks, in order to reach the expected outcome. The most common form of intelligent agents is wizards, which asks a series of questions, and takes the answers to create the final project. The use of intelligent agents is on the rise, because it simplifies using software, searching websites, and comparison-shopping on e-commerce sites (Murugavel, 2014). Virtual Reality

Virtual reality is a computer generated world, and uses multisensory interfaces, which allows end-users to experience real-world situations. Examples include; Computer Aided Design
Medical Diagnostics and Treatment
Scientific Experimentation
Flight Simulation
Product Simulation
Employee Training
(Murugavel, 2014)
AI has a lot to offer businesses besides killer robots, especially with “Big Data” on the rise, which drastically increases the amount of information stored, and used. The benefits of AI applications to businesses include; predicting human behavior; assisting decision-makers; improving operational efficiency, customer satisfaction and knowledge workers productivity, which reduces overhead costs, thus increasing revenues.

Murugavel, K.N. (2014). Scribd. Retrieved from http://www.scribd.com/doc/93120964/Chapter-5-Decision-Support-System

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