What is Artificial intelligence?

Artificial Intelligence (AI) simulates human intelligence in machines programmatically imitating the human capabilities of learning, thinking, and sensing. AI is the study of systems that appears to be intelligent. But before that, we need to define “What is intelligence?” Here, intelligence can be defined as the properties then machine exhibits, like the ability to deal with situations or solve complex problems, devise plans, and so on. Machine intelligence that is as smart as human intelligence may be a part of imagination which is centuries old but became part of modern science with the rise of digital computers. In many cases, AI can solve from relatively simple to complex problems that are internal to more complex systems. Interestingly, AI involves using techniques based on the intelligent behavior of humans to solve complex problems.

To explain more, Artificial intelligence is the deception of human intelligence processes by machines, especially computer systems. This umbrella term covers Robotics process automation, Machine Learning, Deep Learning, Machine Vision, Natural Language Processing, Pattern recognization, Robotics, etc. Introduced by John McCarthy, the American Computer Scientist at The Dartmouth Conference in 1956, it has gained prominence due to big data and its role in increasing the speed, size, and variety of data businesses. Artificial Intelligence can do the tasks such as recognizing data patterns more efficiently than humans, enabling businesses to achieve more details of their data. Artificial intelligence has gained significant importance in almost all domains like healthcare, business, education, finance, law, and manufacturing.

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Components of AI

1. Natural Language Processing (NLP)

2. Knowledge representation

3. Reasoning

4. Problem solving

5. Machine learning

What is an Expert system?

There are several research areas of AI, and expert systems are one of the prominent areas among them. This is the most successful demonstration of AI capabilities that represents truly commercial application of the work done in the field of AI. Like other AI programs, expert systems are computer programs that simulate the human expert thought process to solve complex decision problems in a specific domain. 

In other words, an expert system is a knowledge-based system that employs knowledge about its application domain and uses an inferencing (reason) procedure to solve problems that would otherwise require human competence or expertise. The power of expert systems comes primarily from the expert system’s knowledge base that stores specific knowledge about a narrow domain. Unlike other streams of AI, expert systems do not have human capabilities. It is the knowledge base that works as the center of a particular domain. Also, the knowledge base of an expert system also contains heuristic knowledge – rules of thumb used by human experts who work in the domain.

Components of expert system:

1. Inference engine

2. Knowledge base

3. User interface

4. Knowledge acquisition module

Characteristics of an Expert System : 

• Human experts are not permanent, but an expert system is permanent.
• One expert system can be more efficient as it may contain more than one human expert knowledge.
• It helps to distribute the expertise of a human.
• Widely used in medical diagnosis, the expert system decreases the cost of consulting of an expert.
• It is based on the knowledge base and inference engine.
• By deducing new facts through existing facts of knowledge, expert systems can solve complex problems. It uses if-then rules rather than conventional procedural code.
• Expert systems are among the first truly successful forms of artificial intelligence (AI) software.

AI vs. Expert system

1. Definition:

Artificial Intelligence – Artificial intelligence is the deception of human intelligence processes by machines, especially computer systems.

Expert system – Expert systems are computer programs that simulate the human expert thought process to solve complex decision problems in a specific domain.

2. Components

Artificial Intelligence – It is an umbrella term that covers Robotics process automation, Machine Learning, Deep Learning, Machine Vision, Natural Language Processing, Pattern recognization, Robotics, etc.,

Expert system – Components of expert system cover Inference engine, Knowledge base, User interface, Knowledge acquisition module.

3. Applications

Artificial Intelligence – AI is used in a wide range of industries. Some of them are healthcare, finance, automotive, transport, social media, travel, data security, etc.

Expert system –  The application of an expert system can be found in almost all areas of business or government. They include areas such as –

• Different types of medical diagnoses like internal medicine, blood diseases, and show on.
• Diagnosis of the complex electronic and electromechanical system.
• Diagnosis of a software development project.
• Planning experiments in biology, chemistry, and molecular genetics.
• Forecasting crop damage.
• Diagnosis of the diesel-electric locomotive system.
• Identification of chemical compound structure.
• Scheduling of customer orders, computer resources, and various manufacturing tasks.
• Assessment of geologic structure from dip meter logs.
• Assessment of space structure through satellite and robot.
• The design of the VLSI system.
• Teaching students specialized tasks.
• Assessment of log, including civil case evaluation, product liability, etc

4. Capability

Artificial Intelligence is the study of systems that act so that any observer would appear to be intelligent.

Expert system –  There are several research areas of AI, and expert systems are one of the prominent areas among them. This is the most successful demonstration of AI capabilities that represents truly commercial application of the work done in the field of AI.