Artificial Intelligence: The New Fuel for Digital Transformation
McCarthy coined the term “artificial intelligence” in 1955. He defined AI as
“The science and engineering of making intelligent machines, especially intelligent computer programs”.
AI pursues to create machines as intelligent as humans. The idea is to imitate human logic reasoning and rationale. Humans learn from past experiences but computer programs follow instructions. Now the question is: Can computers also learn based on experiences? The answer is Yes.
Domain of AI
The original 7 aspects of AI:
- Simulating higher functions of the human brain.
- Programming a computer to use general language.
- Arranging hypothetical neurons in a manner so that they can form concepts.
- A way to determine and measure problem complexity.
- Abstraction: Defined as the quality of dealing with ideas rather than events.
- Randomness and creativity.
Types of AI: Broadly, AI technologies are classified into two types as described below:
(i) It is a stimulation of human behavior.
(ii) Such systems don’t have reasoning capabilities of a human.
(iii) They work under human observation.
(i) It can do anything as well/better than a Human.
(ii) The machine can take decisions like humans.
(iii) Doesn’t require human interference.
(iv) Doesn’t exist yet.
Different types of AI
The AI system is composed of an agent and its environment.
The agent has two components: Sensors and Effectors. The Sensor is anything through which an agent can perceive its environment. While Effectors are actuators through which agents act upon the environment.
Types of Agents
Let’s have a look at some of the prominent areas of AI:
(i) Expert Systems: An expert system emulates human intelligence and expertise. They are developed to solve the problem in a particular domain.
(ii) Robotics: Robotics deals with artificial agents (Robots). It smuggles with the design, construction, operation, and robots utilization, moreover exert computer systems for their control, sensory feedback, and information processing.
(iii) Neural Networks: Artificial neural networks (ANNs) are computing system inspired by biological neural networks of human brains.
(iv) Fuzzy Logic: It is a method of reasoning that resembles human reasoning. It takes inputs which are not true or false, is ambiguous, inaccurate and produces definite output.
(v) Natural Language Processing: It deals with the interaction between humans and computer systems. We can deal with NLP systems in natural language. For example: google search.
It was the overview of Artificial Intelligence. AI is a very vast field to be able to grasp in one article. Each of the applications is a complete subject of study.