Introduction to Artificial Intelligence – Definition, Scope & Goals

 Artificial Intelligence (AI) is the creation of computer systems that are capable of executing tasks that would otherwise be done by a human, namely learning, problem-solving, and perception. It has very broad applications, such as machine learning, computer vision, and natural language processing, and aims at both automatization of tasks and decision making and the ability of machines to perceive and react to human emotion.

Definition

• AI refers to the capacity of a computer or a program to selflessly replicate the human capacity to think, learn and perceive.
• It is a computer science discipline concerned with designing systems that are capable of addressing problems and performing tasks without being written code to do so on a case-by-case basis.
• Machine learning, pattern recognition, and neural networks are some of the technologies used by AI to analyze information and learn by the experience of its work over time. 

Scope

• Narrow AI (Weak AI): This is the most widespread type of AI whose purpose is to perform a task, which may include the voice assistants, such as Siri, recommendation systems, or image recognition programs.
• Machine Learning and Deep Learning: It is just a subset of AI that learns data with the help of algorithms. Machine learning is a process that works with structured data, and deep learning is a process that operates with multi-layer neural networks.
• Computer Vision: Computer vision is an area of study which teaches computers to perceive and understand what they see in the world allowing applications such as self-driving cars and medical image processing.
• Natural Language Processing (NLP): It is an AI that enables computers to read, comprehend, and produce human language. Examples would be translation services and chatbots.
• Others: This consists of cognitive modeling, pattern recognition, and such as AIOps (AI for IT Operations). 

Goals

• Task Automation: To reduce repetitive and complex jobs in the digital and physical worlds, to liberate human labor, employ it on more creative or strategic work.
• Improved decision-making: To make faster, more accurate, and reliable decisions based on data due to further analytics and predictions.
• Error Reduction: To cut down human error within the processes either by giving them guidance or making them one hundred percent automated, particularly in areas that are very precise such as healthcare.
• Solving Complex Problems: To solve problems that are outside of the human abilities because of their complexity or size.
• Human like Interaction: To develop systems that can comprehend human attitudes and intentions in order to facilitate more advanced and sympathetic interactions as in the case of the “Theory of Mind Objective.