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Artificial intelligence (AI) and artificial general intelligence (AGI) are often used interchangeably. However they represent distinct concepts within the broader field of AI. In this article we will dive deep into the differences between AI and AGI, exploring their definitions, historical developments, applications and challenges. By the end of this article you will have a clear understanding of these two groundbreaking technologies and their implications for the future.
What is Artificial Intelligence (AI)?
AI refers to machines or systems that can perform tasks that typically require human intelligence. These tasks include learning, problem solving, pattern recognition, understanding natural language, perception and decision making. AI systems can be classified into two main categories:
1. Narrow AI (or weak AI): This type of AI is designed to perform specific tasks without possessing general human like intelligence. Examples include recommendation systems virtual assistants like Siri and Alexa and image recognition software. Narrow AI is task specific and cannot perform tasks outside its designated scope.
2. Artificial General Intelligence (AGI): Also known as strong AI, AGI refers to machines or systems that possess human like intelligence and can perform any intellectual task that a human being can do. This type of AI is still theoretical as no such system exists yet. Unlike narrow AI, AGI can understand or learn any intellectual task a human can perform.
Historical Developments
AI: A Brief History
The idea of AI dates back to ancient Greek myths of automatons and human like machines. However, the modern concept of AI was born in the mid 20th century. Alan Turing a British mathematician is often credited as the founding father of AI due to his work on the Turing Test. The test, proposed in 1950 aimed to determine if a machine could exhibit intelligent behavior indistinguishable from a human.
In the following decades researchers began developing AI algorithms and systems. Early AI work focused on rule based systems which relied on pre defined rules to make decisions. In the 1980s, machine learning — a subset of AI…
