Field of computer science and engineering practices for intelligence demonstrated by machines and intelligent agents.
Artificial Intelligence (AI) is a rapidly evolving field that is transforming the world in numerous ways. To fully grasp the impact and potential of AI, it's essential to understand its fundamental concepts.
Artificial Intelligence refers to the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions), and self-correction.
The primary goals of AI include:
While these terms are often used interchangeably, they are not the same. AI is a broader concept that involves machines mimicking human intelligence. Machine Learning (ML) is a subset of AI that involves machines learning from data without being explicitly programmed. Deep Learning, on the other hand, is a subset of ML that uses neural networks with many layers (hence the 'deep' in Deep Learning) to learn from vast amounts of data.
An algorithm in AI is a set of instructions designed to perform a specific task. This can be simple, like sorting a list of numbers, or complex, like parsing data from a natural language. AI algorithms are designed to make decisions, often using real-world data, input, and feedback, to help the system learn and improve over time.
In conclusion, understanding these fundamental AI concepts is crucial to appreciate the potential and challenges of AI. As we delve deeper into the subject in the following units, you'll see how these concepts play out in various applications and contexts.
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