Artificial Intelligence (AI)

AI is a broad field of computer science that aims to create systems or machines that can perform tasks that typically require human intelligence. This can include tasks such as visual perception, speech recognition, decision-making, problem-solving, natural language processing, and many others. AI can be classified into two types: Narrow or Weak AI, which is designed for a specific task or domain, and General or Strong AI, which possesses the ability to perform any intellectual task that a human can.

Machine Learning (ML)

Machine learning is a subset of AI and refers to the process by which a machine or system learns from experience or data without being explicitly programmed. In other words, it involves the development of algorithms that enable a system to learn from data, identify patterns, and make predictions or decisions based on the learned patterns. ML algorithms can be categorized into three types: supervised learning, unsupervised learning, and reinforcement learning.

The main difference between AI and ML is that AI is a broader concept that encompasses the overall field of creating intelligent systems, while ML is a specific subset of AI that focuses on the development of algorithms that enable machines to learn from data. In other words, ML is a technique used within the broader field of AI to enable machines to learn and improve their performance over time without being explicitly programmed, whereas AI encompasses a wider range of concepts, methods, and technologies beyond just machine learning, such as expert systems, rule-based systems, and symbolic reasoning, among others.

In summary, AI is the broader field of creating intelligent systems, while ML is a specific subset of AI that focuses on the development of algorithms for machines to learn from data. ML is one of the techniques used within the field of AI to enable machines to learn and make decisions based on patterns learned from data.