What is the Difference Between Artificial Intelligence and Machine Learning?

Yes, your observation is correct! Artificial Intelligence (AI) and Machine Learning (ML) are closely related, and at first glance, it may seem like they both revolve around creating mathematical models for decision-making. However, the key difference lies in the scope and methods of these two fields. Here’s a more detailed breakdown to clarify the distinction:

Scope of AI vs ML

• Artificial Intelligence (AI) is a broader concept that refers to machines or systems designed to simulate or exhibit some form of intelligence. The goal of AI is to create machines that can mimic human-like reasoning, problem-solving, and decision-making across a wide range of tasks. AI is essentially an umbrella term that encompasses various techniques and approaches, including logic-based systems, expert systems, rule-based decision-making, and machine learning.
• Machine Learning (ML) is a subset of AI. It specifically focuses on the idea of enabling machines to learn from data (rather than being explicitly programmed for every possible scenario) and improve their performance over time. ML uses statistical models, algorithms, and data to make predictions or decisions without human intervention.

 
In short, AI is the broader field concerned with creating intelligent systems, and ML is one of the methods used to achieve this by learning from data.