Differences between Artificial Intelligence and Machine Learning !

Differences between Artificial Intelligence and Machine Learning 

Artificial intelligence (AI) is a broad field that includes machine learning (ML) as a subset:

AI

The ability of a computer to mimic human intelligence and perform tasks like learning, problem-solving, and speech recognition. 

AI uses math and logic to simulate human reasoning. Examples of AI include smart assistants, robotic vacuum cleaners, and self-driving cars.

ML

A subset of AI that allows computers to learn and improve from experience. 

ML uses algorithms and statistical models to process data and identify patterns. 

ML enables computers to perform complex tasks without explicit instructions, relying on patterns and inference instead. 

 

AI and ML work together to make computers smarter and more effective at producing solutions. For example, ML can help identify changes in data, allowing AI to make adjustments. 

Summary of Differences: AI vs. Machine Learning 

 

	Artificial Intelligence	Machine Learning
What is it?	AI is broad term for machine-based applications that mimic human intelligence. Not all AI solutions are ML.	ML is an artificial intelligence methodology. All ML solutions are AI solutions.
Best suited for	AI is best for completing a complex human task with efficiency.	ML is best for identifying patterns in large sets of data to solve specific problems.
Methods	AI may use a wide range of methods, like rule-based, neural networks, computer vision, and so on.	For ML, people manually select and extract features from raw data and assign weights to train the model.
Implementation	AI implementation depends on the task. AI is often prebuilt and accessed via APIs.	You train new or existing ML models for your specific use case. Prebuilt ML APIs are available