Machine Learning, AI Definitions

Artificial intelligence

Artificial intelligence (AI) is a broad concept that encompasses machine learning (ML) and other subfields, while ML is a specific application of AI that focuses on teaching machines to perform tasks: 

• AI
  The ability of a computer system to mimic human cognitive functions, such as learning and problem-solving. AI uses math and logic to simulate human reasoning. Examples of AI include smart assistants like Alexa, robotic vacuum cleaners, and self-driving cars. 
  
  
• ML
  A subfield of AI that uses mathematical models and algorithms to teach computers to perform tasks without direct instruction. ML systems use patterns and inference to learn from data and improve themselves over time. Examples of ML include sorting images, analyzing big data, and forecasting sales. 
  

ML enhances AI's ability to perform tasks more accurately and efficiently. For example, AI uses ML to perform tasks like speech recognition and object detection.

Machine learning

Machine learning involves using algorithms to train models on data, allowing the model to identify patterns and make predictions. Traditional programming involves manually writing code to create a solution to a specific problem.

Classical programming versus machine learning paradigm. (A) In classical programming, a computer is supplied with a dataset and an algorithm. The algorithm informs the computer how to operate upon the dataset to create outputs. (B) In machine learning, a computer is supplied with a dataset and associated outputs. The computer learns and generates an algorithm that describes the relationship between the two. This algorithm can be used for inference on future datasets.