Common machine learning algorithms include linear regression, decision trees, neural networks, support vector machines, and k-nearest neighbors, among others.

Deep Learning is a subset of machine learning that involves artificial neural networks with multiple layers (deep neural networks). It is particularly suitable for tasks like image and speech recognition, and it automatically learns features from data.

AI systems learn from data through a process called training. They use algorithms to analyze data, identify patterns, and adjust their internal parameters to improve performance over time.

Ethical considerations in AI include issues like bias in AI algorithms, data privacy, job displacement, and the responsible use of AI in sensitive applications like healthcare and criminal justice.

AI is used in diverse industries, including healthcare (diagnosis and treatment), finance (fraud detection and trading), autonomous vehicles, retail (personalized recommendations), and manufacturing (predictive maintenance).