Machine Learning (ML) is a subset of AI that focuses on training computers to learn from data and improve their performance on specific tasks without being explicitly programmed. It enables machines to recognize patterns and make predictions.

AI often uses ML as a crucial component. ML algorithms enable AI systems to acquire knowledge and adapt to new information. AI, in turn, utilizes this knowledge to make intelligent decisions and carry out tasks effectively.

There are two main types of AI: Narrow or Weak AI, which is designed for specific tasks, and General or Strong AI, which possesses human-like intelligence and can perform a wide range of tasks. Currently, Narrow AI is more prevalent.

Machine Learning includes supervised learning (where models learn from labelled data), unsupervised learning (for finding patterns in unlabelled data), and reinforcement learning (where agents learn through trial and error).

AI and ML offer benefits such as automation of repetitive tasks, improved decision-making, enhanced efficiency, personalized recommendations, and advancements in healthcare, finance, and many other industries

AI and ML will continue to transform industries, making processes more efficient, enhancing healthcare with diagnostic tools, and enabling innovative solutions in fields like autonomous vehicles, robotics, and personalized education.

Examples include virtual assistants like Siri and Alexa, recommendation systems on streaming platforms, fraud detection in banking, self-driving cars, medical image analysis, and predictive maintenance in manufacturing. These technologies are already part of our daily lives.