Artificial Intelligence (AI) is a branch of computer science that aims to create intelligent machines that can perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and natural language processing. AI systems can learn from data and improve their performance over time, without being explicitly programmed to do so.

Machine learning (ML) is a subset of AI that focuses on developing algorithms and statistical models that enable machines to automatically learn from data and improve their performance on a specific task. ML techniques include supervised learning, unsupervised learning, and reinforcement learning. Supervised learning involves training a model on labelled data, while unsupervised learning involves training a model on unlabelled data. Reinforcement learning involves training a model to make decisions based on feedback received from its environment.

AI and ML are rapidly advancing and have numerous applications in fields such as healthcare, finance, transportation, and entertainment. They have the potential to revolutionize many industries and improve people’s lives in countless ways. However, there are also concerns about the potential risks and ethical implications of AI and ML, including bias, job displacement, and the possibility of autonomous systems making harmful decisions.