What subset of AI focuses on enabling computer systems to learn and improve from experience?

Machine Learning is a subset of artificial intelligence that specifically emphasizes the ability of computer systems to learn from data, improve their performance over time, and make predictions or decisions without being explicitly programmed for each task. This learning process involves the analysis of patterns in data, allowing systems to adapt and enhance their accuracy as they are exposed to more information.

While Artificial Intelligence encompasses a broader spectrum of technologies and ideas, including reasoning, problem-solving, and natural language processing, it is Machine Learning that directly addresses the concept of systems improving from experience. Deep Learning, on the other hand, is a further specialization within Machine Learning that focuses on neural networks with many layers, enabling even more complex data representations and learning tasks. Generative AI refers to models and systems capable of generating new content, such as images or text, based on learned characteristics from existing data but does not focus on general learning from experience in the same way as Machine Learning does. This distinction is crucial in understanding the scope of various AI technologies.