What subset of AI is specifically known for learning from data?

Machine Learning is the subset of artificial intelligence that focuses on the development of algorithms that allow computers to learn from and make predictions or decisions based on data. It involves training models on a dataset, where the models identify patterns or relationships within that data, enabling them to improve their performance over time as they are exposed to more data.

In the context of AI, Machine Learning distinguishes itself by emphasizing the importance of data-driven insights and adaptability, which are crucial for tasks such as predictive analytics, natural language processing, and computer vision. Through techniques like supervised learning, unsupervised learning, and reinforcement learning, Machine Learning systems can refine their operations without being explicitly programmed for each task.

While Deep Learning is a specialized branch of Machine Learning that utilizes neural networks with many layers (hence the name ‘deep’), it is important to note that not all Machine Learning involves deep learning techniques. Neural Networks, on the other hand, are a structure used within Machine Learning (and particularly in Deep Learning) but do not encompass the entire field. Automation, while related to AI, does not specifically refer to learning from data, as it typically focuses on executing tasks and processes without human intervention. Thus, Machine Learning is the most accurate and comprehensive answer regarding the focus on learning