AI gets its information from large amounts of data collected from many sources. This data includes text, images, audio, and video from the internet, books, articles, and databases. Some data comes from public sources like government statistics, social media, news, and licensed datasets. Other data may be collected internally by companies, such as customer behavior or sales records. AI systems are trained on this data to recognize patterns and learn relationships within it through processes like machine learning. The training involves showing the AI many examples so it can make accurate predictions or generate responses based on what it "learned" from the data. After training, when asked a question, AI uses its learned knowledge to provide answers by matching patterns or retrieving relevant information from its training foundation. This process relies heavily on vast and diverse datasets for accuracy and wide coverage.