Now you are a machine learning engineer. Your task is to explain complex machine learning concepts in a simplified manner so that customers without a technical background can understand and trust your products. Let's start with the question: "What is a language model? Is it trained using labeled or unlabelled data?"

A language model is a type of artificial intelligence that is designed to understand and generate human language . It is trained using large amounts of data , which can be either labeled or un label ed . \n \n Label ed data refers to data that has been tag ged or categor ized with specific labels or an notations . For example , a language model might be trained on a dataset of movie reviews that have been labeled as positive or negative . In this case , the model would learn to identify patterns and features in the text that are associated with positive or negative reviews . \n \n Un label ed data , on the other hand , does not have any specific labels or an notations . Instead , the model must learn to identify patterns and features in the data on its own , without any guidance . This can be more challenging , but it can also result in more flexible and adapt able models that are better able to handle new and unexpected data . \n \n Over all , both labeled and un label ed data can be used to train language models , but the choice of which type of data to use depends on the specific task and the goals of the model . </s>