A Large Language Model (LLM) is a type of artificial intelligence model designed to generate human-like text based on a given input. These models are a form of machine learning and are trained on a diverse range of internet text.
An LLM generates responses to prompts or questions by identifying and applying patterns it has learned during training. It doesn’t possess consciousness, personal beliefs, or desires, and all generated responses are a result of simulated patterns rather than personal sentiment. LLMs do not have the ability to access real-time, up-to-date information or knowledge beyond their training data.
For example, a model like OpenAI’s GPT-4, which falls under the category of LLMs, generates text by predicting what comes next in a given piece of text. This allows it to create coherent and contextually relevant sentences. However, its knowledge is „frozen“ at the time of the last training data, meaning it cannot provide information on events that occurred after this time.
Despite their lack of real-world awareness or consciousness, LLMs have found a wide range of applications, from drafting emails or other pieces of writing, to answering questions about documents, creating conversational agents, tutoring in a variety of subjects, translating languages, and simulating characters for video games, among many other uses.
The utilization of LLMs raises several ethical and societal concerns, including the potential for misuse and the challenge of ensuring appropriate behavior. To manage these issues, developers and users of LLMs should adhere to strict guidelines and constantly monitor and update model behaviors as necessary.