LLMs often reflect societal, cultural, or data-source biases due to their training on human-generated content.

In the context of artificial intelligence, LLM stands for Large Language Model.

A Large Language Model is a type of AI model that is trained on massive amounts of text data to understand and generate human-like language. These models use deep learning, specifically transformer architectures, to perform tasks such as:

1. Text generation
2. Translation
3. Summarization
4. Question answering
5. Sentiment analysis

Examples of LLMs include OpenAI's GPT-4, Google's PaLM, and Meta's LLaMA.

The "large" refers to both:

1. The size of the dataset used in training (often hundreds of gigabytes or more), and
2. The number of parameters (which can be in the billions or trillions) that the model learns.

In the context of artificial intelligence, LLM stands for Large Language Model. It refers to advanced AI models trained on massive amounts of text data to understand, generate, and interact using natural language. Examples include models like GPT (Generative Pre-trained Transformer), which can perform a wide range of language tasks such as translation, summarization, and conversation.

In the context of artificial intelligence, LLM stands for Large Language Model. It refers to a type of AI model that is trained on vast amounts of text data to understand, generate, and interact using human language. These models, like GPT (Generative Pre-trained Transformer), can perform tasks such as translation, summarization, question-answering, and content creation by predicting and generating text based on input prompts.