What are Large Language Models (LLMs)?

About Large Language Models (LLMs):

• A large language model (LLM) is a type of artificial intelligence (AI) program that can recognize and generate text, among other tasks.
• LLMs are trained on huge sets of data—hence the name "large."
• LLMs are built on machine learning: specifically, a type of neural network called a transformer model.
• In simpler terms, an LLM is a computer program that has been fed enough examples to be able to recognize and interpret human language or other types of complex data. 
• Many LLMs are trained on data that has been gathered from the Internet—thousands or millions of gigabytes' worth of text.
• However, the quality of the samples impacts how well LLMs will learn natural language, so an LLM's programmers may use a more curated data set.
• LLMs use a type of machine learning called deep learning in order to understand how characters, words, and sentences function together.
  • Deep learning involves the probabilistic analysis of unstructured data, which eventually enables the deep learning model to recognize distinctions between pieces of content without human intervention.
• LLMs are then further trained via tuning: they are fine-tuned or prompt-tuned to the particular task that the programmer wants them to do, such as interpreting questions and generating responses, or translating text from one language to another.
• What are LLMs used for?
  • LLMs can be trained to do a number of tasks. One of the most well-known uses is their application as generative AI: when given a prompt or asked a question, they can produce text in reply. 
  • The publicly available LLM ChatGPT, for instance, can generate essays, poems, and other textual forms in response to user inputs.