What is a Large Language Model (LLM)?

In today’s world of artificial intelligence, one term you’ll hear again and again is large language model, or LLM. But what exactly does that mean?

On a fundamental level, an LLM is a type of AI that has been trained on massive amounts of text data. This training allows it to discover patterns of human language, context, and meaning. As a result, LLMs can generate text that sounds remarkably human — be it responding to a question, writing a story, or even conversing.

The goal of an LLM is not just to "know" words, but to grasp how language flows, how ideas connect, and how humans communicate emotions, facts, and opinions through writing.

Some popular examples of large language models include:

• OpenAI’s GPT series (like GPT-3.5 and GPT-4)
• Google’s Gemini
• Anthropic’s Claude

These models are each built somewhat differently, but they share one thing: they've read (and learned from) trillions of words in books, articles, websites, and other texts to become "fluent" in human language.

Thanks to LLMs, we're seeing incredible advances in technology — from smarter virtual assistants and customer service chatbots to sophisticated writing assistants and creative AI collaborators. As the technology continues to evolve, LLMs are becoming increasingly adept at understanding not just what we say, but what we mean.

In short, a large language model is the engine behind many of today's most promising AI developments — by learning the art of human language.