large language model

Definitions

A type of neural network specializing in language, typically including billions of parameters.

Equivalents

Examples

“GPT-3 belongs to a category of deep learning known as a large language model⟳, a complex neural net that has been trained on a titanic data set⟳ of text: in GPT-3’s case, roughly 700 gigabytes of data drawn from across the web, including Wikipedia, supplemented with a large collection of text from digitized books. GPT-3 is the most celebrated of the large language models, and the most publicly available, but Google, Meta (formerly known as Facebook) and DeepMind have⟳ all developed their own⟳ L.L.M.s in recent years.”

“GPT-2 is a large language model⟳ with 1.5 billion parameters, trained on a dataset of 8 million web pages scraped from the internet.”

“Less charitable observers (like⟳ this columnist) see⟳ two alternative interpretations. One is that it’s an attempt⟳ to consolidate OpenAI’s lead⟳ over the rest⟳ of the industry in large language models (LLMs), because history suggests that regulation often enhances dominance.”

“Large language models work⟳ well because they’re so large. The latest models from OpenAI, Meta, and DeepSeek use⟳ hundreds of billions of “parameters” […] With more parameters, the models are better able to identify⟳ patterns and connections, which in turn⟳ makes them more powerful and accurate. But this power comes at a cost⟳ […] huge computational resources […] energy hogs […] In response, some researchers are now thinking small. IBM, Google, Microsoft, and OpenAI have⟳ all recently released small language models (SLMs) that use⟳ a few billion parameters—a fraction of their LLM counterparts.”

CEFR level