How Large Language Models (LLMs) Learn: Playing Games
How Large Language Models (LLMs) Learn: Playing Games
How Large Language Models (LLMs) Learn: Playing Games
James Thorn
January, 9, 2025
Summary
This article offers a friendly, high-level overview of how Large Language Models (LLMs) like ChatGPT learn. LLMs are statistical models trained on vast amounts of text data, including books, websites, and user content, to understand and generate human-like language. Their training resembles the “Mad Libs” game—predicting missing words using context—which allows them to learn language patterns through a process called self-supervised learning. Over time, they develop "emergent capabilities" such as coding, translation, and summarization. The article also touches on the debate about whether LLMs could achieve Artificial General Intelligence (AGI), raising questions about the nature of intelligence and language.
Reference
Thorn, J. (2025, January 9). How Large Language Models (LLMs) learn: Playing games. Towards Data Science. https://towardsdatascience.com/how-large-language-models-llms-learn-playing-games-cb023d780401/