What defines Large Language Models?

Large Language Models (LLMs) are defined as foundation models that specialize in processing, generating, and understanding human language as well as computer code. These models leverage vast amounts of text data to learn patterns, grammar, and context, allowing them to perform a variety of language-related tasks. They are built on advanced neural network architectures and require extensive training on diverse and comprehensive text datasets to achieve their capabilities.

The focus on text and code is essential because it enables LLMs to perform numerous applications, such as text generation, translation, summarization, and coding assistance, which are significant in today’s technology landscape. This definition encompasses their flexibility and scalability, which are fundamental components of their utility in various domains.