Language Model Education 1 article

Language models generate or analyze text using learned statistical patterns, a process that requires attention to context and limitations. Tokenization, training objectives, context windows, inference, and prompting help explain why models can produce fluent but incorrect text; materials may compare language-model families and their roles inside applications. A useful study also examines how a model is evaluated and why apparently confident answers may still need independent verification.