Large Language Models (LLMs) have risen to prominence in recent years thanks to their ability to accurately model human Natural Language, solve reasoning tasks and effectively assist humans in several tasks via a chat interface.
In my talk I will introduce the core neural network architecture behind LLMs, the Transformer. I will further present the main line of research and insights that lead to the successful scaling of Transformer Language Models up to hundreds of billions of parameters. Finally I will relate the main ideas that let us turn a Large Language Model into a useful language assistant such as ChatGPT.