The field of Natural Language processing has been witnessing a rapid acceleration in model improvement in the last few years. The majority of the state-of-the-art models in the field are based on the Transformer architecture. Examples include models like BERT (which when applied to Google Search, resulted in what Google calls "one of the biggest leaps forward in the history of Search") and OpenAI's GPT2 and GPT3 (which are able to generate coherent text and essays).
This talk by the author of the popular "Illustrated Transformer" guide will introduce the Transformer architecture and its various applications. This will be a visual presentation accessible to people with various levels of ML experience.
Overview and Author Bio
A Gentle Intro to Transformer Neural Networks
Machine Learning Research Engineer | jalammar.github.io