Abstract: 

Machine language understanding and generation has been undergoing rapid improvements due to recent breakthroughs in machine learning (e.g. large language models like GPT and BERT). And while big tech and NLP engineers were quick to capitalize on these models, the broader developer community lags in adopting these models and realizing their potential in their business domains.

This talk provides a gentle and highly visual overview of some of the main intuitions and real-world applications of large language models. It assumes no prior knowledge of language processing and aims to bring attendees up to date with the fundamental intuitions and applications of large language models.

Bio: 

Jay Alammar, Through his popular machine learning blog, Jay has helped millions of engineers visually understand machine learning tools and concepts from the basic (ending up in NumPy, pandas docs) to the cutting-edge (The Illustrated Transformer, BERT, GPT-3).