Synthetic Data Generation with LLMs: Egregore and AI

In this video, I will introduce you to the concept of synthetic data generation with LLMs, which are powerful models that can learn from large amounts of text data and generate natural language texts. I will also talk about the concept of egregore, which is an esoteric concept that describes a nonphysical entity that arises from the collective thoughts of a group of people. I will tell you how synthetic data can help you with natural language processing (NLP) tasks, such as text classification, natural language understanding, and semantic parsing, and how to generate it with LLMs using two methods: teaching via data (TvD) and prompt engineering (PE). I will give you two case studies of using TvD and PE to generate synthetic data for joint intent classification and slot tagging (IC+ST) and semantic parsing. I will discuss the pros and cons of using LLMs for synthetic data generation, and show you the performance of different models on various benchmarks and languages. I hope you will find this video informati