AN INTUITIVE INTRODUCTION TO TEXT EMBEDDINGS

Summary from the TLDR Web Dev newsletter

Text embeddings are representations of text in high-dimensional spaces for various NLP tasks like search, spam filtering, content moderation, and conversational agents. The preservation of distance is a key feature of embedding spaces. This article goes through the evolution of sequential models in NLP, including fully-recurrent neural networks, long short-term memory, and the transformer architecture, which uses attention mechanisms to better capture the context and dependencies between words in a sequence and has become essential in large language models.