New Breakthroughs in Text Embedding 🚀!

Angelina Yang
4 min readFeb 15, 2024

Text embeddings play pivotal roles in Natural Language Processing (NLP) tasks such as modern information retrieval, question answering, and retrieval-augmented generation (RAG). From classics like GloVe and BERT to the latest state-of-the-art (SOTA) models, these embeddings encode semantic information, proving indispensable in various applications.

Text Embedding📽️

If you’re new to the concept of embeddings, check out our quick 2-minute interview prep on this topic: