Notes from Gemini Embedding Paper

I was reading a paper by the Google DeepMind team on how they trained Gemini Embedding, a state-of-the-art, unified embedding model. This is the second paper I’ve read this month on training embedding models. Last week, I read about how the Jina embedding model was trained. The Jina embedding paper was thin and lacked details, … Continue reading "Notes from Gemini Embedding Paper"