Cohere introduced Embed v3, an advanced model for generating document embeddings, boasting top performance on a few benchmarks. It excels in matching document topics to queries and content quality, improving search applications and retrieval-augmentation generation (RAG) systems. The new version offers models with 1024 or 384 dimensions, supports o

Vector databases can be used to store and serve machine learning models and their corresponding embeddings. The primary application is similarity search (also semantic search),

It wasn’t so much about hiding the data at all costs but preventing harm from the way that data was used.

The premise of the paper is that while OpenAI and Google continue to race to build the most powerful language models, their efforts are rapidly being eclipsed by the work happening in the open source community.