Learn about why you need distance metrics in vector search and the metrics implemented in Weaviate (Cosine, Dot Product, L2-Squared, Manhattan, and Hamming).
What is a Vector Database? Explaination of core concepts, such as vector embeddings, vector search, and vector indexing
Learn about our latest open source demo and how we used Semantic and Generative Search to improve access to health
Learn about the new native multi-tenancy feature
Learn about the intersection between LLMs and Search
A discussion on data privacy and privacy-preserving machine learning for LLMs
Videos on authentication: an overview, how to log in, how to set it up, and core concepts - including recommendations.
Learn about how to monitor Weaviate in production and observe key metrics.
A gentle introduction to Large Language Models (LLMs) - how they work and what they learn.
Machine learning models can create beautiful and novel images. Learn how Diffusion Models work and how you could make use of them.
Get an intuitive understanding of what exactly vector embeddings are, how they're generated, and how they're used in semantic search.
