Vector Database Stories
From company news to technical tutorials – explore the most popular content on the Zilliz blog.
Community
What is BERT (Bidirectional Encoder Representations from Transformers)?
BERT, or Bidirectional Encoder Representations from Transformers, has dramatically reshaped the landscape of natural language processing (NLP) since its debut by Google in 2018.
Community
What is Computer Vision?
Computer Vision is a field of Artificial Intelligence that enables machines to capture and interpret visual information from the world just like humans do.
Community
What is a Knowledge Graph (KG)?
A knowledge graph is a data structure representing information as a network of entities and their relationships.
Engineering
Scaling Search with Milvus: Handling Massive Datasets with Ease
A tutorial on how to scale your search engine with massive amounts of data using the Milvus vector database.
Community
Relational Databases vs Vector Databases
Choosing the right database is crucial. Relational databases manage structured data well, while vector databases excel in unstructured data and AI tasks. However, before adding a vector database it's important to evaluate whether the benefits outweigh the costs.
Community
Top 10 NLP Techniques Every Data Scientist Should Know
In this article, we will explore the top 10 techniques widely used in NLP with clear explanations, applications, and code snippets.
Community
Navigating the Challenges of ML Management: Tools and Insights for Success
Learn how XetHub and vector databases like Milvus address ML model management challenges.
Community
The Evolution of Search: From Traditional Keyword Matching to Vector Search and Generative AI
Explores the evolution of search, the limitations of keyword-matching systems, and how vector search and GenAI are setting new standards for modern search.
Community
How Metadata Lakes Empower Next-Gen AI/ML Applications
Metadata lakes are centralized repositories that store metadata from various sources, connecting data silos and addressing various challenges in RAG.