Engineering
Zilliz Cloud Pipelines February Release - 3rd Party Embedding Models and Usability Improvements!
The latest updates to Zilliz Cloud Pipelines in February focuses on new embedding models and ease of use.
Engineering
Crafting Superior RAG for Code-Intensive Texts with Zilliz Cloud Pipelines and Voyage AI
We are thrilled to announce that embedding models from Voyage AI are available in Zilliz Cloud Pipelines.
Engineering
Elasticsearch Was Great, But Vector Databases Are the Future
Purpose-built vector databases outperform dual-system setups by unifying Sparse-BM25 and semantic search in a single, efficient implementation.
Company
Jiang Chen: Why I Joined Zilliz
I am passionate about democratizing AI-native infrastructures and enjoying working with awesome people here at Zilliz.
Product
Introducing the Databricks Connector, a Well-Lit Solution to Streamline Unstructured Data Migration and Transformation
The latest release of Zilliz Cloud introduces a Databricks Connector, a well-lit solution to streamline this process by integrating Apache Spark/Databricks and Milvus/Zilliz Cloud.
Engineering
The Landscape of GenAI Ecosystem: Beyond LLMs and Vector Databases
Initially, Large Language Models (LLMs) and vector databases captured the most attention. However, the GenAI ecosystem is much broader and more complex than just these two components.
Engineering
Unlock AI-powered search with Fivetran and Milvus
Fivetran supports the Milvus vector database as a destination, making it easier to onboard every data source for RAG and AI-powered search.
Engineering
How AI Is Transforming Information Retrieval and What’s Next for You
This blog will summarize the monumental changes AI brought to Information Retrieval (IR) in 2024.
Engineering
Tame High-Cardinality Categorical Data in Agentic SQL Generation with VectorDBs
This article explores how integrating vector databases with agentic text-to-SQL systems can address High-Cardinality Categorical Data problems.