Jiang Chen

Head of Ecosystem and Developer Relations

Jiang is currently Head of Ecosystem and Developer Relations at Zilliz. He has years of experience in data infrastructures and cloud security. Before joining Zilliz, he had previously served as a tech lead and product manager at Google, where he led the development of web-scale semantic understanding and search indexing that powers innovative search products such as short video search. He has extensive industry experience handling massive unstructured data and multimedia content retrieval. He has also worked on cloud authorization systems and research on data privacy technologies. Jiang holds a Master's degree in Computer Science from the University of Michigan.

Product

Zilliz Cloud Delivers Better Performance and Lower Costs with Arm Neoverse-based AWS Graviton

Zilliz Cloud adopts Arm-based AWS Graviton3 CPUs to cut costs, speed up AI vector search, and power billion-scale RAG and semantic search workloads.

Jul 21, 20255 min read

Product

Zilliz Cloud Enterprise Vector Search Powers High-Performance AI on AWS

Zilliz Cloud delivers blazing-fast, secure vector search on AWS, optimized for AI workloads with AutoIndex, BYOC, and Cardinal engine performance.

Jul 21, 20256 min read

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.

Jan 20, 20257 min read

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.

Dec 02, 20245 min read

Product

Safe RAG with HydroX AI and Zilliz: PII Masking for Responsible GenAI

Organizations can ensure privacy at every layer of their data pipeline by anonymizing or masking PII using the PII Marker before data reaches the vector database.

Nov 07, 20243 min read

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.

Sep 23, 20244 min read

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.

Sep 16, 20248 min read

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.

Aug 09, 202410 min read

Engineering

Optimizing RAG with Rerankers: The Role and Trade-offs

Rerankers can enhance the accuracy and relevance of answers in RAG systems, but these benefits come with increased latency and computational costs.

Apr 02, 202413 min read

Jiang Chen

AI Assistant