Frank Liu

Director of Operations & ML Architect at Zilliz

Frank Liu is the Director of Operations & ML Architect at Zilliz, where he serves as a maintainer for the Towhee open-source project. Prior to Zilliz, Frank co-founded Orion Innovations, an ML-powered indoor positioning startup based in Shanghai and worked as an ML engineer at Yahoo in San Francisco. In his free time, Frank enjoys playing chess, swimming, and powerlifting. Frank holds MS and BS degrees in Electrical Engineering from Stanford University.

VectorDB 101

Hierarchical Navigable Small Worlds (HNSW)

Hierarchical Navigable Small World (HNSW) is a graph-based algorithm that performs approximate nearest neighbor (ANN) searches in vector databases.

Jul 17, 202413 min read

Engineering

Evaluating Your Embedding Model

We'll review some key considerations for selecting a model and a practical example of using Arize Pheonix and RAGAS to evaluate different text embedding models.

Jun 26, 20249 min read

VectorDB 101

Deploying Vector Databases in Multi-Cloud Environments

Multi-cloud deployment has become increasingly popular for services looking for as much uptime as possible, with organizations leveraging multiple cloud providers to optimize performance, reliability, and cost-efficiency.

Apr 12, 20245 min read

Engineering

Hybrid Search: Combining Text and Image for Enhanced Search Capabilities

Milvus enables hybrid sparse and dense vector search and multi-vector search capabilities, simplifying the vectorization and search process.

Apr 09, 20248 min read

Engineering

Introduction to the Falcon 180B Large Language Model (LLM)

Falcon 180B is an open-source large language model (LLM) with 180B parameters trained on 3.5 trillion tokens. Learn its architecture and benefits in this blog.

Mar 18, 20248 min read

VectorDB 101

What is a Vector Database and How Does It Work?

A vector database stores, indexes, and searches vector embeddings generated by machine learning models for fast information retrieval and similarity search. This post explains how vector databases work, their key features and use cases, and the ecosystem.

Mar 01, 202413 min read

Engineering

Training Your Own Text Embedding Model

Explore how to train your text embedding model using the `sentence-transformers` library and generate our training data by leveraging a pre-trained LLM.

Jan 18, 20246 min read

Engineering

Sentence Transformers for Long-Form Text

Learn about sentence transformers for long-form text, Sentence-BERT architecture and use the IMDB dataset for evaluating different embedding models.

Jan 10, 20247 min read

Engineering

Sparse and Dense Embeddings

Learn about sparse and dense embeddings, their use cases, and a text classification example using these embeddings.

Dec 13, 202311 min read