Chang She
Chang is the CEO/Co-founder of Eto Labs and a co-creator of LanceDB, a new open source vector database that supports low-latency vector search on billion-scale vectors on a single node. Previously Chang was VP of Engineering at Tubi TV and was a co-author of the pandas library from 2009-2014.
@changhiskhan
Notable open source projects that you contribute to. Add URLs, one per line. –I was one of the original co-authors of the pandas library from before it was open-sourced to 2014.
Session
From recommendation systems to LLM-based applications, vector search is a critical component of the modern AI workflow. Existing vector solutions are complicated to use, hard to maintain, and cost too much. LanceDB is a free open-source vector store that can perform low latency vector search on billion-scale vector datasets on a single node. LanceDB is powered by Lance format, a modern columnar data format for machine learning and data science. Compatible with pandas/polars/duckdb, Lance format supports vector index, predicate pushdown, and random access performance 2000x faster than parquet.