ML⇄DB Seminar Series — Fall 2023

Databases provide a sanctuary for the vast volumes of information required for the grand pursuit of machine learning (ML). Every bit and byte, meticulously organized and indexed, forming a labyrinthine treasure trove of data, awaiting its turn to be harnessed by ML algorithms. But it is a symbiotic relationship where ML algorithms, armed with their predictive prowess and pattern-seeking prowess, infuse the databases with newfound intelligence. The union of databases and ML is a testament to the virtuous circle of progress, where each empowers the other in a perpetual cycle of advancement.

Given this, the Carnegie Mellon University Database Research Group celebrates this grand convergence of data storage and computational mastery with the ML⇄DB Seminar Series (Machine Learning for Databases + Databases for Machine Learning). Each speaker will present the implementation details of their respective systems and examples of the technical challenges they faced when working with real-world customers.

All talks are on-line and open to the public via Zoom. You do not need to be a current CMU student to attend. Random people off of the internet are especially welcome. Videos will be posted on the CMU-DB Youtube Channel after each talk.

This seminar series is held in conjunction with the following groups at Carnegie Mellon:


Date Speaker Talk Title Video
Sep 11Qdrant Sep 11 Andrey Vasnetsov Qdrant: Vector Search Engine Internals
Sep 18OtterTune Sep 18 Dana Van Aken OtterTune: AI-Powered Database Optimization as a Service!
Sep 25PostgresML Sep 25 Montana Low PostgresML: Why Moving the Compute to the Data is Better than the Alternative
Oct 2Weaviate Oct 2 Etienne Dilocker Weaviate: The Vector Database Your Parents Wished They Had!
Oct 9Featureform Oct 9 Simba Khadder Featureform: Yeah, Your Database Can Do That!
Oct 16FeatureBase Oct 16 Pat O'Keeffe FeatureBase: Analytics & Vector Engine Made for AI!
Oct 23LanceDB Oct 23 Chang She Lance Columnar Format for Multi-modal AI Data Management
Oct 30 Akamas Oct 30 Stefano Cereda Akamas: The Database Tuner of the Future!
Nov 6 Milvus Nov 6 Li Liu Milvus: A Purpose-Built Vector Data Management System!
Nov 13 Alibaba Nov 13 Jian Tan Domain Knowledge Augmented AI for Databases
Nov 20 pgvector Nov 20 Jonathan Katz pgvector: Stylish Hierarchical Navigable Small World Indexes!
Nov 27 Chroma Nov 27 Hammad Bashir +
Liquan Pei
Chroma: Vector Database Straight From the Tenderloin!