ODSC AI & Chalk Meetup in San Francisco
ODSC AI & Chalk Present: Relevance at Decision Time
Most marketplace recommender systems don’t fail because of poor model quality—they fail because of stale data.
When systems rely on rigid batch pipelines and precomputed features, the information is often outdated by the time a ranking decision is actually made. Join us in San Francisco for an evening dedicated to solving the production bottlenecks of real-time machine learning.
The Talk
Building Recommender Systems with On-Demand Feature Computation
Elliot Marx (Co-founder of Chalk) will break down why production recommenders break and introduce a better way: computing features on demand at decision time. Using a query execution engine purpose-built for real-time ML, he’ll demonstrate how to maintain relevance under strict latency and scale constraints.
The Speaker
Elliot Marx, Co-founder of Chalk has spent the last decade building ML systems that operate under intense real-world constraints. Before founding Chalk, he built the data engineering platform for fraud at Affirm and later sold his previous company to Credit Karma, where he led ML infrastructure development.
Agenda & Logistics
📅 Date: 29th January 2026 Time: 6:00 PM – 8:00 PM PT 📍 Location: 55 Stockton St, Floor 4, San Francisco, CA 94108 🍕 Food: Pizza and refreshments included!
6:00 PM – 6:30 PM: Networking & Bites/Drinks
6:30 PM – 7:15 PM: Presentation + Live-Code Demo
7:15 PM – 7:30 PM: Q&A
7:30 PM – 8:00 PM: Networking
Space is limited, so please RSVP to secure your spot!
Useful Links
Free access to more talks/trainings: Ai+ Training platform
ODSC blog: https://opendatascience.com/
Slack Channel: https://hubs.li/Q038cQBy0
Code of conduct: https://odsc.ai/code-of-conduct/