

by Snorkel AI Community Events
Join us for the launch of the Snorkel AI Reading Group, a recurring forum to explore the latest frontier developments in AI while building meaningful connections within the community.In our inaugural session, Mayee Chen of Stanford AI Research Lab will dive into her paper “Olmix: A Framework for Data Mixing Throughout LM Development.”Agenda:
5:30pm - doors open6pm - talk beginsLight drinks and appetizers provided
Training data is one of the most powerful levers in modern language models. This talk dives into data mixing, a critical but under-explored factor that can significantly impact model performance.
You’ll learn:
What actually works (and doesn’t) when mixing data across domainsWhich design choices meaningfully improve model performanceHow to handle constantly evolving datasets in real-world LM developmentA practical method to reduce compute by 74% while maintaining performanceHow smarter data mixing can drive double-digit gains on downstream tasks
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is a free independent taking place on Thursday, April 30, 2026 at 101 Second Street, San Francisco, CA 94105, USA, San Francisco, United States. Attendance is free — register to secure your spot.
Join this independent over 2 hours and 30 minutes for an engaging session of learning, discussion, and networking with fellow attendees.
This independent in San Francisco is ideal for:
This morning independent is part of the growing events scene in San Francisco. Whether you're based in San Francisco or visiting for the independent, it's a great opportunity to connect with the local community. Browse more upcoming events in San Francisco on Rifio.
Reading Group: Olmix: A Framework for Data Mixing Throughout LM Development covers topics including AI. Find similar events by browsing these topics on Rifio.