Feature Store Summit 2024
Check out all videos and slides presented at the conference!
From Feature Store to AI Lakehouse
Hopsworks introduces the AI Lakehouse - an extension to the Lakehouse with MLOps capabilities, real-time data support, LLMs and more.
Get the presentationUber's GenAI Oncall Co-Pilot Journey
Uber discusses how they built a GenAI Bot to boost on-call efficiency and minimize downtime.
Get the presentationChronon, Airbnb's Open Source Feature Engineering Framework
Airbnb talks about Chronon - an open-source solution for ML practitioners, ensuring online-offline consistency.
Get the presentationServing Real-Time Features at Etsy
Learn more about Etsy’s Rivulet, a real-time feature store, enhancing ML performance by ensuring feature freshness.
Get the presentationShepherd: High-Scale, Low-Latency Machine Learning with Flink at Stripe
Stripe explores Shepherd's architecture: Flink, tiled data storage, and an automated control plane for faster feature development.
Get the presentationReal-time Feature Serving for Online Inference
Learn how Chalk built its just-in-time online feature store to enable realistic ML use-cases and serve requests in under 5 milliseconds.
Get the presentationThe Snowflake Schema Data Model comes to Feature Stores
Learn how Hopsworks now supports the Snowflake Schema Data Model, enabling more features via foreign keys in online tables.
Get the presentationFeature Store as a Service: How Intuit's Feature Store Service Boosts Developer Productivity on One Intuit Platform
Discover Intuit's strategy for a millisecond-ready Feature Store, enabling developers to build faster, data-driven apps.
Get the presentationImmutable KV Store on Cassandra
Learn how Uber's Michelangelo team uses Cassandra for online prediction, its limitations, and how an immutable store offers a solution.
Get the presentationTurboML’s Platform to leverage Fresh Data for ML
Learn how TurboML's platform overcomes the challenges posed by real-time data that enable fresher features, faster models and more.
Get the presentationEnabling Low Latency Fraud Detection with Real-Time Feature Engineering
Learn how to build real-time fraud detection pipelines with Quix Streams, a Python library, for faster, simpler feature computation.
Get the presentationBanking on Features: Varo's Feature-Driven Approach to Smart Banking
Varo Bank uses its feature platform to embed data & ML in products, supporting traditional and innovative use cases for financial growth.
Get the presentationLarge-Scale Embedding Feature Generation at Uber
Explore how Uber uses embeddings for ML systems, covering their lifecycle, from creation to deployment, and their impact on performance.
Get the presentationHow Roche’s Data Platform accelerates Feature Engineering through Generative AI
Discover how Roche’s data platform uses GenAI to transform feature engineering, enhancing healthcare analytics.
Get the presentationFennel's Primitives for maintaining Data & Feature Quality
Learn seven key primitives from Fennel that ensure data and features are reliable and trustworthy for high-quality ML models.
Get the presentation