Topics of Interest

All submissions will be reviewed by experts in the field. The authors of the submissions are invited to present their session live (online) under the following talk categories: 

Track 1: Real-Time AI Systems

Submit talk proposals for talks focusing on real-time feature engineering, low latency data stores, and other topics related to building real-time AI systems, such as architecture, implementation, use cases, and best practices. Our goal is to share insights into how real-time AI systems enable efficient data processing and low latency feature/model serving in challenging environments. 

Track 2: Batch AI Systems

Submit talk proposals that focus on the integration of feature stores with analytical data and batch data processing pipelines. We are interested in talks for how best to integrate data warehouses with feature stores, and how to efficiently integrate Python frameworks with lakehouses, data warehouses, and data lakes. Use cases for how to manage feature data at scale and governance of data are topics of interest.

Track 3: LLM AI Systems

Submit talk proposals for highlighting the intersection of feature stores with Large Language Models (LLMs). We are interested in talks for how to manage data for LLMs, from retrieval augmented generation (RAG), to instruction datasets for fine-tuning, to prompt stores for collecting and organizing prediction logs from LLMs.

Track 4: Building an AI Factory 

Submit talk proposals for highlighting how feature stores enable improvements in delivering better models faster at large organizations. We are interested in talks for how feature stores enable new ways of working and improvements in organizational efficiency, feature reuse, and improved data governance - including how to manage data securely given the changing legislative environment globally.

Important Dates

Submissions Deadline: June 30th, 2024

Results: July 5th, 2024

Conference Date: October 15th, 2024