GenAI Pipelines: From Data Exploration to Prototype to Production

Explore the process of building in-house GenAI data pipelines from proof-of-concept to production in this 38-minute talk sponsored by Airbyte. Learn how to use PyAirbyte for efficient data sourcing from over 250 sources with minimal Python code. Discover the steps to elevate pipelines from prototypes to full production using the ELTP framework, with a focus on the crucial 'Publish' step for vector store destinations. Gain insights into managing Large Language Model (LLM) "documents" as data, comparing them to traditional data forms. Enhance your data pipeline capabilities for the GenAI era with strategies shared by AJ Steers, Staff Software Engineer in AI at Airbyte. Access additional resources like the LLM Compact Guide and Big Book of MLOps to further your understanding of MLOps and GenAI data management.

Sponsored by: Airbyte | GenAI Pipelines: From Data Exploration to Prototype to Production