Generative AI is under the spotlight and it has diverse applications but there are also many considerations when deploying a generative model at scale. This presentation will make a deep dive into multiple architectures and talk about optimization hacks for the sophisticated data pipelines that generative AI requires. The session will cover: - How to create and prepare a dataset for training at scale in single GPU and multi GPU environments. - How to optimize your data pipeline for training and inference in production considering the complex deep learning models that need to be run. - Tradeoff between higher quality outputs versus training time and resources and processing times.

Agenda: - Basic concepts in Generative AI: GAN networks and Stable Diffusion - Training and inference data pipelines - Industry applications and use cases

Talk by: Paula Martinez and Rodrigo Beceiro

Here’s more to explore: LLM Compact Guide: https://dbricks.co/43WuQyb Big Book of MLOps: https://dbricks.co/3r0Pqiz

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc