The influx of new tools like ChatGPT spark the imagination and highlight the importance of Generative AI and foundation models as the basis for modern AI applications. However, the rise of generative AI also brings a new set of MLOps challenges. Challenges like handling massive amounts of data, large scale computation and memory, complex pipelines, transfer learning, extensive testing, monitoring, and so on. In this 9 minute demo video, we share MLOps orchestration best practices and explore open source technologies available to help tackle these challenges.

ChatGPT sparks the imagination and highlights the importance of Generative AI and foundation models as the basis for modern AI applications. However, this also brings a new set of AI operationalization challenges. Challenges like handling massive amounts of data, large scale computation and memory, complex pipelines, transfer learning, extensive testing, monitoring, and so on. In this talk, we explore the new technologies and share MLOps orchestration best practices that will enable you to automate the continuous integration and deployment (CI/CD) of foundation models and transformers, along with the application logic, in production.

A panel featuring Gilad Shaham, Director of Product at Iguazio, Ofer Shemesh ( Ziprecruter ), and Amir Alush ( Visual Layer)

Hear from Iguazio's Director of Product Management, Gilad Shaham, as he explains the proven production-first approach for scaling your ML operations.

In this session, Jiri shares enterprise secrets to establishing efficient systems for ML/AI and how his team: Watch Jiri and Yaron's fascinating deep dive into HCI’s journey to MLOps efficiency.

Watch Julien Simon (Hugging Face), Noah Gift (MLOps Expert) and Aaron Haviv (Iguazio) discuss how you can deploy models into real business environments, serve them continuously at scale, manage their lifecycle in production, and much more in this on-demand webinar!

A demo showing how to use our feature store in conjunction with Snowflake. Focusing on.