From Notebooks to production with Flyte 1.14

00:00 Intro 03:21 Notebooks integration 17:13 Offloading of large literals 36:36 Msgpack to serialize dataclass/Pydantic 40:07 Updates to eager (coming in the 1.15 release) 44:21 Demo: Flyte-native Hyper-Parameter Optimization Join this session to learn from Flyte maintainers how the 1.14 release elevates the reproducibility and production-readiness of experiments developed in interactive Notebooks, enhances support for dataclass/Pydantic BaseModel, and improves the reliability of your AI pipelines with automated data offloading. Finally, get a sneak peek into what's coming in Flyte 1.15. Bring your questions!