feast

Hey folks! I recently gave a talk with the Milvus Community showing a demo of how to transform PDFs with Feast using Docling for RAG. The tutorial is available here: https://github.com/feast-dev/feast/tree/master/examples/rag-... And the video is available here: https://www.youtube.com/watch?v=DPPtr9Q6_qE The goal with having a feature store transform and retrieve your data for RAG is that (1) we make it easy to configure vector retrieval with just a boolean in the code declaration and (2) you can use existing tooling that data scientists / ml engineers are already familiar with. I'd love any feedback or ideas on how we could make things better or easier. The Feast maintainers have quite a lot in the pipeline (batch transformations, support for Ray, computer vision and more). Thanks a ton!

Hey folks! I'm a maintainer for Feast (https://github.com/feast-dev/feast) (the Open Source Feature Store) and the Feast community is working on creating a Kubernetes Operator for deploying Feast on Kubernetes and would love any feedback you have before we get started! Here is the GitHub issue: https://github.com/feast-dev/feast/issues/4561, a design doc: https://docs.google.com/document/d/1vGKMizf3_14IyiF_W_Ik7CR0..., and a Slack channel: https://communityinviter.com/apps/feastopensource/feast-the-...! Thanks a ton in advance for your interest/comments!

AI Engineering is basically Data Engineering focused on AI. When in "traditional" Data Engineering you create pipelines that store processed data in something like a Data Lake, in AI Eng. your end storage might be a specialized Feature Storage (like Feast or GCP Vertex AI). There are some AI Engineers with strong scientific/mathematical background, but that's rare. Usually, you're paired with these ML people that actually develop and evaluate the models. So my advice is to start with Data Engineering and then find a specialization AI. You should have a VERY solid foundation on scripting and programming, specially Python. Also, a lot of concepts of "data wrangling". Understanding how data flows from point A to point B, how the intermediate storages and streaming engines work, etc. Functional programming is key here. [0] https://github.com/

But is it open-source? Our Hopsworks Feature Store is * https://github.com/logicalclocks/hopsworks as is GoJEK Feast * https://github.com/feast-dev/feast I really believe that all Enterprise platform software should have an open-source version if it is to have a meaningful effect on how people work (in this case, how Data Scientists and Data Engineers work together).