sedna/docs/roadmap.md

# Roadmap

This document defines a high level roadmap for sedna development.

The [milestones defined in GitHub](https://github.com/kubeedge/sedna/milestones) represent the most up-to-date plans.


## 2021 Q1 Roadmap

- Support edge model and dataset management.
- Support incremental learning, with time trigger, sample size trigger, and precision-based trigger, and integrating hard sample discovering algorithm.
- Support collaborative training, integrating some common weight/gradient compression algorithm.  


## Future

- Integrate some common multi-task migration algorithms to resolve the problem of low precision caused by small size samples.
- Integrate KubeFlow and ONNX into Sedna, to enable interoperability of edge models with diverse formats.
- Integrate typical AI frameworks into Sedna, include Tensorflow, Pytorch, PaddlePaddle and Mindspore etc.