Roadmap

This document defines a high level roadmap for sedna development.

The milestones defined in GitHub 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.