Roadmap

The roadmap is an encapsulation of the features that we intend to build for the Core Engine. However, please note that we limited resources and therefore no means of guaranteeing that this roadmap will be followed precisely as described on this page. Rest assured we are working to follow this diligently - please keep us in check!

We intend for this to be a reflection of the current thinking of what we and our users think are the most critical features to be prioritized and added to the Core Engine. If you do not agree with the prioritization, or see a feature here that you expect, please contact us at support@maiot.io, or join the chat in our Discord server.

Feature Roadmap (Updated May 25th 2020)

  • Ability to run custom code

    • Status: WIP
    • Expected: Early Q2 2020
  • Images as a datasource

    • Status: WIP
    • Expected: Early Q2 2020
  • Automatic Model Deployment

    • Status: WIP
    • Expected: Early Q2 2020
  • Enhanced support for trainer key (more layers, optimizers, models etc.)

    • Status: WIP
    • Expected: Mid Q2 2020
  • Hyper-parameter Tuning

    • Status: Not Started
    • Expected: Q2 2020
  • Distributed Training

    • Status: Not Started
    • Expected: Q3-Q4 2020
  • Continuous training pipelines

    • Status: Not Started
    • Expected: Q3-Q4 2020
  • Web Interface

    • Status: Not Started
    • Expected: Dependant on user feedback

History

  • Q1 2020:
    • Initial release of Core Engine. CLI interface launched.
    • Support for BigQuery as a datasource
    • Distributed preprocessing pipelines
    • Evaluation of single and multiple pipeline runs
    • Training with GPU
    • Timeseries support