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v2.1 (02/28/2025)

New Features

Improvements

  • Improved stability of XAI

Bug Fixes

  • Fixed a crucial bug in which majority_sampling_ratio was not working as expected

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v2.0 (02/14/2025)

We’re thrilled to announce a major update to the Kumo platform, featuring a fully redesigned interface and . This update brings a more streamlined, modern look and feel to the platform—making it easier for ML engineers and data scientists to train and run models.

What’s New:

  • **Redesigned Navigation & Layout. **A cleaner layout and intuitive navigation bar help you find the right features faster—reducing clicks and saving you time when setting up data connections or reviewing model outputs.
  • Powerful new Python SDK. Designed to use Kumo in your favorite IDE or notebook, seamlessly integrate with the UI, enabling robust, flexible, and interoperable workflows between code and visual interactions. SDK Reference.
  • Enhanced Workflows. An intuitive expeirence to help select graphs and train models faster with quicker iterations.

Improvements

  • Reduced the time between AutoML trials to a minimum, significantly speeding up execution, especially for workflows with many trials.
  • Improved encoding efficiency: Raw data is now encoded and hashed upon graph snapshotting, leading to improved security and faster execution.
  • Relative time is now computed for all timestamp columns, independent of whether they were assigned as a designated time column.
  • Kumo can now gracefully handle timestamps outside of UNIX/int64 range
  • Introduce job queuing for individual workflow like training table generation, prediction table generation, etc.

Bug Fixes

  • Fix bugs for concurrent table ingestion workflow.

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v1.47 (01/31/2025)

New Features

  • Supporting XAI in batch predictions.

Improvements

  • Improved stability of Explanations of models
  • More robust encoder logic for highly skewed numerical distributions
  • Fixed artifact export to Snowflake and DB.
  • Improve memory efficiency for global baselines.
  • Improved health check for concurrent jobs.

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v1.46 (01/17/2025)

Features

  • Forecasting: added year-over-year and handle_new_entities option labels to support learning seasonal and holiday trends.
  • Improved syntax error messaging in Model Plan for better clarity.
  • Extended support for long-duration training jobs and batch predictions (2 to 20 days).

Bug Fixes

  • Resolved timestamp data type casting issues. Users no longer need to specify ts_format or unit for affected datasets.
  • Corrected estimated prediction times for large output sizes to improve accuracy.

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v1.45 (01/06/2025)

Features

  • Kumo can now be run as a Native app on Snowflake Azure regions.

Bug Fixes

  • Resolved bar graph display issues within the Subgraph table.

Breaking Change

  • Reduced download limit of holdout dataset to 1M entities.