May 2024¶
May 22, 2024
This page provides announcements of newly released features available in DataRobot's SaaS single- and multi-tenant AI Platform, with links to additional resources. From the release center, you can also access:
In the spotlight: Asset migration¶
Deployed last month, DataRobot allows you to transfer projects and notebooks created in DataRobot Classic to DataRobot NextGen. This is how.
Video: Asset migration
Preview documentation.
Feature flag OFF by default: Enable Asset Migration
The following table lists each new feature:
Features grouped by capability
| Name | GA | Preview |
|---|---|---|
| Generative AI | ||
| Anthropic Claude 2.1 now available | ✔* | |
| Predictions and MLOps | ||
| Batch prediction output support for SAP HANA JDBC connector | ✔ | |
| Notebooks | ||
| Create schedules for Codespaces | ✔ | |
| API | ||
| Python client v3.4 | ✔ | |
| DataRobot REST API v2.33 | ✔ | |
| Deprecations and migrations | ||
| DataRobot account portal deprecation | ||
* Premium feature
GA¶
Anthropic Claude 2.1 now available¶
Now available on SaaS, the DataRobot GenAI playground introduces Anthropic Claude 2.1 as an LLM option when constructing LLM blueprints. Claude Anthropic is an open-source generative LLM that is the base model that powers many chatbots, billing itself as the “ethical alternative.” It is available in new experiments and also can be added to existing playgrounds.
Batch prediction output support for SAP HANA JDBC connector¶
DataRobot now supports JDBC write-back when you configure a JDBC prediction destination using a SAP HANA data connection through the Job Definitions UI or the Batch Prediction API.
For a complete list of supported output options, see the data sources supported for batch predictions.
Preview¶
Create schedules for codespaces¶
Now available as a preview feature, you can automate your code-based workflows by scheduling notebooks in codespaces to run on a schedule in non-interactive mode. Scheduling is managed by notebook jobs, and you can only create a new notebook job when your codespace is offline. You can also parameterize a notebook to enhance the automation experience enabled by notebook scheduling. By defining certain values in a codespace as parameters, you can provide inputs for those parameters when a notebook job runs instead of having to continuously modify the notebook itself to change the values for each run.
Preview documentation.
Feature flag ON by default: Enable Codespace Scheduling
API¶
Python client v3.4¶
v3.4 for DataRobot's Python client is now generally available. For a complete list of changes introduced in v3.4, view the Python client changelog.
DataRobot REST API v2.33¶
DataRobot's v2.33 for the REST API is now generally available. For a complete list of changes introduced in v2.33, view the REST API changelog.
Deprecations and migrations¶
DataRobot account portal deprecation¶
In this release, the DataRobot account portal is deprecated and removed. This deprecation updates the appearance and selection of DataRobot user profile settings, as shown below.
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