Google Cloud updated its AI Hub to enable more collaboration between data scientists and machine learning teams.
AI Hub, which launched as a beta in April, is getting an overhaul that includes a new home page, machine learning taxonomy, more content and the ability to favorite notebooks, models and other assets.
Google Cloud outlined the AI Hub upgrades at one of its CloudNext gatherings in San Francisco.
However, the sharing features are more likely to have a larger impact on data science workflows. The sharing, permission, and collaboration features in AI Hub rhyme with what's available in G Suite today.
Google Cloud bets that data scientists and developers will collaborate more with a familiar sharing interface that allows them to share notebooks, trained machine learning models and KubeFlow pipelines.
The new AI Hub home page allows logged in users to access recent shared private assets and content designed for faster model building.
Collaboration with groups and permissions to enable colleagues to edit or just view. One key caveat: "'Viewers' will still be able to fork the asset you share by downloading or opening a copy, but they won't be able to edit or change the version shared on AI Hub."
URLs of public assets can be shared on social media.
The ability to label and categorize machine learning assets using a list of data types, techniques and use cases.
More than 70 new content assets for tutorials on model building.
Here are a few screens of the home page and documentation areas.