It’s been an eventful week in the open source community — if you’re a deep learning practitioner or Google Cloud customer, that is.
A day after Amazon released Neo-AI, a framework for optimizing AI models, Google’s made the Cloud Search Connector SDK — a software development kit intended to bridge the gap between Google’s Cloud Search technology and enterprise content and identity repositories — freely available on GitHub.
As Google explained in a blog post, the identity and content connectors built with the SDK enable Google Cloud users to search on-premises, cloud, and software-as-a-service applications “more efficiently,” with the help of the Google Cloud Search Indexing API.
Machine learning powers the API’s instant query suggestions and surfaces results across different content systems in over 100 different languages.
Granular access-level controls — including individual-level, group-level, and content-based hierarchies — allow admins to prevent users from seeing search results they shouldn’t.
The Connector SDK is designed to handle tasks like service communication, multithreaded API operations, traversal strategies, connector configuration, error handling, and more, and it’s been used by partners to develop third-party connectors for over 50 sources, Google says.