Google Delays Paid Access Requirement for Gemini in BigQuery

January 28, 2025 at 5:54:19 AM

TL;DR Google has enhanced BigQuery ML with new generative AI capabilities and improved access control features. Updates include remote model creation using open models from Vertex Model Garden or Hugging Face, support for text generation models like Llama and Gemma, and new functions like ML.GENERATE_TEXT and ML.EVALUATE. Google has also delayed Gemini procurement requirements, allowing users to access its features for free until further notice.

Google Delays Paid Access Requirement for Gemini in BigQuery

Google has announced a temporary extension of free access to Gemini features in BigQuery, postponing the previously planned purchase requirement that was set to take effect after January 27, 2025. The company will continue to provide free access to Gemini functionality until further notice.

New Generative AI Capabilities

Google has expanded BigQuery ML's capabilities with several generally available features that enhance its generative AI functionality. The platform now supports:

  • Remote model creation using open models from Vertex Model Garden or Hugging Face
  • Integration with leading text generation models including Llama and Gemma
  • Implementation of the ML.GENERATE_TEXT function for diverse AI tasks
  • Addition of the ML.EVALUATE function for model evaluation

Enhanced Security Controls

The update introduces conditional IAM (Identity and Access Management) access controls for BigQuery datasets using access control lists (ACLs). This security enhancement is now generally available, providing administrators with more granular control over dataset access permissions.

Users can explore these new features through the Generate text documentation and tutorials, which demonstrate the use of ML.GENERATE_TEXT function and Gemma open model integration.

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