Whitepaper Edits
Created on April 1|Last edited on April 1
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Gemini Branding: While Gemini is mentioned, given its prominence in Google's AI strategy, its capabilities and role within Vertex AI Agent Builder could potentially be highlighted more explicitly or earlier in the document
We can add changes in the following sections. For the "Maintaining Quality" section, we could add:
Support for Gemini 2.5 Pro and other Gemini models enhances reasoning and consistency in production environments.
And also add a similar sentence to the "Building with Vertex AI" section here.
Add the following Sentence:
Developers can build and deploy generative AI applications that are tailored to their organization’s needs while leveraging Google’s most advanced models, including Gemini 2.5 Pro.
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Specificity on Google Cloud Integration: While integration is mentioned, the Ebook could benefit from slightly more specific examples or details on how Vertex AI integrates seamlessly with other Google Cloud services (e.g., specific workflows involving BigQuery for data sourcing or Cloud Monitoring for infrastructure observability).
We could add a sentence about Cloud Monitoring for infrastructure observability in the "Scalability and Google Cloud integration" section.
Add: Cloud Monitoring can be used alongside Vertex AI to provide real-time infrastructure observability, helping teams detect and resolve performance issues quickly.
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Visuals: Image 3 appears to show code related to openai.chat.completions.create (on Page 10)
While W&B Weave is LLM-agnostic, ensuring visuals align closely with the Google Cloud/Vertex AI focus where possible is important for any material to be presented at Next25.
And also traces from an AIME eval using Gemini here. (Note you will need to select evals that use a Gemini Model)
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