2.1 Describe Google Cloud's Strengths in the Field of Gen AI. GENERATIVE-AI-LEADER Practice Questions (Page 4)

Questions 16–20

1. 16expert · hard

   A global bank is evaluating Google Cloud for a gen AI customer service application. They have strict regulatory requirements for data residency and auditability. They also want to avoid being locked into a single vendor's models. The bank's security team insists on using open-source models for transparency. How should the bank proceed?

   • AUse a third-party cloud that offers open-source models but no data residency options.
   • BDeploy the application on-premises and use Google Cloud only for storage.
   • CUse Google Cloud's data residency options, audit logging, and deploy open-source models on the platform.
   • DUse Google's proprietary models and rely on Google's compliance certifications.
   Reveal Solution Discussion Select an answer first
2. 17foundation · easy

   What is a key advantage of Google's comprehensive AI ecosystem?

   • AThe ecosystem is closed and does not support third-party integrations.
   • BGen AI capabilities are integrated across many Google products and services.
   • CGen AI is only available in Google Cloud, not in other Google products.
   • DThe ecosystem only includes hardware, not software.
   Reveal Solution Discussion Select an answer first
4. 18foundation · easy

   How does Google Cloud's open approach help avoid vendor lock-in?

   • ABy offering only proprietary APIs.
   • BBy requiring users to use only Google Cloud services.
   • CBy supporting open standards and interoperability with other platforms.
   • DBy preventing users from exporting their data.
   Reveal Solution Discussion Select an answer first
5. 19application · medium

   A small marketing agency with no data science team wants to add AI-powered content generation to their campaigns. They need a solution that requires minimal coding and can be integrated with their existing Google Analytics and Google Ads. What should they use?

   • AUse an open-source model hosted on a competitor's cloud and manually export data to Google Ads.
   • BUse Google Cloud's pre-trained models and APIs, such as the Gemini API, and integrate with Google Analytics and Ads.
   • CBuild a custom model using TensorFlow and deploy it on Vertex AI.
   • DHire a team of ML engineers to build a bespoke solution from scratch.
   Reveal Solution Discussion Select an answer first
6. 20expert · hard

   A large enterprise is choosing a cloud provider for a strategic gen AI initiative. They value being at the forefront of AI technology and need to scale from prototype to production quickly. They also have a mandate to use the most advanced hardware available. The CTO is concerned about the risk of the provider's AI roadmap stagnating. Which combination of Google Cloud strengths best addresses these concerns?

   • AOpen-source model support and multi-cloud deployment.
   • BEnterprise-ready security and compliance certifications.
   • CAI-first strategy, continuous innovation, and AI-optimized infrastructure like TPUs.
   • DLow-code tools and pre-trained models for rapid development.
   Reveal Solution Discussion Select an answer first