Why Google Cloud for gen AI
Generative AI Leader · Lesson 4 of 14 · 32:36
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In this lesson
Prepare for the Google Cloud Generative AI Leader exam. In this lesson: Google's AI-first approach and the gen AI integrated across its ecosystem, Google Cloud's open approach (more than 200 models in Model Garden, an open-source, model-agnostic Agent Development Kit), an enterprise-ready platform (responsible, secure, private, reliable, scalable, with Google's commitment not to train models on customer data without permission), AI Hypercomputer with TPUs and GPUs, data controls (data residency, customer-managed keys, VPC Service Controls, Access Transparency, agent identities, Model Armor), and how low-code tools, pre-trained models, and APIs democratize AI. Includes three original practice questions.
Preview the topics
- Cymbal Retail wants Gemini for some tasks and a partner’s model for others, all managed on one platform, with the freedom to switch later. Which Google Cloud strength is this?
- Cymbal Retail’s legal team asks what happens to the product data and prompts it sends to Agent Platform. What does Google Cloud commit to?
- Cymbal Retail’s merchandising team has no machine learning engineers, but it wants a custom model that sorts product photos into its own categories, from photos it has already labeled. What should it use?