Generative AI Leader Google Cloud QUESTIONS
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Terms in this set (103)
A law firm handles thousands of Fine-tune a foundation model like Gemini on the
legal documents daily and needs an firm's proprietary legal documents using Vertex AI
efficient way to summarize key Custom Training, and ensure data encryption
clauses and identify relevant
precedents. The summaries must be
highly accurate and maintain legal
terminology. The documents are
proprietary and sensitive. To build a
Generative AI solution for this task,
which approach would best balance
accuracy, domain specificity, and
data sensitivity?
,A large retail company wants to use Using a pre-trained LLM and performing extensive
Generative AI to create highly prompt engineering to inject customer specific
personalized email campaigns for its details and documents
customers. The emails should reflect
individual purchase history, browser
behavior, and stated preferences,
moving beyond generic templates.
The company has a vast amount of
customer data. To achieve this level
of personalization and scale, which
generative ai strategy would be most
effective?
What is the most effective way to Increase model size
reduce hallucinations in a gen ai
system?
,A home improvement maker Google Agentspace
company has multiple internal
systems to manage the operation like
sales, inventory, marketing, and
customer management. The company
decides to implement a central Gen
AI solution to easily access and
understand data across these
systems for better decisions and
efficiency. Which solution can help?
A MLOps team frequently updates Vertex AI Model Registry
and deploys new versions of a
generative AI model. They need a
system that allows them to track
change between model versions,
easily revert to previous working
version if a new deployment causes
issues, and ensure auditability. Which
Vertex AI Feature is essential for
managing model versions, facilitating
rollbacks, and maintaining a
historical record of deployed
models?
A chatbot for a fitness app gives Prompt engineering to request specific details
vague responses to workout-related
questions. What technique can
improve response specificity?
, A product team needs a low-code Vertex AI Studio
interface to quickly prototype with
pre-trained generative models from
Google without writing a lot of code.
Which Vertex AI tool should they
use?
A research institution has a vast, Vertex AI Search
frequently updated repository of
scientific papers. They want their
Generative AI assistant to answer
complex research questions by citing
specific passages from this internal
repository, avoiding generic or
hallucinated responses.Which Vertex
AI capability is specifically designed
to "ground" a Generative AI model
with an organization's proprietary
data for accurate, verifiable
responses?
A small business wants to use Using the Generative AI APIs directly
Google's cutting-edge Generative AI
models (like Gemini) for common
tasks such as text summarization and
translation, without needing to
manage complex model deployment
or infrastructure.Which Google
Cloud offering provides the easiest
way to consume these pre-trained
Generative AI models via APIs for
specific tasks?
AND ANSWERS LATEST UPDATE INSTANT
DOWNLOAD
Save
Terms in this set (103)
A law firm handles thousands of Fine-tune a foundation model like Gemini on the
legal documents daily and needs an firm's proprietary legal documents using Vertex AI
efficient way to summarize key Custom Training, and ensure data encryption
clauses and identify relevant
precedents. The summaries must be
highly accurate and maintain legal
terminology. The documents are
proprietary and sensitive. To build a
Generative AI solution for this task,
which approach would best balance
accuracy, domain specificity, and
data sensitivity?
,A large retail company wants to use Using a pre-trained LLM and performing extensive
Generative AI to create highly prompt engineering to inject customer specific
personalized email campaigns for its details and documents
customers. The emails should reflect
individual purchase history, browser
behavior, and stated preferences,
moving beyond generic templates.
The company has a vast amount of
customer data. To achieve this level
of personalization and scale, which
generative ai strategy would be most
effective?
What is the most effective way to Increase model size
reduce hallucinations in a gen ai
system?
,A home improvement maker Google Agentspace
company has multiple internal
systems to manage the operation like
sales, inventory, marketing, and
customer management. The company
decides to implement a central Gen
AI solution to easily access and
understand data across these
systems for better decisions and
efficiency. Which solution can help?
A MLOps team frequently updates Vertex AI Model Registry
and deploys new versions of a
generative AI model. They need a
system that allows them to track
change between model versions,
easily revert to previous working
version if a new deployment causes
issues, and ensure auditability. Which
Vertex AI Feature is essential for
managing model versions, facilitating
rollbacks, and maintaining a
historical record of deployed
models?
A chatbot for a fitness app gives Prompt engineering to request specific details
vague responses to workout-related
questions. What technique can
improve response specificity?
, A product team needs a low-code Vertex AI Studio
interface to quickly prototype with
pre-trained generative models from
Google without writing a lot of code.
Which Vertex AI tool should they
use?
A research institution has a vast, Vertex AI Search
frequently updated repository of
scientific papers. They want their
Generative AI assistant to answer
complex research questions by citing
specific passages from this internal
repository, avoiding generic or
hallucinated responses.Which Vertex
AI capability is specifically designed
to "ground" a Generative AI model
with an organization's proprietary
data for accurate, verifiable
responses?
A small business wants to use Using the Generative AI APIs directly
Google's cutting-edge Generative AI
models (like Gemini) for common
tasks such as text summarization and
translation, without needing to
manage complex model deployment
or infrastructure.Which Google
Cloud offering provides the easiest
way to consume these pre-trained
Generative AI models via APIs for
specific tasks?
