This content explores various aspects of generative AI, including model limitations, data types, relevant Google Cloud products, agent types, model settings, and strategic benefits of AI adoption.
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A company trains a generative AI model
designed to classify customer feedback
as positive, negative, or neutral.
However, the training data set
disproportionately includes feedback
from a specific demographic and uses
outdated language norms that don't
reflect current customer communication
styles. When the model is deployed, it
shows a strong bias in its sentiment
analysis for new customer feedback,
misclassifying reviews from
underrepresented demographics, and
struggling to understand current slang
or phrasing.
What type of model limitation is this? A
data dependency.
B edge case.
C. Hallucination.
A company collects customer feedback
through open-ended survey questions
where customers can write detailed
responses in their own words such as the
product was easy to use and the customer
support was excellent but the delivery
took longer than expected.
What type of data is this? A
unstructured data B structured data. C a
labelled data. D a quantitative data.
A national bank is overwhelmed by
customer inquiries across multiple
channels and needs an AI powered
solution to provide seamless consistent
support, empower customer support agents
and improve service quality.
What Google Cloud product should the
bank use? A. Vertex AI search. B. Gemini
for Google Workspace.
C. Google contact center as a service.
D. Gemini for Google Cloud.
Correct answer C. Google contact center
An order fulfillment team has an agent
that automatically processes orders,
updates inventory, sends shipping
notifications, and handles returns.
What type of agent is this? A a workflow
agent. B an employee productivity agent.
C. A customer service agent.
D a conversational agent.
A team is using a generative AI model to
automatically generate short summaries
of customer feedback.
They need to ensure that these summaries
are concise and easy to digest.
What model setting should they adjust?
At top p nucleus sampling, b safety settings.
settings.
C a temperature.
D output length.
What is nucleus sampling? Top P. A
sampling from tokens whose cumulative
probability is greater than P. B.
Removing tokens under a probability threshold.
threshold.
C. Combining top K and temperature.
D. using all tokens with equal probability.
probability.
Correct answer A.
Sampling from tokens whose cumulative
probability is greater than P. Nucleus
sampling selects from the smallest set
of tokens that add up to a cumulative
What does model garden enable a company
to do? A discover, customize, and deploy
existing models from Google and its partners.
partners.
B evaluate the performance of different
models using various metrics.
C. Manage different versions of a model,
including the code, data, and parameters
used to train it. D. Train new models
from scratch using large data sets.
What is the primary benefit of using a
foundation model like Palm 2 in a
generative AI solution?
A. It avoids the need for any prompt engineering.
engineering.
B. It eliminates all bias from AI systems.
systems.
C. It can be fine-tuned or prompted for
a wide range of tasks.
D. It replaces the need for labeled
training data. Answer. C. It can be
fine-tuned or prompted for a wide range
of tasks.
Answer C. It can be fine-tuned or
What does top K sampling do in
generative text generation?
A keeps only the K longest words. B
samples the next token from the top K
most probable options.
C keeps tokens with the least frequency.
D ignores all punctuation.
Correct answer. B samples the next token
from the top K most probable option. Top
EK sampling limits the model's choice to
the K most likely tokens, helping
Which two benefits do organizations
typically achieve from adopting Gen AI strategically?
strategically?
Choose two. A full elimination of all
manual workflows.
B faster content creation and customization.
customization.
C. Improved personalization for customers.
customers.
D. Guaranteed zero hallucinations.
Which two use cases benefit most from
prompt chaining? Choose two uh
multi-step reasoning tasks,
B image segmentation,
C conversational workflows,
D and neural architecture search.
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