with Correct Answers | Latest Update 2026 | Exam Prep |
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1. In a scenario where an AI model is used to predict customer preferences
based on past purchases, what role does input data play in this process?
Input data is used solely for storage purposes.
Input data is irrelevant to the AI model's predictions.
Input data only serves to confuse the AI model.
Input data provides the historical context needed for the AI model
to make accurate predictions.
2. Describe how data contributes to the learning process of machine learning
models.
Data is only used for storage and does not influence learning.
Data is used solely for testing the models after they are trained.
Data provides the necessary information for machine learning
models to identify patterns and make accurate predictions.
Data is irrelevant to machine learning and serves no purpose.
3. _________ focuses on creating artificial intelligence devices that can move and
react to sensory input.
Robotics
Drone
RFID
4. If an AI model is experiencing AI drift, what steps could a data scientist take
to mitigate its effects?
, Reduce the amount of training data used.
Ignore the drift and continue using the model as is.
Regularly update the model with new data.
Increase the model's complexity without new data.
5. What is the primary purpose of structured prompts in AI?
To enhance machine learning algorithms
To create random responses
To analyze user data
To guide output generation
6. In a scenario where an AI system is used to forecast stock market trends,
what role does prediction play in its functionality?
Prediction has no role in stock market analysis.
Prediction helps the AI system analyze past market data to forecast
future stock prices.
Prediction is used to evaluate the performance of the AI system itself.
Prediction only focuses on current market conditions.
7. Google applies generative AI to products like Google Workspace, but what is
generative AI?
A type of artificial intelligence that can create and sustain its own
consciousness.
A type of artificial intelligence that can understand and respond to
human emotions.
, A type of artificial intelligence that can make decisions and take
actions.
A type of artificial intelligence that can produce new content,
including text, images, audio, and synthetic data.
8. In a scenario where an AI chatbot misinterprets user intent, what might be a
potential consequence?
The AI will automatically correct its understanding.
The AI will escalate the issue to a human operator.
The user may receive irrelevant or unhelpful responses.
The user will be prompted to rephrase their query.
9. What is generative AI?
An AI that generates new content based on patterns from existing
data
An AI that is generated by an AI (also called "matrioska AI")
An AI that focuses on world domination and annihilation of human
race
A type of AI that focuses on analyzing and understanding existing
data
10. What is the primary purpose of Generative Artificial Intelligence (GAI)?
Identify existing patterns in data
Analyze historical data trends
Create new content resembling input data
Enhance data security algorithms
, 11. What is the primary focus of General AI?
Mimicking specific human behaviors
Enhancing natural language processing
Maximizing machine strengths
Emulating general human intelligence
12. How does an AI model typically "learn"?
It stores additional data into a database it can look-up later.
It determines more or improved parameter values in complex
mathematical models based on additional data.
It uses a special type of inference processor located near the CPU
that is capable of making connections between nodes similar to
neurons in the brain.
13. Describe the characteristics of detailed prompts and their role in AI
interactions.
Detailed prompts are only used in machine learning.
Detailed prompts are clear and specific instructions that provide
context and guide AI responses.
Detailed prompts are vague instructions that confuse AI responses.
Detailed prompts are irrelevant to AI systems.
14. Describe how machine learning differs from traditional programming in AI.
Machine learning algorithms are always more accurate than
traditional programming methods.