SISA CSPAI Exam Questions - Real Practice Questions for Guaranteed Success

Question 1

Which of the following is a characteristic of domain-specific Generative AI models?

AThey are designed to run exclusively on quantum computers

BThey are tailored and fine-tuned for specific fields or industries

CThey are only used for computer vision tasks

DThey are trained on broad datasets covering multiple domains

Correct : B

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AThey are designed to run exclusively on quantum computers

BThey are tailored and fine-tuned for specific fields or industries

CThey are only used for computer vision tasks

DThey are trained on broad datasets covering multiple domains

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Question 2

Which of the following is a method in which simulation of various attack scenarios are applied to analyze the model's behavior under those conditions.

Ainput sanitation

BModel firewall

CPrompt injections

DAdversarial testing

Correct : D

Adversarial testing involves systematically simulating attack vectors, such as input perturbations or evasion techniques, to evaluate an AI model's robustness and identify vulnerabilities before deployment. This proactive method replicates real-world threats, like adversarial examples that fool classifiers or prompt manipulations in LLMs, allowing developers to observe behavioral anomalies, measure resilience, and implement defenses like adversarial training or input validation. Unlike passive methods like input sanitation, which cleans data reactively, adversarial testing is dynamic and comprehensive, covering scenarios from data poisoning to model inversion. In practice, tools like CleverHans or ART libraries facilitate these simulations, providing metrics on attack success rates and model degradation. This is crucial for securing AI models, as it uncovers hidden weaknesses that could lead to exploits, ensuring compliance with security standards. By iterating through attack-defense cycles, it enhances overall data and model integrity, reducing risks in high-stakes environments like autonomous systems or financial AI. Exact extract: 'Adversarial testing is a method where simulation of various attack scenarios is applied to analyze the model's behavior, helping to fortify AI against potential threats.' (Reference: Cyber Security for AI by SISA Study Guide, Section on AI Model Security Testing, Page 140-143).

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Ainput sanitation

BModel firewall

CPrompt injections

DAdversarial testing

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Question 3

An AI system is generating confident but incorrect outputs, commonly known as hallucinations. Which strategy would most likely reduce the occurrence of such hallucinations and improve the trustworthiness of the system?

ARetraining the model with more comprehensive and accurate datasets.

BReducing the number of attention layers to speed up generation

CIncreasing the model's output length to enhance response complexity.

DEncouraging randomness in responses to explore more diverse outputs.

Correct : A

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ARetraining the model with more comprehensive and accurate datasets.

BReducing the number of attention layers to speed up generation

CIncreasing the model's output length to enhance response complexity.

DEncouraging randomness in responses to explore more diverse outputs.

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Question 4

How does the multi-head self-attention mechanism improve the model's ability to learn complex relationships in data?

ABy forcing the model to focus on a single aspect of the input at a time.

BBy ensuring that the attention mechanism looks only at local context within the input

CBy simplifying the network by removing redundancy in attention layers.

DBy allowing the model to focus on different parts of the input through multiple attention heads

Correct : D

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ABy forcing the model to focus on a single aspect of the input at a time.

BBy ensuring that the attention mechanism looks only at local context within the input

CBy simplifying the network by removing redundancy in attention layers.

DBy allowing the model to focus on different parts of the input through multiple attention heads

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Question 5

In a scenario where Open-Source LLMs are being used to create a virtual assistant, what would be the most effective way to ensure the assistant is continuously improving its interactions without constant retraining?

ATraining a larger proprietary model to replace the open-source LLM

BShifting the assistant to a completely rule-based system to avoid reliance on user feedback.

CImplementing reinforcement learning from human feedback (RLHF) to refine responses based on user input.

DReducing the amount of feedback integrated to speed up deployment.

Correct : C

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ATraining a larger proprietary model to replace the open-source LLM

BShifting the assistant to a completely rule-based system to avoid reliance on user feedback.

CImplementing reinforcement learning from human feedback (RLHF) to refine responses based on user input.

DReducing the amount of feedback integrated to speed up deployment.

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Master SISA CSPAI Exam with Reliable Practice Questions

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