SISA CSPAI Exam Questions Instant Access - No Installation Required

Question 1

In a financial technology company aiming to implement a specialized AI solution, which approach would most effectively leverage existing AI models to address specific industry needs while maintaining efficiency and accuracy?

AAdopting a Foundation Model as the base and fine-tuning it with domain-specific financial data to enhance its capabilities for forecasting and risk assessment.

BIntegrating multiple separate Domain-Specific GenAI models for various financial functions without using a foundational model for consistency

CBuilding a new, from scratch Domain-Specific GenAI model for financial tasks without leveraging preexisting models.

DUsing a general Large Language Model (LLM) without adaptation, relying solely on its broad capabilities to handle financial tasks.

Answer : A

Question 2

What is a key concept behind developing a Generative AI (GenAI) Language Model (LLM)?

AOperating only in supervised environments

BHuman intervention for every decision

CData-driven learning with large-scale datasets

DRule-based programming

Answer : C

Question 3

Which of the following is a potential use case of Generative AI specifically tailored for CXOs (Chief Experience Officers)?

ADeveloping autonomous vehicles for urban mobility solutions.

BAutomating financial transactions in blockchain networks.

CConducting genetic sequencing for personalized medicine

DEnhancing customer support through AI-powered chatbots that provide 24/7 assistance.

Answer : D

Question 4

Which of the following describes the scenario where an LLM is embedded 'As-is' into an application frame?

AIntegrating the LLM into the application without modifications, using its out-of-the-box capabilities directly within the application.

BReplacing the LLM with a more specialized model tailored to the application's needs.

CCustomizing the LLM to fit specific application requirements and workflows before integration.

DUsing the LLM solely for backend data processing, while the application handles all user interactions.

Answer : A

Question 5

What is a potential risk associated with hallucinations in LLMs, and how should it be addressed to ensure Responsible AI?

AHallucinations can lead to creative outputs, which are beneficial for all applications; hence, no measures are necessary.

BHallucinations cause models to slow down; optimizing hardware performance is necessary to mitigate this issue.

CHallucinations can produce inaccurate or misleading information; it should be addressed by incorporating external knowledge bases and retrieval systems.

DHallucinations are primarily due to overfitting; regularization techniques should be applied during training.

Answer : C

Question 6

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

Answer : D

Question 7

Which of the following is a primary goal of enforcing Responsible AI standards and regulations in the development and deployment of LLMs?

AMaximizing model performance while minimizing computational costs.

BDeveloping AI systems with the highest accuracy regardless of data privacy concerns

CFocusing solely on improving the speed and scalability of AI systems

DEnsuring that AI systems operate safely, ethically, and without causing harm.

Answer : D

SISA Certified Security Professional in Artificial Intelligence CSPAI Exam Questions