Online Access Free CSPAI Exam Questions

What metric is often used in GenAI risk models to evaluate bias?

• A.Accuracy rate without considering demographics.
• B.Fairness metrics like demographic parity or equalized odds.
• C.Number of parameters in the model.
• D.Computational efficiency during training.

When deploying LLMs in production, what is a common strategy for parameter-efficient fine-tuning?

• A.Implementing multiple independent models for each specific task instead of fine tuning a single model
• B.Training the model from scratch on the target task to achieve optimal performance.
• C.Using external reinforcement learning to adjust the model's parameters dynamically.
• D.Freezing the majority of model parameters and only updating a small subset relevant to the task

In ISO 42001, what is required for AI risk treatment?

• A.Delegating all risk management to external auditors.
• B.Identifying, analyzing, and evaluating AI-specific risks with treatment plans.
• C.Focusing only on post-deployment risks.
• D.Ignoring risks below a certain threshold.

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?

• A.Encouraging randomness in responses to explore more diverse outputs.
• B.Retraining the model with more comprehensive and accurate datasets.
• C.Reducing the number of attention layers to speed up generation
• D.Increasing the model's output length to enhance response complexity.

In a Transformer model processing a sequence of text for a translation task, how does incorporating positional encoding impact the model's ability to generate accurate translations?

• A.It speeds up processing by reducing the number of tokens the model needs to handle.
• B.It simplifies the model's computations by merging all words into a single representation, regardless of their order
• C.It helps the model distinguish the order of words in the sentence, leading to more accurate translation by maintaining the context of each word's position.
• D.It ensures that the model treats all words as equally important, regardless of their position in the sequence.