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質問 1：
When deploying LLMs in production, what is a common strategy for parameter-efficient fine-tuning?
A. Using external reinforcement learning to adjust the model's parameters dynamically.
B. Implementing multiple independent models for each specific task instead of fine tuning a single model
C. Freezing the majority of model parameters and only updating a small subset relevant to the task
D. Training the model from scratch on the target task to achieve optimal performance.
正解：C
解説: (Pass4Test メンバーにのみ表示されます)
質問 2：
In the Retrieval-Augmented Generation (RAG) framework, which of the following is the most critical factor for improving factual consistency in generated outputs?
A. Utilising an ensemble of multiple LLMs to cross-check the generated outputs.
B. Fine-tuning the generative model with synthetic datasets generated from the retrieved documents
C. Tuning the retrieval model to prioritize documents with the highest semantic similarity
D. Implementing a redundancy check by comparing the outputs from different retrieval modules.
正解：C
解説: (Pass4Test メンバーにのみ表示されます)
質問 3：
In assessing GenAI supply chain risks, what is a critical consideration?
A. Focusing only on internal development risks.
B. Evaluating third-party components for embedded vulnerabilities.
C. Assuming all vendors comply with standards automatically.
D. Ignoring open-source dependencies to reduce complexity.
正解：B
解説: (Pass4Test メンバーにのみ表示されます)
質問 4：
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 ensures that the model treats all words as equally important, regardless of their position in the sequence.
B. It speeds up processing by reducing the number of tokens the model needs to handle.
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 simplifies the model's computations by merging all words into a single representation, regardless of their order
正解：C
解説: (Pass4Test メンバーにのみ表示されます)
質問 5：
What aspect of privacy does ISO 27563 emphasize in AI data processing?
A. Storing all data indefinitely for auditing.
B. Consent management and data minimization principles.
C. Maximizing data collection for better AI performance.
D. Sharing data freely among AI systems.
正解：B
解説: (Pass4Test メンバーにのみ表示されます)
When deploying LLMs in production, what is a common strategy for parameter-efficient fine-tuning?
A. Using external reinforcement learning to adjust the model's parameters dynamically.
B. Implementing multiple independent models for each specific task instead of fine tuning a single model
C. Freezing the majority of model parameters and only updating a small subset relevant to the task
D. Training the model from scratch on the target task to achieve optimal performance.
正解：C
解説: (Pass4Test メンバーにのみ表示されます)
質問 2：
In the Retrieval-Augmented Generation (RAG) framework, which of the following is the most critical factor for improving factual consistency in generated outputs?
A. Utilising an ensemble of multiple LLMs to cross-check the generated outputs.
B. Fine-tuning the generative model with synthetic datasets generated from the retrieved documents
C. Tuning the retrieval model to prioritize documents with the highest semantic similarity
D. Implementing a redundancy check by comparing the outputs from different retrieval modules.
正解：C
解説: (Pass4Test メンバーにのみ表示されます)
質問 3：
In assessing GenAI supply chain risks, what is a critical consideration?
A. Focusing only on internal development risks.
B. Evaluating third-party components for embedded vulnerabilities.
C. Assuming all vendors comply with standards automatically.
D. Ignoring open-source dependencies to reduce complexity.
正解：B
解説: (Pass4Test メンバーにのみ表示されます)
質問 4：
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 ensures that the model treats all words as equally important, regardless of their position in the sequence.
B. It speeds up processing by reducing the number of tokens the model needs to handle.
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 simplifies the model's computations by merging all words into a single representation, regardless of their order
正解：C
解説: (Pass4Test メンバーにのみ表示されます)
質問 5：
What aspect of privacy does ISO 27563 emphasize in AI data processing?
A. Storing all data indefinitely for auditing.
B. Consent management and data minimization principles.
C. Maximizing data collection for better AI performance.
D. Sharing data freely among AI systems.
正解：B
解説: (Pass4Test メンバーにのみ表示されます)
Ruike -
やはりアプリの方が頭に入りやすいから、あるのは嬉しい。
役に立った。受かる可能性は大きい。