EXIN BCS Gen AI Award Practice Questions - EXIN BCS Generative Artificial Intelligence Award Exam - EXIN BCS Gen AI Award Practice Questions - EXIN BCS Generative Artificial Intelligence Award Exam

Question 1

What is the primary distinction between traditional discriminative machine learning models and generative AI models?

Discriminative models classify or predict labels based on input data, whereas generative models learn data distributions to create new, plausible data instances. Discriminative models use neural networks, whereas generative models rely exclusively on rule-based expert systems. Discriminative models process unlabelled data, whereas generative models require fully supervised labelled data for training. Discriminative models generate continuous numerical outputs, whereas generative models only output discrete text tokens.

Correct Answer:

Discriminative models classify or predict labels based on input data, whereas generative models learn data distributions to create new, plausible data instances.

Question 2

Which architectural innovation introduced in the 2017 paper 'Attention Is All You Need' forms the foundation of modern Large Language Models?

Convolutional Neural Network (CNN) Recurrent Neural Network (RNN) Transformer Generative Adversarial Network (GAN)

Correct Answer:

Transformer

Question 3

What is the primary function of the self-attention mechanism within a Transformer model?

It dynamically calculates importance weights between every pair of tokens in a sequence, allowing the model to capture long-range contextual relationships. It compresses the input text into a single static scalar score to reduce memory consumption. It filters out stopwords and irrelevant vocabulary prior to model processing. It enforces strict sequential left-to-right grammar rules across input tokens.

Correct Answer:

It dynamically calculates importance weights between every pair of tokens in a sequence, allowing the model to capture long-range contextual relationships.

Question 4

In the context of Large Language Models, what does 'tokenization' refer to?

The process of encrypting text before sending it over an external API connection. The process of breaking input text into smaller sub-word or word units (tokens) and mapping them to numerical identifiers. The assignment of monetary API charges based on output length. The technique of converting user prompts into database SQL queries.

Correct Answer:

The process of breaking input text into smaller sub-word or word units (tokens) and mapping them to numerical identifiers.

Question 5

What occurs when an input prompt exceeds the maximum 'context window' of a Large Language Model?

The model automatically increases its underlying parameter count to accommodate the extra tokens. Tokens beyond the maximum context window limit are truncated or ignored, causing loss of earlier contextual information. The model executes fine-tuning on the additional context in real time. The model returns an encrypted cryptographic hash instead of generating text.

Correct Answer:

Tokens beyond the maximum context window limit are truncated or ignored, causing loss of earlier contextual information.

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Prepare with the EXIN BCS Gen AI Award Practice Questions - EXIN BCS Generative Artificial Intelligence Award Exam practice quiz. This question bank includes 100 questions covering prompt, models, large, language, and model. Use it to review important concepts, identify knowledge gaps, and build confidence for the related exam, course, or assessment.

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EXIN BCS Gen AI Award Practice Questions - EXIN BCS Generative Artificial Intelligence Award Exam

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EXIN BCS Gen AI Award Practice Questions - EXIN BCS Generative Artificial Intelligence Award Exam

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