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IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. In the context of Generative AI (GenAI), various embedding models are used to represent textual data.
Which of the following best describes the difference between Word2Vec, BERT, and Sentence-BERT embedding models?

A) Word2Vec captures contextual relationships between words, while BERT and Sentence-BERT generate sentence-level embeddings based on the overall document length.
B) Word2Vec uses a transformer architecture for embedding generation, whereas BERT and Sentence-BERT use neural networks to model context.
C) Word2Vec creates static word embeddings, BERT generates dynamic embeddings based on context, and Sentence-BERT produces embeddings specifically optimized for sentence-level tasks like semantic similarity.
D) Word2Vec captures both word and sentence meanings in a single vector space, BERT generates only word embeddings, and Sentence-BERT generates embeddings for entire documents.

2. You have applied a set of prompt tuning parameters to a language model and collected the following statistics: ROUGE-L score, BLEU score, and memory utilization.
Based on these metrics, how would you prioritize further optimizations to balance the model's performance in terms of output relevance and resource efficiency?

A) Focus on improving the ROUGE-L score while increasing memory utilization
B) Maximize BLEU score and reduce memory utilization
C) Increase memory utilization to reduce BLEU and ROUGE-L scores
D) Reduce memory utilization and maintain BLEU and ROUGE-L scores

3. You are tasked with generating a product description for an e-commerce platform using a generative AI model. However, you notice that the generated text tends to repeat phrases excessively, leading to verbose output. To address this, you decide to adjust the model's temperature parameter.
Which of the following changes would help reduce the repetitiveness of the generated text while maintaining a balance between creativity and coherence?

A) Decrease the temperature from 0.9 to 0.3
B) Set the temperature to 0.0
C) Decrease the temperature from 0.8 to 0.6
D) Increase the temperature from 0.5 to 1.5

4. You are tasked with integrating watsonx.ai into a legacy system that operates over HTTP and requires strict security and monitoring of the API calls. The legacy system lacks modern authentication mechanisms like OAuth.
Which integration method would best suit the needs of this environment while ensuring security and efficient API management?

A) Use REST API with API key-based authentication, leveraging HTTPS for encrypted communication between the legacy system and watsonx.ai.
B) Implement a GraphQL API to allow the legacy system to query specific fields and reduce payload size, thereby improving efficiency.
C) Use a REST API with OAuth authentication and token management to secure the communication.
D) Directly embed the watsonx.ai SDK into the legacy system to handle API management and security, eliminating the need for external API calls.

5. You are tasked with deploying a watsonx Generative AI solution for a client who requires real-time inference with minimal latency. The solution will be used for large-scale text generation tasks, where throughput is critical. The client also requires the system to handle fluctuating loads efficiently.
What would be the most appropriate deployment strategy?

A) Deploy the model on a multi-node GPU cluster with Kubernetes to handle auto-scaling and fault tolerance.
B) Deploy the model on a single GPU-based cloud instance with auto-scaling enabled.
C) Use a CPU-based deployment for cost efficiency, and manually adjust the number of instances as needed.
D) Deploy the model in a hybrid architecture, splitting inference tasks between on-premise servers and cloud resources.

Solutions: