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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q298-Q303):

NEW QUESTION # 298
You are configuring a chatbot using IBM Watsonx, and you want the chatbot to respond appropriately based on the conversation's context.
Which of the following best represents an appropriate stopping criterion for a task where the chatbot generates step-by-step instructions?

A. The model will stop generating as soon as the probability of the next token falls below the median probability of previously generated tokens.
B. The model will stop generating once the instruction count reaches five steps, regardless of whether the task has been fully described.
C. The model will stop generating once it encounters a user query that requires it to reevaluate the entire prompt context and restart from the beginning.
D. The model will stop generating once it identifies a natural completion of the task description, such as reaching a final instruction or a conclusion marker (e.g., "All done").

Answer: D

NEW QUESTION # 299
You are tasked with designing a prompt to translate a sentence from English to French using an AI model.
Which of the following prompt would best guide the AI to achieve accurate translation, while maintaining cultural nuance and avoiding literal word-for-word translation?

A. "Translate the following sentence from English to French: 'The weather is nice today.'"
B. "Explain the meaning of 'The weather is nice today' in French."
C. "Translate the sentence 'The weather is nice today' into French and make sure to avoid literal translation, focusing on cultural nuances."
D. "Translate 'The weather is nice today' to French but ensure that the translation reflects word-for-word accuracy and no cultural considerations."

Answer: C

NEW QUESTION # 300
You are developing a generative AI application using LangChain, and you want the system to perform actions like searching a database or retrieving live web content based on a user's request.
How can you best incorporate tools in LangChain to enable the AI to perform such tasks autonomously?

A. Rely on LangChain's memory module to remember previous user queries and provide real-time data access.
B. Configure LangChain to automatically load data from static sources based on historical query patterns, avoiding the need for dynamic tool selection.
C. Build a LangChain chain that uses user inputs to sequentially call all the available tools and pick the one with the most relevant output.
D. Use a LangChain agent with a predefined set of tools to dynamically select and invoke the appropriate tool (e.g., database access, API call) based on the user's request.

Answer: D

NEW QUESTION # 301
Which quantization technique aims to optimize a model by converting weights and activations into 8-bit integers while minimizing the impact on the model's performance?

A. Quantization-aware training (QAT)
B. Hybrid quantization
C. Post-training dynamic quantization
D. Post-training static quantization

Answer: A

NEW QUESTION # 302
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. Directly embed the watsonx.ai SDK into the legacy system to handle API management and security, eliminating the need for external API calls.
B. Use a REST API with OAuth authentication and token management to secure the communication.
C. Implement a GraphQL API to allow the legacy system to query specific fields and reduce payload size, thereby improving efficiency.
D. Use REST API with API key-based authentication, leveraging HTTPS for encrypted communication between the legacy system and watsonx.ai.

Answer: D

NEW QUESTION # 303
......

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