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Exam C1000-185 Registration, Latest C1000-185 Test Question

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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q331-Q336):

NEW QUESTION # 331
You are tuning a generative AI model to reduce repetitive outputs, which often occur when generating long texts.
Which of the following parameter adjustments would most likely reduce the model's tendency to repeat words or phrases without compromising the quality of the generated text?

A. Lowering the temperature to 0.1
B. Increasing the Top-k value to 200
C. Increasing the repetition penalty to 1.2
D. Reducing the beam size to 1

Answer: C

NEW QUESTION # 332
You are building a RAG system in IBM watsonx for a legal document retrieval platform. The platform deals with highly structured legal texts and unstructured client queries. Your task is to ensure that both structured documents and unstructured queries can be efficiently retrieved using vector embeddings generated by the system.
Which of the following actions will help you optimize the generation of vector embeddings to support accurate retrieval in the RAG system, considering the diverse data types? (Select two)

A. Rely on pre-trained general-purpose embeddings without any domain-specific adaptation, as they provide broad coverage across many industries.
B. Generate embeddings for legal documents at the sentence level rather than the document level, as this increases precision in retrieval.
C. Use a separate embedding model for legal documents and client queries to account for differences in data structure.
D. Fine-tune the embedding model on legal text data to ensure embeddings capture the specific structure and semantics of the documents.
E. Ensure that embeddings for legal documents are based solely on the document metadata, as it contains the most important information.

Answer: C,D

NEW QUESTION # 333
In the context of AI governance, what is the most important aspect of managing model performance in a production environment to ensure compliance with regulatory and ethical guidelines?

A. Deploying the model only in secure, on-premises environments to prevent data breaches
B. Minimizing the model's inference time to optimize user experience
C. Ensuring traceability of model decisions and providing auditability for each inference
D. Maximizing the number of datasets the model is trained on to cover more use cases

Answer: C

NEW QUESTION # 334
Your team is tasked with enhancing a document search engine using IBM watsonx Discovery. The search engine will be used to help employees quickly find relevant internal documentation, such as policy guides, project specifications, and technical manuals. You have decided to use Retrieval-Augmented Generation (RAG) to enhance this search engine's performance. The current focus is on selecting the best retriever for the task and setting up a vector database to store document embeddings.
Which of the following retriever types is most suitable for this RAG-based search engine setup, considering the diverse and unstructured nature of the documents, and why?

A. Sparse retriever with BM25 ranking in combination with a traditional relational database.
B. Hybrid retriever that combines sparse retrieval methods with dense embeddings stored in a flat-file system.
C. Sparse retriever with BM25 ranking in combination with a traditional relational database.
D. Rule-based retriever using manually crafted rules to find documents based on predefined logic.

Answer: A

NEW QUESTION # 335
You are tasked with generating synthetic data for a fine-tuning task on an IBM watsonx model. The goal is to mimic the distribution of existing training data while ensuring the synthetic data maintains its statistical similarity to the original. You are provided with two algorithms, Algorithm A (Kolmogorov-Smirnov Test) and Algorithm B, to assess the similarity between the original and synthetic data distributions.
Which of the following best describes how you should implement synthetic data generation using the User Interface and choose the correct algorithm?

A. Use the User Interface to generate synthetic data and validate it using Algorithm B, which assesses the overall shape of the distributions but does not provide a significance test for statistical similarity.
B. Use the User Interface to generate synthetic data and validate it using Algorithm A, which compares the distributions' mean values to ensure close alignment.
C. Use Algorithm A (Kolmogorov-Smirnov Test) to compare the original and synthetic data distributions, checking for deviations across the entire data range.
D. Use Algorithm A (Kolmogorov-Smirnov Test) to match the covariance matrix of the original and synthetic data distributions, ensuring high correlation between data points.

Answer: C

NEW QUESTION # 336
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