Question 1

You are working on a recommendation system for an e-commerce platform that needs to provide personalized product suggestions based on customer behavior and preferences. The system must handle large volumes of data, including user interactions, product descriptions, and reviews. Given that your company is already using the Databricks Lakehouse platform, which approach would be most efficient for implementing this recommendation system?

Options :

A : Implement a third-party vector database and integrate it with the existing Databricks Lakehouse platform for managing and querying high-dimensional data.

B : Use a traditional relational database to store and query user data and product information, integrating it with the recommendation system.

C : Develop a custom in-house solution for vector storage and search, integrating it with the Databricks Lakehouse platform.

D : Utilize the Databricks Vector Search to store, index, and query vector embeddings of user interactions and product data, leveraging its tight integration with the Databricks Lakehouse platform.

Answer: D

Question 2

You are developing an AI application that needs to handle and generate diverse types of content for an interactive storytelling platform. The platform must integrate text and images seamlessly, allowing users to generate stories with accompanying visuals. Which of the following approaches best leverages Multi-Model Architectures for this scenario?

Options :

A : Embed text and images into the same vector space but do not use any advanced Multi-Modal LLMs, relying on basic retrieval systems to handle each modality individually.

B : Use one modality, such as text, as the primary focus and adapt images according to predefined templates or rules, without dynamically generating or integrating images with the text.

C : Use a Multi-Modal LLM like GPT-4V(ision) to generate both the narrative text and associated images in a unified manner, allowing the system to produce a story with integrated visuals based on user input.

D : Store text and images separately in distinct databases, and use separate models for text generation and image retrieval, without integrating them into a single system.

Answer: C

Question 3

When choosing between "Deploy Model" and "Deploy Code" patterns in a Databricks environment, which approach is generally recommended for more effective management of ML workflows?

Options :

A : Deploy Model: Move the model artifact from staging to production after training in the dev environment, and handle other code (inference, monitoring) separately.

B : Deploy Code: Develop and test code in separate environments, then deploy it to production, ensuring the training pipeline is also run in each environment while deploying the model only in production.

C : Deploy Model: Train the model in the development environment and deploy it directly to production without separate processes for inference and monitoring.

D : Deploy Code: Train the model only in the production environment and use the same environment for testing and deployment.

Answer: B

Question 4

As a Gen AI engineer managing the lifecycle of models in MLflow, which of the following URI patterns are used for referencing models in the Unity Catalog (MLflow) Model Registry? Choose two correct answers.

Options :

A : models:/{model_name}/latest

B : models:/{model_name}@{alias}

C : models:/{model_name}@{version}

D : models:/{model_name}/{model_version}

Answer: B,D

Question 5

As a Gen AI engineer setting up LLM-as-a-Judge for evaluating your model outputs, which of the following best practices should you follow to ensure effective evaluation?

Options :

A : Employ a wide variety of examples, including only examples of good outputs, to guide the LLM’s evaluation process.

B : Use a broad rubric scale, such as 1-10, to capture nuanced differences in the quality of outputs.

C : Use a high-token LLM to provide more context and detail in the evaluation, improving the quality of feedback from the model.

D : Avoid using an additive scale, as it can complicate the evaluation process and introduce inconsistencies.

Answer: C

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