Generative AI Leader Google AI Ecosystem and Strategy Practice Test 2 — 15 Questions

Question 1

A healthcare startup needs to process sensitive patient data using NLP models on Google Cloud. They require HIPAA compliance and the ability to run models within their VPC. Which service should they use to access Gemini models?

Accepted Answer

Vertex AI. Vertex AI provides enterprise-grade features including VPC Service Controls, data isolation, and HIPAA BAA. Google AI Studio is free-tier prototyping only and does not offer these compliance or security controls.

Answer

Gemini API directly via API key

Answer

BigQuery ML

Answer

Google AI Studio

Question 2

A data science team wants to run a large-scale transformer training job with custom model architectures. They need the highest compute density for a multi-node job and want to minimize inter-node communication latency. Which Google Cloud infrastructure is BEST suited for this workload?

Accepted Answer

TPU v4 Pod slices with high-speed inter-chip interconnect. TPU v4 Pod slices provide the highest compute density for multi-node transformer training by using a custom 3D torus interconnect with 800 Gbps per chip bandwidth, which minimizes inter-node communication latency far below what standard networking can achieve. This architecture is specifically designed for large-scale model parallelism, making it ideal for custom transformer architectures that require frequent all-reduce and collective communication operations.

Answer

A single TPU v5e VM with multiple accelerators

Answer

A cluster of A100 GPU VMs connected via standard networking

Answer

Cloud Run jobs with GPU acceleration

Question 3

A company wants to build a text-to-speech application for generating voiceovers in multiple languages. They need to use a pre-built Google API without training custom models. Which service should they use?

Accepted Answer

Cloud Text-to-Speech API. Cloud Text-to-Speech API is a pre-built service for converting text to natural-sounding speech in many languages. The other options are either for speech recognition or not pre-built APIs.

Answer

Vertex AI Text-to-Speech with a custom model

Answer

Gemini API with a custom prompt

Answer

Cloud Speech-to-Text API

Question 4

A financial analyst wants to run a regression model inside BigQuery using SQL, without moving data to a separate ML environment. Which Google Cloud service allows this directly?

Accepted Answer

BigQuery ML. BigQuery ML enables creating and running ML models using standard SQL queries directly in BigQuery. Vertex AI and AI Platform require data to be moved, and AutoML is a higher-level service but still not SQL-based.

Answer

AI Platform

Answer

AutoML Tables

Answer

Vertex AI

Question 5

A machine learning engineer needs to deploy a Gemini model on an Android device for offline inference (no internet connection) to provide real-time suggestions. Which Gemini model variant is MOST appropriate?

Accepted Answer

Gemini Nano. Gemini Nano is specifically designed for on-device inference with small memory footprint. Ultra, Pro, and Flash are cloud-only models that require internet connectivity.

Answer

Gemini Ultra

Answer

Gemini Pro

Answer

Gemini Flash

Question 6

A researcher wants to quickly prototype an AI model using a free, hosted Jupyter notebook environment with GPU support. Which Google product is BEST suited for this?

Accepted Answer

Google Colab. Google Colab provides free hosted Jupyter notebooks with GPU support. Kaggle is for datasets and competitions but not primarily for notebooks. Vertex AI Workbench and AI Platform are enterprise tools with costs.

Answer

AI Platform Notebooks

Answer

Kaggle Notebooks

Answer

Vertex AI Workbench

Question 7

A company is evaluating Google Cloud vs AWS Bedrock for building a multimodal application that needs to understand images, video, and text in a single model. Which unique Google Cloud capability supports this requirement?

Accepted Answer

Gemini API's native multimodal support across text, images, video, and audio. Gemini is a natively multimodal model capable of processing text, images, audio, video, and code. AWS Bedrock's models are primarily text or image-only, lacking native video understanding.

Answer

Use of Hugging Face models on Vertex AI

Answer

Integration with Amazon Bedrock's Titan model

Answer

BigQuery ML's image analysis functions

Question 8

A company needs to extract structured data from scanned invoices (invoice number, date, total amount) using a pre-built AI solution. Which Google Cloud service is MOST appropriate?

Accepted Answer

Document AI. Document AI is specifically designed for processing documents like invoices and extracting structured data. Vision AI is for general image analysis, Natural Language AI for text, and Translation API for translation.

Answer

Natural Language AI

Answer

Translation API

Answer

Vision AI

Question 9

A company is deploying a chatbot using Vertex AI and wants to ensure that the model's responses are grounded in Google Search results to reduce hallucinations. Which feature should they enable?

Accepted Answer

Vertex AI Search for grounding. Google Search grounding in Vertex AI allows the model to retrieve real-time information from Google Search to ground answers. RAG uses private data, not web search. Vertex AI Agent Builder includes grounding but is for building agents, not specifically the grounding feature itself.

Answer

Vertex AI Agent Builder

Answer

Retrieval-Augmented Generation (RAG) with internal documents

Answer

Gemini API with custom fine-tuning

Question 10

A developer wants to use a pre-trained model to identify objects in images. Which Google Cloud AI API should they use?

Accepted Answer

Vision AI. Vision AI provides pre-trained models for object detection, image classification, etc. Natural Language AI is for text, Speech-to-Text for audio, and Translation for text translation.

Answer

Speech-to-Text

Answer

Translation API

Answer

Natural Language AI

Question 11

A company wants to use Google DeepMind's advances in protein structure prediction to accelerate drug discovery. Which DeepMind achievement is most relevant to this goal?

Accepted Answer

AlphaFold. AlphaFold solves protein structure prediction, a key enabler for drug discovery. AlphaGo is for board games, AlphaCode for programming, and WaveNet for audio.

Answer

WaveNet

Answer

AlphaCode

Answer

AlphaGo

Question 12

An enterprise customer needs to ensure that all data sent to the Gemini API is not used by Google for model improvement and must support a HIPAA BAA. Which access tier should they use?

Accepted Answer

Vertex AI (enterprise tier). Vertex AI for enterprise offers data isolation, no use of customer data for training, and HIPAA BAA. Google AI Studio and Gemini API (developer) do not provide these guarantees.

Answer

Google AI Studio (free tier)

Answer

Gemini API via Google Workspace

Answer

Gemini API via API key (developer tier)

Question 13

A data scientist wants to use Google Cloud AI services to build a solution that transcribes customer support calls, analyzes sentiment, and translates transcripts into multiple languages. Which TWO services are needed?

Accepted Answer

Cloud Translation API. Speech-to-Text transcribes audio, Translation API translates text. Natural Language AI could be used for sentiment but is not required for translation. Document AI and Vision AI are irrelevant.

Answer

Vision AI

Answer

Natural Language AI

Answer

Document AI

Question 14

A company is comparing Google Cloud's AI offerings with AWS Bedrock and Azure OpenAI. They need to select a platform that provides: 1) native multimodal capabilities (image, video, text in one model), 2) integration with enterprise productivity tools, and 3) custom TPU hardware for training. Which THREE differentiators are unique to Google Cloud?

Accepted Answer

Integration with Google Workspace (Gmail, Docs, etc.). Gemini's native multimodality, Workspace integration, and TPU infrastructure are unique to Google Cloud. AWS and Azure do not offer the same combination.

Answer

Azure OpenAI Service with GPT-4

Answer

Amazon Bedrock with Titan models

Question 15

A financial services firm must deploy a conversational AI application using Gemini on Vertex AI. They require: 1) SOC2 compliance, 2) audit logging of model inputs/outputs, and 3) data isolation within their VPC. Which THREE configurations or features should they enable?

Accepted Answer

Enable VPC Service Controls to restrict data access. Vertex AI offers VPC Service Controls for data isolation, Cloud Audit Logs for logging, and SOC2 compliance is available. Google AI Studio does not provide these, and Data Loss Prevention API is for data masking, not a requirement.

Answer

Deploy the Data Loss Prevention API

Answer

Use Google AI Studio Prototyping