Google Cloud Digital Leader — All Questions

A developer wants to add image-label detection to an app without collecting training data or building a model. Which Google Cloud option is the fastest path?

• a.Train a custom model from scratch on Compute Engine
• b.Use Cloud Spanner to store and classify images
• c.Call the pre-trained Cloud Vision API✓
• d.Build a data warehouse in BigQuery first

The Cloud Vision API is a pre-trained service that detects objects, labels, text, and more from images with a simple API call, requiring no training data or model building. Training a custom model from scratch is slower and needs data and expertise. Spanner and BigQuery are data services, not vision models. Pre-trained APIs are the quickest route for common tasks.

How are artificial intelligence (AI) and machine learning (ML) best related?

• a.AI and ML are completely unrelated fields
• b.Machine learning is a subset of artificial intelligence✓
• c.Artificial intelligence is a subset of machine learning
• d.ML replaced AI as a newer, unrelated technology

AI is the broad field of building systems that perform tasks requiring human-like intelligence, and machine learning is a subset of AI in which systems learn patterns from data rather than being explicitly programmed. ML is not the larger category, nor is it unrelated to or a replacement for AI. Knowing this hierarchy clarifies where tools like Vertex AI fit.

A data science team wants a single unified platform to build, train, tune, and deploy custom machine learning models, as well as access foundation models. Which Google Cloud product is designed for this?

• a.Vertex AI✓
• b.Cloud SQL
• c.Cloud Run
• d.Pub/Sub

Vertex AI is Google Cloud's unified machine learning platform for building, training, tuning, and deploying custom models, and it also provides access to foundation models like Gemini. Cloud SQL is a database, Cloud Run runs containers, and Pub/Sub is messaging. Vertex AI is the end-to-end ML platform described here.

A global company needs to automatically translate user-generated reviews between dozens of languages in real time. Which pre-trained Google Cloud API is the best fit?

• a.Cloud Vision API
• b.Speech-to-Text API
• c.Natural Language API
• d.Cloud Translation API✓

The Cloud Translation API uses pre-trained models to translate text between many languages, making it ideal for translating reviews on the fly. The Vision API handles images, Speech-to-Text converts audio to text, and the Natural Language API analyzes sentiment and entities. For language-to-language text translation, the Translation API is correct.

An organization is adopting AI and wants to reduce unfair bias, protect privacy, and keep humans accountable for outcomes. Which concept describes these commitments?

• a.Serverless computing
• b.The shared responsibility model
• c.Responsible AI✓
• d.Infrastructure as a Service

Responsible AI refers to developing and using AI in ways that are fair, safe, privacy-preserving, transparent, and accountable, which matches reducing bias and keeping humans accountable. Serverless computing and IaaS are infrastructure concepts, and the shared responsibility model concerns security duties between provider and customer. Responsible AI is the governing principle for ethical AI use.

A team wants to use a Google multimodal foundation model that can understand and generate text, and also reason across images and other inputs, to power a generative AI assistant. Which model family fits?

• a.Gemini✓
• b.Cloud SQL
• c.Compute Engine
• d.Pub/Sub

Gemini is Google's family of multimodal foundation models capable of understanding and generating text while reasoning across images and other modalities, making it well suited for generative AI assistants. Cloud SQL, Compute Engine, and Pub/Sub are infrastructure and data services, not generative models. Gemini is the correct model family for generative, multimodal AI.