AB-410 Exam Questions

The Prebuilt Receipt model is specifically trained to find and extract key-value pairs from financial receipts.

Language Detection identifies the source language, allowing the bot to use the correct localized response logic.

In-context learning lets the model adjust to new tasks or styles by using the instructions and examples included in the current prompt.

Chunking breaks large text files into smaller pieces so they fit within the model‘s context window.

Dynamic Chaining lets the system create a custom “chain“ of actions or agents at runtime based on the user‘s specific request.

The context window is the model‘s active memory; when it is exceeded, the model forgets earlier parts of the chat.

Hierarchical orchestration uses a lead agent to manage task delegation and review work performed by subordinate agents.

The Evaluation tool in AI Studio measures Groundedness to determine whether the AI is making up information.

The On-premises Data Gateway enables Microsoft Cloud services to securely access data that is stored in local, private networks.

Document Intelligence uses advanced deep learning for complex OCR tasks, including distorted images or images with high noise.

Category Classification is the standard model for labeling and routing text-based content into predefined business categories.

Prompt Shields are the main defense mechanism in Content Safety for blocking inputs designed to bypass model safety filters.

Agentic AI extends beyond conversation by using reasoning to work with tools, navigate apps, and complete workflows independently.

System topics are foundational logic blocks included in every bot to handle common conversational scenarios.

Few-shot prompting uses a small set of examples to “guide“ the model toward the correct output format or reasoning logic.

Content filtering helps the AI follow safety standards by blocking unsafe inputs and outputs.

Prompt compression removes unnecessary information from the context while keeping the semantic meaning for the LLM.

Document Intelligence is specifically optimized for high-accuracy OCR in difficult or unstructured visual conditions.

Plugins expand Copilot capabilities by enabling it to interact with external data and perform transactional actions.

Increasing Temperature adds more randomness to token selection, which leads to more creative or varied outputs.

Frequency Penalty directly reduces verbatim token repetition so the output sounds more natural.

The Canvas is the visual drag-and-drop environment used to orchestrate an agent‘s conversational logic.

The Speech service supports live audio-to-text and audio-to-audio translation, known as Speech Translation, with low latency.

Setting Temperature to 0 makes the model deterministic, so the same input always produces the same output.

Content Safety for Images identifies harmful visual content across multiple categories, including Hate, Self-harm, Sexual, and Violence.

Phi-3 is an efficient SLM that is designed to deliver strong reasoning capability in a smaller, faster, and more cost-effective model package.

The Evaluation tab in Azure AI Studio provides metrics such as groundedness and relevance for assessing model quality against datasets.

The Planner is the intelligence layer that identifies the sequence of actions needed to complete a high-level user goal.

Azure Cost Management supports tagging and reporting so AI spending can be tracked across different business units.

RBAC ensures the agent can access only the specific tables and rows it is authorized to see.

Vector search finds semantic matches by measuring the distance between high-dimensional numerical representations of text.

Adding overlap helps preserve entities or concepts that are split across chunk boundaries by keeping them in both chunks, which improves retrieval quality.

The Planner is the intelligence layer that identifies the sequence of actions needed to complete a high-level goal.

The Prebuilt ID Document model is specifically trained to recognize and extract data from identity documents such as licenses and passports.

Category Classification automatically tags or labels text-based content into predefined business categories.

Few-shot prompting directs the model’s reasoning and formatting by showing examples of the desired behavior.

Max Tokens defines a firm limit on generated tokens, which controls both response length and cost.

The Alpha parameter in hybrid search controls the balance between keyword (BM25) scores and vector (Semantic) search scores.

Prompt Shields are designed specifically to detect and block malicious content concealed in user inputs or retrieved data.

Azure AI Studio’s Playground is a web-based environment used to quickly experiment with LLM configurations.

The Search Index is the specialized database that enables fast retrieval of relevant context used to ground the LLM.

Azure APIM enables you to publish, secure, and analyze the APIs consumed by your intelligent applications.

Fine-tuning is used when a model must learn specific vocabulary, style, or deep domain knowledge that is not available in the base training.

Zero-shot prompting depends on the model’s pre-trained knowledge to complete a request without task-specific examples.

This system trigger supports global pre-processing, such as checking for profanity or logging interactions.

The system message is the foundational instruction that tells the AI what it is and defines the boundaries it must follow.

Inclusiveness helps ensure technology can be used by everyone, regardless of physical or cognitive abilities.

Azure AI Studio provides evaluation tools that calculate metrics such as “Groundedness“ to identify factual inconsistencies.

The On-premises Data Gateway enables Microsoft Cloud services to securely access data located in local networks.

Azure AI Studio is the unified platform for finding, comparing, and deploying many types of foundation models.

Metadata filtering applies hard filters, such as Date or Category, before semantic search to improve accuracy.

Computer Use is an agentic feature that lets the bot interact with non-API-based web interfaces and desktop apps in a human-like way.

Brand Detection in Azure AI Video Indexer recognizes thousands of well-known logos and brands within video frames.

Fairness is about ensuring AI systems treat all groups of people equitably and do not reinforce social bias.

Purview provides the data governance framework that helps ensure AI models use compliant and authorized data sources.

Plugins expand Copilot‘s capabilities so it can “do“ tasks, such as updating a CRM record or checking stock in an ERP system.

The Vector Search Engine uses mathematical embeddings to locate document chunks that match the “meaning“ of the user‘s query.

Grounding limits the model‘s knowledge base to a specific trusted set of documents so the response is accurate and relevant.

Purview‘s AI Hub is the centralized place for discovering risks, governing data, and monitoring AI usage at scale.

MCP is an open standard that enables smooth integration between AI models and local or remote data and tools.