Azure AI Chatbot Demo

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Questions and Answers

What is the primary focus of the chatbot demo presented by Mega during the session?

  • Building a chatbot using a low-code/no-code approach in the Azure AI Foundry playground using Azure AI Search. (correct)
  • Implementing cybersecurity measures for cloud-based systems.
  • Developing mobile applications with advanced UI/UX designs.
  • Creating complex algorithms for data analysis.

Mega, the speaker, has worked in which of the following companies?

  • Intel, Cisco, HP, Dell
  • IBM, Oracle, SAP, VMware
  • Google, Amazon, Facebook, Netflix
  • Samsung, MakeMyTrip, Microsoft, Apple (correct)

Which type of search functionality is used in the chatbot demo?

  • Fuzzy search algorithm
  • Hybrid search (lexical + vector) (correct)
  • Simple keyword search
  • Full-text search only

What is the primary role of Azure AI Search in the chatbot architecture?

<p>To provide data chunking, AI enrichment, and hybrid search capabilities. (A)</p> Signup and view all the answers

What is the significance of converting user prompts into vectors in the chatbot application?

<p>To facilitate semantic search based on the meaning of the words, enhancing context understanding. (C)</p> Signup and view all the answers

Which of the following is a key benefit of using Azure AI Search, as highlighted in the session?

<p>It provides built-in keyword and vector search storage, simplifying the architecture. (C)</p> Signup and view all the answers

What is the recommended region to choose when creating a Resource Group in Azure for Open AI capabilities, based on the session?

<p>East US (D)</p> Signup and view all the answers

What type of files are stored in the container within the Azure storage account?

<p>Block blobs (PDFs in this case) (B)</p> Signup and view all the answers

What is the purpose of deploying models in the Azure AI Foundry portal?

<p>To deploy embedding and chat completion models such as test embedding (small) and GPT-4o. (B)</p> Signup and view all the answers

What is the main function of the chat completion model in the playground?

<p>To generate chat responses based on the data used to train the model. (A)</p> Signup and view all the answers

According to the session, what is one of the expectations of modern applications?

<p>They should be Gen AI-powered, enabling users to interact with data and systems. (B)</p> Signup and view all the answers

What is the role of text embedding models in building a generative AI application?

<p>To convert text data into vector embeddings for semantic understanding. (C)</p> Signup and view all the answers

Which of the following is a typical application of generative AI?

<p>Image synthesis (A)</p> Signup and view all the answers

Why are vectors important in the context of AI models and search?

<p>They help LLMs understand the meaning of tokens/words, enabling semantic search. (D)</p> Signup and view all the answers

What is the purpose of the indexing engine in Azure AI Search?

<p>To create vectors from the ingested data. (C)</p> Signup and view all the answers

What role does Azure Blob Storage play in the chatbot architecture described in the session?

<p>It stores the PDF documents that the chatbot interacts with. (B)</p> Signup and view all the answers

According to Mega, what does deil squad provide?

<p>Deil (Developer Interaction Layer) as a service and product (C)</p> Signup and view all the answers

What is the advantage of using low-code/no-code solutions in chatbot development, as highlighted in the session?

<p>It enables chatbot development without extensive coding. (C)</p> Signup and view all the answers

How does Azure AI Search handle data from different sources?

<p>It ingests content from various sources (databases, firewalls) and handles indexing, refreshing, and AI enrichment. (A)</p> Signup and view all the answers

For what purpose would you use Azure Open AI Studio (Azure AI Foundry)?

<p>To build Enterprise Generative AI applications. (D)</p> Signup and view all the answers

Flashcards

Generative AI

AI models that generate human-like responses, used in chatbots, content creation, and automation.

Azure AI Search

An Azure service that allows you to build vectors (embeddings) on top of data for semantic search.

Azure AI Foundry

An environment in Azure for building, testing, and deploying generative AI applications.

Text Embeddings

Turning text into numerical representations (vectors) to understand meaning.

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Vector Search

Looking for the documents that are most similar to the query based off of numerical representations.

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Hybrid Search

Combining keyword-based and vector-based search for better results.

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Azure Blob Storage

A type of storage optimized for storing large amounts of unstructured data, like PDFs.

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Data Chunking

Automatically splitting text that are too large into smaller segments prior to vectorization.

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Azure Resource Group

A container for managing related resources for an Azure solution.

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Multimodal Models

Models that can interpret and process various types of input data such as text, images, and audio.

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Low-Code/No-Code

A low-code/no-code method for creating applications with minimal coding, aiding in rapid development.

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RAG

A method in which responses include content external to the LLM.

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Study Notes

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