🚀 Generative AI Interview Questions with Answers (Part 2)
6️⃣ What is Fine-Tuning in Generative AI?
👉 Fine-tuning is the process of taking a pre-trained AI model and training it further on a specific dataset to improve its performance for a particular task or domain.
📌 Pre-trained Model → Domain-Specific Data → Fine-Tuned Model
Examples:
🔹 Customer Support
🔹 Medical Text Processing
🔹 Legal Documents
🔹 Code Generation
💡 Fine-tuning is different from training a model completely from scratch.
---
7️⃣ What is RAG (Retrieval-Augmented Generation)?
👉 RAG combines information retrieval with Generative AI. Before generating an answer, the system retrieves relevant information from an external knowledge source and provides it to the model.
📌 Basic flow:
User Query → Retrieve Documents → Add Context → LLM → Answer
Benefits:
🔹 Works with private data
🔹 Uses updated external information
🔹 Useful for document-based chatbots
🔹 Can improve factual grounding
---
8️⃣ What is a Vector Database?
👉 A Vector Database stores numerical vector representations (embeddings) and enables efficient similarity searches.
It is commonly used in:
🔹 RAG Applications
🔹 Semantic Search
🔹 Recommendation Systems
🔹 Document Retrieval
🔹 AI Chatbots
📌 Text → Embedding → Vector Database → Similar Documents
💡 Vector search finds information based on semantic similarity, not just exact keyword matches.
---
9️⃣ What is an AI Agent?
👉 An AI Agent is a system that can reason about a goal, use tools, and take actions to complete tasks.
Example:
AI agents can potentially use:
🔹 APIs
🔹 Databases
🔹 Web Search
🔹 Code Execution
🔹 External Tools
---
🔟 What is Multimodal AI?
👉 Multimodal AI can process or generate multiple types of data, such as text, images, audio, and video.
Example:
📷 Image + 📝 Text → AI → 💬 Answer
Applications include:
🔹 Image Understanding
🔹 Voice Assistants
🔹 Document Analysis
🔹 Video Understanding
🔹 AI Content Creation
💡 Multimodal AI allows systems to work with information beyond text alone.
---
💬 Save this for your Generative AI interview preparation!
🔥 Part 3 will cover 5 questions on AI Models, LLM Parameters, Context Window, Temperature & Top-P.
#GenerativeAI #GenAI #AI #LLM #RAG #AIAgents #VectorDatabase #MultimodalAI #AIInterview #InterviewQuestions
6️⃣ What is Fine-Tuning in Generative AI?
👉 Fine-tuning is the process of taking a pre-trained AI model and training it further on a specific dataset to improve its performance for a particular task or domain.
📌 Pre-trained Model → Domain-Specific Data → Fine-Tuned Model
Examples:
🔹 Customer Support
🔹 Medical Text Processing
🔹 Legal Documents
🔹 Code Generation
💡 Fine-tuning is different from training a model completely from scratch.
---
7️⃣ What is RAG (Retrieval-Augmented Generation)?
👉 RAG combines information retrieval with Generative AI. Before generating an answer, the system retrieves relevant information from an external knowledge source and provides it to the model.
📌 Basic flow:
User Query → Retrieve Documents → Add Context → LLM → Answer
Benefits:
🔹 Works with private data
🔹 Uses updated external information
🔹 Useful for document-based chatbots
🔹 Can improve factual grounding
---
8️⃣ What is a Vector Database?
👉 A Vector Database stores numerical vector representations (embeddings) and enables efficient similarity searches.
It is commonly used in:
🔹 RAG Applications
🔹 Semantic Search
🔹 Recommendation Systems
🔹 Document Retrieval
🔹 AI Chatbots
📌 Text → Embedding → Vector Database → Similar Documents
💡 Vector search finds information based on semantic similarity, not just exact keyword matches.
---
9️⃣ What is an AI Agent?
👉 An AI Agent is a system that can reason about a goal, use tools, and take actions to complete tasks.
Example:
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User Goal
↓
AI Agent
↓
Reasoning
↓
Tool / API
↓
Action
↓
Result
AI agents can potentially use:
🔹 APIs
🔹 Databases
🔹 Web Search
🔹 Code Execution
🔹 External Tools
---
🔟 What is Multimodal AI?
👉 Multimodal AI can process or generate multiple types of data, such as text, images, audio, and video.
Example:
📷 Image + 📝 Text → AI → 💬 Answer
Applications include:
🔹 Image Understanding
🔹 Voice Assistants
🔹 Document Analysis
🔹 Video Understanding
🔹 AI Content Creation
💡 Multimodal AI allows systems to work with information beyond text alone.
---
💬 Save this for your Generative AI interview preparation!
🔥 Part 3 will cover 5 questions on AI Models, LLM Parameters, Context Window, Temperature & Top-P.
#GenerativeAI #GenAI #AI #LLM #RAG #AIAgents #VectorDatabase #MultimodalAI #AIInterview #InterviewQuestions
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What is Vector Database? How It Works with AI and RAG
What is Vector Database, Artificial Intelligence applications are becoming more powerful because they can understand text, documents, images, and
What is Vector Database? How It Works with AI and RAG
Vector Databases are becoming an important part of modern AI applications. They help AI systems store, search, and retrieve information based on meaning rather than only matching exact keywords.
In this tutorial, you will learn:
- What is a Vector Database?
- What are Vector Embeddings?
- How does a Vector Database work?
- What is Semantic Search?
- How does Similarity Search work?
- What is RAG (Retrieval-Augmented Generation)?
- How does Vector Database work with RAG?
- Complete RAG workflow
- Vector Database vs Traditional Database
- Popular Vector Database Technologies
- Real-world applications of Vector Databases
- Advantages and challenges of Vector Databases
This tutorial is useful for students and developers who want to understand Artificial Intelligence, Generative AI, Large Language Models, RAG, Vector Embeddings, and modern AI applications.
Read Full Article:
https://updategadh.com/what-is-vector-database/
Join Our Telegram Channel:
@ProjectWithSourceCodes
#VectorDatabase #RAG #AI #ArtificialIntelligence #GenerativeAI #VectorEmbeddings #SemanticSearch #LLM #RAGTutorial #AITutorial #MachineLearning #VectorSearch #AIDatabase #AIProjects #GenerativeAI #Programming #UPDATEGADH
Vector Databases are becoming an important part of modern AI applications. They help AI systems store, search, and retrieve information based on meaning rather than only matching exact keywords.
In this tutorial, you will learn:
- What is a Vector Database?
- What are Vector Embeddings?
- How does a Vector Database work?
- What is Semantic Search?
- How does Similarity Search work?
- What is RAG (Retrieval-Augmented Generation)?
- How does Vector Database work with RAG?
- Complete RAG workflow
- Vector Database vs Traditional Database
- Popular Vector Database Technologies
- Real-world applications of Vector Databases
- Advantages and challenges of Vector Databases
This tutorial is useful for students and developers who want to understand Artificial Intelligence, Generative AI, Large Language Models, RAG, Vector Embeddings, and modern AI applications.
Read Full Article:
https://updategadh.com/what-is-vector-database/
Join Our Telegram Channel:
@ProjectWithSourceCodes
#VectorDatabase #RAG #AI #ArtificialIntelligence #GenerativeAI #VectorEmbeddings #SemanticSearch #LLM #RAGTutorial #AITutorial #MachineLearning #VectorSearch #AIDatabase #AIProjects #GenerativeAI #Programming #UPDATEGADH