Get AI summaries of any video or article — Sign up free

Retrieval Augmented Generation — Topic Summaries

AI-powered summaries of 10 videos about Retrieval Augmented Generation.

10 summaries

No matches found.

Complete RAG Crash Course With Langchain In 2 Hours

Krish Naik · 3 min read

Retrieval-Augmented Generation (RAG) is presented as a practical way to make large language models answer with up-to-date, domain-specific...

Retrieval Augmented GenerationRAG PipelineChunking Strategies

5-Getting Started With Agentic RAG With Detailed Implementation Using LangGraph

Krish Naik · 2 min read

Agentic RAG shifts retrieval from a fixed pipeline to a decision made on the fly: an autonomous agent chooses when to fetch context, what to fetch,...

Agentic RAGLangGraph WorkflowConditional Routing

LangChain Agents: Build Personal Assistants For Your Data (Q&A with Harrison Chase and Mayo Oshin)

Chat with data · 3 min read

LangChain agents are built around a simple but powerful idea: use a language model as a reasoning engine, then let it reliably choose and run...

LangChain AgentsTool UseAgent Memory

Google's RAG Experiment - NotebookLM

Sam Witteveen · 2 min read

NotebookLM is Google’s early, product-shaped experiment in retrieval-augmented generation (RAG): upload your own documents, ask questions, and get...

NotebookLMRetrieval Augmented GenerationGemini 1.5 Pro

Cohere's Command-R a Strong New Model for RAG

Sam Witteveen · 3 min read

Cohere’s Command-R arrives as a purpose-built model for retrieval-augmented generation (RAG) and tool/function calling, not as a bid to replace top...

Command-RRetrieval Augmented GenerationTool Use

LLM In-Context Learning Masterclass feat My (r/reddit) AI Agent

All About AI · 3 min read

A Reddit AI agent can be made to deliver on-topic, “in-style” answers by stuffing a carefully curated “brain” into the model’s prompt—combining a...

In-Context LearningPrompt EngineeringRetrieval Augmented Generation

State of GPT

West Coast Machine Learning · 3 min read

Large language models are built through a pipeline that starts with internet-scale next-token pre-training and then progressively adds human...

GPT Training PipelinePre-Training vs Fine-TuningRLHF Reward Modeling

How to Integrate RAG - Retrieval Augmented Generation into a LLM? (Practical Demo)

AI Researcher · 3 min read

Retrieval-Augmented Generation (RAG) is presented as a practical way to make a language model answer questions using external, user-provided sources...

Retrieval Augmented GenerationVector EmbeddingsCosine Similarity

Build Smarter AI Apps: Memory, Tools, Retrieval & Structured Output with Python, Pydantic & Ollama

Venelin Valkov · 3 min read

AI apps become meaningfully more useful when they’re given four upgrades beyond plain text prompting: memory, structured outputs, tool use, and...

MemoryStructured OutputTool Use

Building a Text to SQL Chatbot with RAG, LangChain, FastAPI And Streamlit | Tech Edge AI

Tech Edge AI-ML · 2 min read

Text-to-SQL chatbots become dependable when they stop guessing and start grounding every generated query in the real database schema. The core fix is...

Text to SQLRetrieval Augmented GenerationRAG Loop