filmov
tv
Understanding Retrieval Augmented Generation (RAG)
Показать описание
🔍 What is RAG?
RAG stands for Retrieval Augmented Generation, and it's a revolutionary technique used in the field of Natural Language Processing (NLP). It combines the power of information retrieval with language generation to enhance the accuracy and reliability of AI-generated text.
💡 Why is Hallucination a Problem?
Hallucination in LLMs occurs when these models generate plausible-sounding but entirely false information. It can mislead users and spread misinformation. RAG helps tackle this issue head-on.
🔒 How Does RAG Work?
We break down the core concepts of RAG, explaining how it leverages external knowledge sources, like databases and the internet, to fact-check and verify the information generated by LLMs. This retrieval step acts as a safety net, reducing the chances of hallucination.
🚀 Benefits of RAG
Discover how RAG not only enhances the trustworthiness of AI-generated content but also makes these systems more adaptable and useful across various domains, from answering questions to generating creative content.
🌐 Real-World Applications
Explore real-world applications of RAG, from improving chatbots and virtual assistants to aiding researchers in data synthesis and knowledge dissemination.
🤖 Future of NLP with RAG
We discuss the exciting prospects of RAG in the ever-evolving landscape of NLP and how it's paving the way for more reliable AI systems.
🧠 Audience Accessibility
This video is tailored for absolute beginners, with clear explanations and visuals to ensure you grasp the fundamentals of RAG without needing a technical background.
🔗 Video Tags
#RAG #RetrievalAugmentedGeneration #AI #NLP #HallucinationInLLMs #GPT3 #LanguageModels #KnowledgeAugmentation #AIResearch #FactCheckingAI #NaturalLanguageProcessing #MachineLearning #BeginnersGuide
Buy me a coffee:
Follow me on social media:
Hope you enjoy today's video. Please show your love and support by just liking and subscribing to the channel so we can grow a strong and powerful community. Activate the 🔔 beside the subscribe button to get the notification!📩 If you have any questions or requests feel free to leave them in the comments below.
Thank you for watching and see you in the next video!!
RAG stands for Retrieval Augmented Generation, and it's a revolutionary technique used in the field of Natural Language Processing (NLP). It combines the power of information retrieval with language generation to enhance the accuracy and reliability of AI-generated text.
💡 Why is Hallucination a Problem?
Hallucination in LLMs occurs when these models generate plausible-sounding but entirely false information. It can mislead users and spread misinformation. RAG helps tackle this issue head-on.
🔒 How Does RAG Work?
We break down the core concepts of RAG, explaining how it leverages external knowledge sources, like databases and the internet, to fact-check and verify the information generated by LLMs. This retrieval step acts as a safety net, reducing the chances of hallucination.
🚀 Benefits of RAG
Discover how RAG not only enhances the trustworthiness of AI-generated content but also makes these systems more adaptable and useful across various domains, from answering questions to generating creative content.
🌐 Real-World Applications
Explore real-world applications of RAG, from improving chatbots and virtual assistants to aiding researchers in data synthesis and knowledge dissemination.
🤖 Future of NLP with RAG
We discuss the exciting prospects of RAG in the ever-evolving landscape of NLP and how it's paving the way for more reliable AI systems.
🧠 Audience Accessibility
This video is tailored for absolute beginners, with clear explanations and visuals to ensure you grasp the fundamentals of RAG without needing a technical background.
🔗 Video Tags
#RAG #RetrievalAugmentedGeneration #AI #NLP #HallucinationInLLMs #GPT3 #LanguageModels #KnowledgeAugmentation #AIResearch #FactCheckingAI #NaturalLanguageProcessing #MachineLearning #BeginnersGuide
Buy me a coffee:
Follow me on social media:
Hope you enjoy today's video. Please show your love and support by just liking and subscribing to the channel so we can grow a strong and powerful community. Activate the 🔔 beside the subscribe button to get the notification!📩 If you have any questions or requests feel free to leave them in the comments below.
Thank you for watching and see you in the next video!!
0:06:36
What is Retrieval-Augmented Generation (RAG)?
0:05:49
Back to Basics: Understanding Retrieval Augmented Generation (RAG)
0:11:37
What is RAG? (Retrieval Augmented Generation)
0:08:03
RAG Explained
0:09:41
What is Retrieval Augmented Generation (RAG) - Augmenting LLMs with a memory
0:10:04
Understanding Retrieval Augmented Generation (RAG)
0:49:24
Retrieval Augmented Generation (RAG) Explained: Embedding, Sentence BERT, Vector Database (HNSW)
0:12:22
What is Retrieval-Augmented Generation (RAG)?
2:09:29
Generative AI in 2 hours | LLM Basics, RAGs, Prompt Engineering | Satyajit Pattnaik
0:03:49
AI Explained - AI LLM Retrieval-Augmented Generation (RAG)
0:14:31
Intro to RAG for AI (Retrieval Augmented Generation)
0:04:34
Retrieval Augmented Generation (RAG) | Embedding Model, Vector Database, LangChain, LLM
0:03:15
Understanding retrieval augmented generation (RAG) | Elastic Snackable Series
0:19:52
How to set up RAG - Retrieval Augmented Generation (demo)
0:03:15
RAG for LLMs explained in 3 minutes
0:14:08
A Helping Hand for LLMs (Retrieval Augmented Generation) - Computerphile
2:33:11
Learn RAG From Scratch – Python AI Tutorial from a LangChain Engineer
5:40:59
Local Retrieval Augmented Generation (RAG) from Scratch (step by step tutorial)
0:14:52
Retrieval Augmented Generation (RAG) with Genkit
0:03:01
Difference between Fine tuning and Retrieval Augmented Generation (RAG)
0:00:30
What is Retrieval Augmented Generation (RAG)?
0:27:54
L-7 RAG (Retrieval Augmented Generation)
0:02:35
What is Retrieval Augmented Generation (RAG)?
0:15:21
Prompt Engineering, RAG, and Fine-tuning: Benefits and When to Use
Комментарии