JSJanmejai Singhincyd3er.hashnode.dev·Jul 19 · 10 min readWhere RAG Fails: Understanding the Limitations of Retrieval-Augmented GenerationIf you've built anything with large language models in the last two years, you've almost certainly run into RAG — Retrieval-Augmented Generation. It's become the default answer to "how do I make my LL00
JAJahangir Abbas Munnaninjahangirabbas.hashnode.dev·Jul 19 · 5 min readWhere RAG Fails: Understand the LimitationsWhen I first started learning about Large Language Models (LLMs), one term kept coming up everywhere: RAG (Retrieval-Augmented Generation). At first, I thought it was a perfect solution. Many videos a00
SShayintoddlerstech.hashnode.dev·Jul 17 · 5 min readWhere RAG Fails: Understand the Limitationsbefore discussing the limitations i would like to discuss what RAG is ? What is RAG ? RAG - Retrieval Augmented Generation This is a process that allows us to give LLM the specific knowledge to answer00
YYashingen-ai-with-yash.hashnode.dev·Jul 15 · 9 min readWhere RAG Fails: Understand the LimitationsNothing is perfect, not even RAG. As every developer knows, "user input is evil," and even a well-designed RAG system can fail. Before we understand how RAG works, let's see where it can go wrong. Can11K
PMPrajwal Minglitch-guy0.hashnode.dev·Jul 15 · 6 min readUnderstanding RAG: A Simple Guide for BeginnersIntroduction: The Problem with LLMs Large Language Models (LLMs) excel at generating text, answering questions, and even writing code. However, they have a critical limitation: they only know what the00
KMKrish Mahyavanshiinkrizh.hashnode.dev·Jul 11 · 7 min readWhere RAG Fails: Understanding the Limitations of Retrieval-Augmented GenerationLarge Language Models (LLMs) are incredibly powerful. Before reading further: If you're new to AI, I recommend first understanding what Large Language Models (LLMs) are and what actually happens afte02MR
OTOmkar Tripathiinllmjourney.hashnode.dev·Jul 11 · 7 min readHow Do LLMs Know Things Beyond Their Training? An Introduction to RAGWe use Large Language Models (LLMs) every single day. But have you ever wondered how they seem to know everything? In my previous blog, we discussed how LLMs are trained on massive datasets. However, 00
VSVraj Soniinblog.sonivraj.com·Jul 10 · 5 min readUnderstanding RAG : Why it Exists, How It Works, and Where It Falls Short Large Language Model (LLM) are impressive but they have fundamental limitations like they only know on what they are trained on. Ask a LLM about what happened after its training cut-off , or about com00
VKVibhu Khatiinlinuxhunting.hashnode.dev·Jul 9 · 14 min readRAG(Retrieval-Augmented Generation): The Good, the Bad, and the HallucinationsUnderstanding RAG: How It Improves LLM Answers—and Where It Can Still Fail Large Language Models (LLMs) such as ChatGPT can answer questions, write code, summarize documents, and generate content in s00
DPDeep Patelindeep1511.hashnode.dev·Jul 4 · 3 min readApplication Developer vs ML Developer: The Power Plant and The ElectricianWhen I started my #GenAI cohort with Hitesh Sir and Piyush Sir, one line completely reframed how I understood AI roles: AI = Input (Engine) → Output But instead of thinking in terms of "engine," I w00
