KHkarthik hubliincustomer-identity-access-management.hashnode.dev·Mar 4, 2025 · 7 min readFrom Words to Vectors: Understanding the Magic of Text EmbeddingTransformers are the backbone of large language models (LLMs) and have revolutionized natural language processing by enabling models to handle vast amounts of text efficiently. Unlike traditional neural networks, transformers use a self-attention mec...00
KHkarthik hubliinrag-101.hashnode.dev·Mar 4, 2025 · 4 min readRAG: Putting the pieces together (Part - 3)RAG has significant advantage over traditional generative models that rely solely on pre-trained data. RAG systems incorporate a retrieval mechanism that dynamically fetches relevant information to improve the accuracy and reliability of responses. E...00
KHkarthik hubliinrag-101.hashnode.dev·Jan 20, 2025 · 3 min readRAG: Building blocks (Part - 1)Introduction LLM/Inference LLMs are the "brain" of RAG systems, responsible for interpreting input queries, retrieving relevant knowledge, and generating coherent, context-aware responses. Key roles of LLM in a RA system involve Natural Language Unde...00
KHkarthik hubliinrag-101.hashnode.dev·Jan 20, 2025 · 3 min readRAG: The big picture (Part - 2)To understand RAG, we must take a few steps back and start with understanding what is AI. There are many definitions for what constitutes an AI. The one broadly accepted is that any system which matches or exceeds average human capability in a comple...00
KHkarthik hubliintext-embedding.hashnode.dev·Nov 21, 2024 · 7 min readFrom Words to Vectors: Understanding the Magic of Text EmbeddingTransformers are the backbone of large language models (LLMs) and have revolutionized natural language processing by enabling models to handle vast amounts of text efficiently. Unlike traditional neural networks, transformers use a self-attention mec...00