Retrieval Augmented Generation (RAG) Explained: Embedding, Sentence BERT, Vector Database (HNSW)

Retrieval Augmented Generation (RAG) Explained: Embedding, Sentence BERT, Vector Database (HNSW)
Share:

Download MP3


Similar Tracks

BERT explained: Training, Inference, BERT vs GPT/LLamA, Fine tuning, [CLS] token Umar Jamil
OpenAI Embeddings and Vector Databases Crash Course Adrian Twarog
Mistral / Mixtral Explained: Sliding Window Attention, Sparse Mixture of Experts, Rolling Buffer Umar Jamil
What is RAG? (Retrieval Augmented Generation) Don Woodlock
Legion Retreat 2024 - Low-Latency, High-Performance LLM Serving and Fine-tuning - Zhihao Jia Legion Programming System
Stanford CS25: V3 I Retrieval Augmented Language Models Stanford Online
Transformers (how LLMs work) explained visually | DL5 3Blue1Brown
Mamba and S4 Explained: Architecture, Parallel Scan, Kernel Fusion, Recurrent, Convolution, Math Umar Jamil
Vector Database Search - Hierarchical Navigable Small Worlds (HNSW) Explained DataMListic
Vector Search RAG Tutorial – Combine Your Data with LLMs with Advanced Search freeCodeCamp.org
GraphRAG: The Marriage of Knowledge Graphs and RAG: Emil Eifrem AI Engineer
Frank Sifei Luan Dissertation Talk 12.6.2024 Frank Luan
RAG vs. Fine Tuning IBM Technology
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks, with Patrick Lewis, Facebook AI Natural Language Processing presentations
Segment Anything - Model explanation with code Umar Jamil
LLaMA explained: KV-Cache, Rotary Positional Embedding, RMS Norm, Grouped Query Attention, SwiGLU Umar Jamil
How to Improve LLMs with RAG (Overview + Python Code) Shaw Talebi
Visualizing transformers and attention | Talk for TNG Big Tech Day '24 Grant Sanderson
Andrew Ng Explores The Rise Of AI Agents And Agentic Reasoning | BUILD 2024 Keynote Snowflake Inc.
Local Retrieval Augmented Generation (RAG) from Scratch (step by step tutorial) Daniel Bourke