Chroma Vector Database: Retrieval for LLMs
Explore Chroma Vector Database's role in enhancing LLM retrieval capabilities with insights from industry experts Hammad Bashir and Liquan Pei.
Unpacking Three Types of Feature Stores - MLOps Podcast
Explore feature stores, vector stores, and embeddings in ML and LLMs. Learn about personalization in prompts, MLOps challenges, and innovations from Featureform's CEO Simba Khadder.
Managing Small Knowledge Graphs for Multi-agent Systems - MLOps Podcast #236
Explore knowledge graph management for multi-agent systems, focusing on structural grounding, selective improvement, and end-to-end reliability. Learn strategies to enhance RAG accuracy and repeatability in AI pipelines.
How Generative AI Powers the Next Generation of Mercari Marketplace
Discover how Mercari leverages GenAI to enhance its C2C marketplace, from streamlining item listings to improving search relevance and product recommendations through advanced ML engineering techniques.
Introduction to Retrieval Augmented Generation (RAG) - From Fundamentals to Implementation
Dive into RAG fundamentals and learn to implement AI-powered chatbots using vector databases, combining retrieval and generative models for enhanced information processing capabilities.
Navigating, Restructuring and Reshaping Learned Latent Spaces
Explore advanced techniques for manipulating learned latent spaces in machine learning, focusing on navigation, restructuring, and reshaping methods for improved model performance and efficiency.
Advanced Retrieval Augmented Generation (RAG) Techniques
Master advanced RAG implementation techniques, focusing on chunking strategies, embedding model selection, and metadata structuring for building more effective and business-valuable AI applications.
A Deep Dive into Vector Search Technology and Tools
Explore vector search technology through practical demonstrations of ClickHouse, OpenSearch, and PGVector, learning how AI models convert text to vectors for enhanced contextual search capabilities.
Building RAG Applications: Speaking with Unstructured Data Using LangChain - Part 2
Dive into building an end-to-end RAG application using Langchain, multiple LLMs, and vector stores to enable interactive conversations with unstructured data through a Streamlit interface.
Building End-to-End RAG Applications with Unstructured Data - Part 3: Docker Integration
Dive into containerization with Docker and Docker Compose while building a RAG application that processes unstructured data using LangChain, multiple LLMs, and vector stores through Streamlit.
Vector Databases: A New Search Paradigm - OCX 2024
Explore how vector databases revolutionize information search through multidimensional data representation, with hands-on examples using Milvus, Weaviate, and Neo4J for enhanced data analysis.
VulSim: Leveraging Similarity of Multi-Dimensional Neighbor Embeddings for Vulnerability Detection
Explore advanced vulnerability detection techniques using multi-dimensional neighbor embeddings and deep learning models to enhance software security through improved pattern recognition and data analysis.