Information Retrieval and Relevance: Vector Embeddings for Semantic Search
Explore vector embeddings for semantic search, learning techniques to create meaningful representations and apply them in information retrieval systems. Gain insights from an experienced technologist.
Exploring Long Context Language Models - MLOps Reading Group August 2024
Explore the potential of Long-Context Language Models to replace traditional methods like retrieval, RAG, and SQL. Dive into recent research and engage in critical discussions about LCLMs' capabilities and limitations.
Neo4J Knowledge Graph: Topic Extraction with Langchain and Phi3 - Part 1
Explore topic extraction for knowledge graphs using Neo4J, Langchain, and Microsoft Phi3. Learn to enrich movie databases with themes from TMDB.org overviews.
Live Coding a Quick and Easy Semantic Search with Qdrant from Scratch - Rust Implementation
Build a simple semantic search using Qdrant's Rust API in a live coding session. Learn implementation techniques and enjoy Rust-related humor along the way.
Embeddings vs Fine-Tuning - Part 1: Understanding and Implementing Embeddings
Explore embedding techniques for language models, including creation, implementation, and performance evaluation. Learn key concepts like semantic search, cosine similarity, and data preparation for optimal results.
A Fun and Absurd Introduction to Vector Databases
Explore vector databases for AI applications and natural language search. Learn to transform data into vectors, query effectively, and discover diverse use cases through engaging demonstrations.
Optimizing Query Performance with Pinecone's Rerank API and Fleak
Explore reranking, Pinecone's Embed and Rerank APIs, and see a live demo using Fleak to enhance query results and improve search performance.
The Magic of Multilingual Search with Pinecone Serverless and Inference
Explore multilingual search using Pinecone Serverless and Inference. Learn about embedding models, vector search basics, and practical applications through a language learning demo and expert insights.
Building a Scalable AI Chatbot with Wikipedia Data - Semantic Search and RAG
Learn to create an AI chatbot using Wikipedia video game data, implementing semantic search and RAG with SingleStore, optimizing with vector indexes, and integrating GPT models for an interactive experience.
Build a Semantic Search App Using Next.js and SingleStoreDB
Learn to create a semantic search app with Next.js and SingleStoreDB, focusing on vector embeddings and efficient data retrieval for enhanced search functionality.
Practical LLM Fine-Tuning for Semantic Search
Explore fine-tuning LLMs for semantic search in specialized domains. Learn data requirements, training techniques, and practical insights to enhance search capabilities using open-source tools.
Mastering Retrieval for LLMs - BM25, Fine-tuned Embeddings, and Re-Rankers
Enhance LLM retrieval with advanced techniques: BM25, fine-tuned embeddings, and re-rankers. Learn document chunking, semantic search, and performance optimization for improved AI-powered information retrieval.
Improving Search Results with Vector Search in Azure Cognitive Search
Discover how to enhance search relevance using semantic and vector search in Azure Cognitive Search, with live expert guidance and interactive Q&A.
Lightning Talks on Search Relevance and AI - Haystack US 2024
Explore cutting-edge search and AI topics through lightning talks from Haystack US 2024. Gain insights on information retrieval, LLMs, vector search, semantic search, and more from industry experts.
Building AI Applications with Transformers
Learn to leverage transformers for AI applications like auto-completion, semantic search, and document AI using open-source tools and models. Explore embeddings, Generative AI, and emerging trends in multimodal and large language models.
Weaviate: An Architectural Deep Dive
Explore Weaviate's architecture, delving into its vector database design, scalability features, and innovative approaches to data storage and retrieval in this comprehensive seminar.
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.
End-to-End Chatbot Web App Development with Azure AI and PromptFlow
Master the process of building and deploying a custom chatbot using Azure AI services, from initial setup to web integration, with practical guidance on PromptFlow, data indexing, and deployment steps.
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.
Building AI Agents in Ruby - From Foundations to Implementation
Discover how to build AI agents using Ruby, exploring RAG, vector embeddings, semantic search, and prompt engineering while creating a practical agent implementation in minutes.
Exploring New Features in Wolfram Language 14.1
Discover the latest features in Wolfram Language 14.1, including unified apps, vector databases, LLM integration, symbolic arrays, biomolecule visualization, and enhanced computational capabilities across various domains.