Personalizing Search Using Multimodal Latent Behavioral Embeddings
Explore personalized search using multimodal latent behavioral embeddings. Learn to integrate user behavior into modern search retrieval pipelines for RAG and end-user search, enhancing relevance and user experience.
Building Vector-Powered Products with User Embeddings
Explore vector embeddings for user modeling, learn vector ops, and discover applications in recommender systems and bot detection. Gain insights from real-world deployments.
Building RAG Systems with Mixed Numeric and Text Data - Workshop
Learn to build high-performing RAG systems by combining numeric and text data embeddings. Explore efficient retrieval techniques for LLMs and improve chatbot performance using an HR policy example.
Neuro-Symbolic AI and AllegroGraph 8.0: Revolutionizing Enterprise Knowledge Graphs
Explore AllegroGraph 8.0's revolutionary features in Enterprise Knowledge Graphs and Neuro-Symbolic AI. Learn how it integrates LLMs, Machine Learning, Symbolic AI, and Logic to enhance AI accuracy and reliability.
Navigating the Skies of Open AI - Perfecting Grounding for Large Language Models
Explore ChatGPT's impact on knowledge consumption, learn about LLM grounding and vector databases, and understand OpenAI's technology for efficient data retrieval and scalability.
The Future of Data Engineering in a Post-AI World
Explore AI's impact on data engineering, including ETL automation, data warehouses, and emerging technologies. Learn to leverage AI for significant business impact in the evolving data landscape.
Using Vector Databases with LLMs - Part One
Explore vector databases for LLMs, enhancing audio and visual data processing, recognition, and search capabilities.
Using Vector Databases with LLMs - Part Two
Explore advanced vector database applications for LLMs, enhancing audio/visual recognition and search capabilities.
GenAI for Observability in the Serverless World
Harness GenAI to enhance serverless observability, leveraging vector databases and ML for improved data ingestion, log analysis, and problem resolution.
Unlocking Innovative Generative AI Use Cases with Text and Multimodal Embeddings
Explore innovative generative AI applications using text and multimodal embeddings, focusing on semantic search, recommender systems, and content classification.
Building Differentiated Generative AI Applications on Google Cloud
Explore building Generative AI apps on Google Cloud using Vertex AI's models, embeddings APIs, and vector databases. Learn to create enterprise-grade conversational AI and search experiences.
From RAG to Autonomous Apps with Weaviate and Gemini on Google Kubernetes Engine
Explore advanced RAG techniques using Weaviate and Gemini on GKE. Learn to deploy, ingest data, and enhance responses for building autonomous AI applications.
Getting Started with OpenSearch and OpenSearch Dashboards
Learn to set up and use OpenSearch for powerful search and analytics. Master cluster configuration, dashboard creation, and best practices for effective data visualization and management.
Spring AI: Integrating AI into Enterprise Applications with Java
Explore Spring AI's seamless integration of AI into enterprise Java applications. Learn key concepts, create effective prompts, and implement features like embeddings, RAG, and semantic search.
Democratizing AI - Vector Databases and LLM Applications
Explore vector databases, LLM app building, and AI democratization with Yujian Tang. Learn about Milvus, production use cases, data challenges, and the future of AI technologies.
Using Vector Databases: Practical Advice for Production - LLMs in Prod Conference
Explore vector databases for LLMs in production. Learn design patterns, context retrieval, feature injection, and common pitfalls. Gain practical insights for efficient deployment and management.
Embeddings and Retrieval for LLMs: Techniques and Challenges
Explore embedding-based retrieval for AI apps, including key limitations and mitigation techniques. Learn about Chroma, an open-source embedding database for LLM applications.
Model Blind Spot Discovery for Better Models and Ingesting Chaos - Mini Summit #2
Discover techniques for model blind spot detection and handling unstructured data at scale. Learn to build resilient AI models through data diagnosis, enhancement, and automated evaluation systems.
RAG Has Been Oversimplified - Exploring Complexities in Retrieval Augmented Generation
Explore the complexities of Retrieval Augmented Generation (RAG) beyond its oversimplified portrayal. Gain insights into practical challenges and nuanced considerations for developers working with RAG systems.
Charting LLMOps Odyssey - Navigating Large Language Model Operations
Navigate the iterative development of LLM applications, addressing unique challenges in LLMOps design. Learn strategies for overcoming obstacles and adapting to the evolving landscape of large language model operations.
RecSys at Spotify - Building and Evaluating Large-Scale Recommender Systems
Explore Spotify's large-scale recommender systems, foundational embeddings for transfer learning, evaluation methods, and MLOps challenges with Senior ML Engineer Sanket Gupta.