AWS Introduces Native Vector Search for DynamoDB
Amazon DynamoDB recently introduced native vector search, allowing developers to store embeddings alongside application data and run approximate nea…
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Presentation: From Models to Agents: Building Context-Aware Consumer AI at Scale at DoorDash
Sudeep Das shares how DoorDash shifts from legacy one-shot predictions to an agentic recommendation platform. He discusses leveraging language-nativ…
Pinecone Introduces Nexus Engine for Compiling Business Context into Structured Data for AI Agents
Now generally available, Pinecone Nexus is a "knowledge engine" for AI agents that transforms enterprise data into a structured layer agents can que…
Version Controlled SQL Database Dolt Releases 2.0 with Automatic Storage Cleanup and Compression
DoltHub has recently released Dolt 2.0, a major update to the open source version-controlled SQL database. The latest major version adds automatic s…
How HubSpot Scaled Semantic Search to 20 Billion Vectors
SaaS software vendor HubSpot has described how its semantic search platform grew from a proof of concept into an internal service that now manages m…
Inside Target’s LLM-Based System for Semantic Matching in Marketing Forecast Pipelines
Target built a generative AI system to improve marketing campaign forecasting by retrieving and ranking similar historical campaigns. Using embeddin…
Article: Why Vector Search Alone Isn't Enough: Hybrid Retrieval for RAG
In this article, author Aaditya Chauhan discusses the limitations of RAG pipelines based purely on vector search and how an internal omni-search app…