Search: “retrieval”

At Google Cloud Next ‘26, we announced that more than 50 Google-managed Model Context Protocol (MCP) servers are generally available or in preview, with more on the way. Why it matters: To move beyond

At Google Cloud, every day is Developer Day, but none so much as day 2 of Google Cloud Next, when we hold the developer keynote. This year’s topic? An in-depth look at Gemini Enterprise Agent Platform

Written by: JP Glab, Tufail Ahmed, Josh Kelley, Muhammad Umair Introduction Google Threat Intelligence Group (GTIG) identified a multistage intrusion campaign by a newly tracked threat group, UNC6692,

Succeeding in the agentic era requires a transformation in your data strategy: moving from human-scale to agent-first workloads, evolving from reactive intelligence to proactive action, and shifting f

pgvector is an open-source PostgreSQL extension that enables efficient storage and similarity search of vector embeddings within a relational database. It allows developers to build vector search capa

This guide covers how to train and fine-tune multimodal embedding and reranker models using the Sentence Transformers library, enabling systems to work with both text and image data simultaneously. It

AI agents struggle to effectively process and extract information from complex enterprise documents due to limitations in context windows, reasoning capabilities, and handling of unstructured data for

Databricks outlines an architecture for implementing real-time product search using its Lakehouse platform, combining vector databases, embedding models, and Delta Lake to enable low-latency semantic

Understanding the relationships within your data is crucial for uncovering hidden insights and building intelligent applications. However, managing operational (OLTP) and analytical (OLAP) graph workl

DigitalOcean's Gradient AI Platform enables developers to build intelligent documentation agents that can automatically generate, maintain, and query technical documentation using large language model

Vercel's open-source Knowledge Agent Template enables developers to build AI knowledge agents using a filesystem and bash tools (grep, find, cat) instead of the traditional vector database, embeddi...

Agentic workflows are already used for initiating action. To be successful, agents typically need to combine multiple steps and execute business logic reflective of real-life decisions. But, as develo

Google Research introduced two AI agents to streamline academic workflows: **PaperVizAgent**, a visualizer agent for drawing academic figures, and **ScholarPeer**, a reviewer agent that automatica...

Mem0 documents a self-hosted agent-memory REST API with a pgvector vector store and Neo4j knowledge graph; local models are optional.

DoorDash and AWS describe a live Bedrock-backed voice agent for Dasher support, reporting hundreds of thousands of calls daily.