venturebeat
Google PM open-sources Always On Memory Agent, ditching vector databases for LLM-driven persistent memory

Google senior AI product manager Shubham Saboo has turned one of the thorniest problems in agent design into an open-source engineering exercise: persistent memory.This week, he published an open-source “Always On Memory Agent” on the official Google Cloud Platform Github page under a permissive MIT License, allowing for commercial usage.It was built with Google's Agent Development Kit, or ADK introduced last Spring in 2025, and Gemini 3.1 Flash-Lite, a low-cost model Google introduced on March 3, 2026 as its fastest and most cost-efficient Gemini 3 series model. The project serves as a practical reference implementation for something many AI teams want but few have productionized cleanly: an agent system that can ingest information continuously, consolidate it in the background, [...]

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venturebeat
AWS claims 90% vector cost savings with S3 Vectors GA, calls it 'complementary' - analysts split on what it means for vector databases

Vector databases emerged as a must-have technology foundation at the beginning of the modern gen AI era. What has changed over the last year, however, is that vectors, the numerical representations o [...]

Match Score: 339.32

venturebeat
From shiny object to sober reality: The vector database story, two years later

When I first wrote “Vector databases: Shiny object syndrome and the case of a missing unicorn” in March 2024, the industry was awash in hype. Vector databases were positioned as the next big thing [...]

Match Score: 220.26

venturebeat
Most enterprises can't stop stage-three AI agent threats, VentureBeat survey finds

A rogue AI agent at Meta passed every identity check and still exposed sensitive data to unauthorized employees in March. Two weeks later, Mercor, a $10 billion AI startup, confirmed a supply-chain br [...]

Match Score: 195.12

venturebeat
Under the hood of AI agents: A technical guide to the next frontier of gen AI

Agents are the trendiest topic in AI today — and with good reason. Taking gen AI out of the protected sandbox of the chat interface and allowing it to act directly on the world represents a leap for [...]

Match Score: 159.33

venturebeat
Moving past speculation: How deterministic CPUs deliver predictable AI performance

For more than three decades, modern CPUs have relied on speculative execution to keep pipelines full. When it emerged in the 1990s, speculation was hailed as a breakthrough — just as pipelining and [...]

Match Score: 134.91

venturebeat
Karpathy shares 'LLM Knowledge Base' architecture that bypasses RAG with an evolving markdown library maintained by AI

AI vibe coders have yet another reason to thank Andrej Karpathy, the coiner of the term. The former Director of AI at Tesla and co-founder of OpenAI, now running his own independent AI project, recent [...]

Match Score: 131.04

venturebeat
Oracle converges the AI data stack to give enterprise agents a single version of truth

Enterprise data teams moving agentic AI into production are hitting a consistent failure point at the data tier. Agents built across a vector store, a relational database, a graph store and a lakehous [...]

Match Score: 129.66

venturebeat
Agents don't replace vector search - they make it harder to get right

What's the role of vector databases in the agentic AI world? That's a question that organizations have been coming to terms with in recent months.<br /> <br /> The narrative had [...]

Match Score: 123.27

venturebeat
Google's Opal just quietly showed enterprise teams the new blueprint for building AI agents

For the past year, the enterprise AI community has been locked in a debate about how much freedom to give AI agents. Too little, and you get expensive workflow automation that barely justifies the &qu [...]

Match Score: 120.53