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ExternalAI
AWS Machine Learning Blog

Automate replenishment with MMF, Databricks Genie, and Amazon Quick

Foundation models made catalog-wide demand forecasting easy; the hard part is now acting on the forecast. This post builds a closed detect-decide-act loop on Databricks and Amazon Quick that reconciles demand surges against live supplier availability and places replenishment orders unattended, escalating to a human only when no supplier can cover a surge.

Advanced (300)Amazon Quick SuiteTechnical How-to
AWS Machine Learning BlogRead original
ExternalSoftware Engineering
DZone

Building a 2KB Histogram with Sub-0.2% Percentile Error

The Problem: Tracking Request Latency Without Slowing Things Down For a cloud data warehouse, performance is not just about average query time. What often matters more is tail latency, predictability, and the ability to pinpoint where things go wrong. In a cloud-native data warehouse like Databend, a single request may pass through multiple stages: SQL planning, distributed execution, remote storage, Raft logging, and state machine apply. Tail latency in any one of these stages can affect the qu

DZoneRead original
External
The Hacker News

⚡ Weekly Recap: Rogue AI Agents, WeChat Worm, PaperCut Attacks, AI Espionage, and Rootkits

AI keeps showing up in the wrong places. Attackers are using it to speed up exploits, test defenses, and automate more of the job. Some models are also crossing lines on their own. That is not a great combination. The rest of the week is more familiar: old bugs still working, fresh exploit chains, exposed systems, weak defaults, and simple paths that should have been harder to abuse. A few of

The Hacker NewsRead original

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