AI

DevOps used to be predictable: same input, same output, binary success, static dependencies, concrete metrics. You could control what you could predict, measure what was concrete, and secure what followed known patterns. Then agentic AI arrived, and everything changed. Agents operate non-deterministically; they don’t follow fixed patterns. Ask the same question twice, get different answers. […]

Weather forecasting has gotten a big boost from machine learning. How that translates into what users see can vary.

This post is cowritten with David Kim, and Premjit Singh from Ring. Scaling self-service support globally presents challenges beyond translation. In this post, we show you how Ring, Amazon’s home security subsidiary, built a production-ready, multi-locale Retrieval-Augmented Generation (RAG)-based support chatbot using Amazon Bedrock Knowledge Bases. By eliminating per-Region infrastructure deployments, Ring reduced the cost

This post is cowritten by  Sebastian Angersbach, Philip Trempler, and Weiran Zhang from Volkswagen Group. Volkswagen Group stands as one of the world’s largest automotive manufacturers, delivering 6.6 million vehicles in the first nine months of 2025. The Group comprises ten distinct brands from five European countries: Volkswagen, Volkswagen Commercial Vehicles, ŠKODA, SEAT, CUPRA, Audi,

The effective monitoring and characterization of solar flares demands sophisticated analysis of X-ray emissions across multiple energy spectrums. Machine learning-based anomaly detection serves as a powerful tool for identifying significant patterns that could indicate notable solar activity. Through the identification of distinct radiation signatures, key solar event characteristics can be detected, analyzed, and comprehensively understood.

Deliver hyperpersonalized viewer experiences with an agentic AI movie assistant using Amazon Nova Sonic 2.0Recommendation systems are the backbone of modern media streaming services, shaping how users discover content. Traditional machine learning (ML) systems use collaborative or content-based filtering to predict content preferences. However, they often miss context-dependent needs, such as time of the day,

In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful new properties. Today, atomic-scale defects are carefully introduced during the manufacturing process of products like steel, semiconductors, and solar cells to help improve strength, control electrical conductivity, optimize performance, and more. But even as defects have

Documents show the tax agency is testing a Palantir tool to surface “highest-value” audit and investigation targets from a maze of legacy systems.

A policy change announced by NeurIPS, the world’s leading AI research conference, drew widespread backlash from Chinese researchers this week and then was quickly reversed.