AI

Sátántango is considered a holy rite for hardcore cinephiles. It also helped me confront my dwindling attention span.

Want to know what our reviewers have actually tested and picked as the best TVs, headphones, and laptops? Ask ChatGPT, and it’ll give you the wrong answers.

Designers, makers, and others often use 3D printing to rapidly prototype a range of functional objects, from movie props to medical devices. Accurate print previews are essential so users know a fabricated object will perform as expected. But previews generated by most 3D-printing software focus on function rather than aesthetics. A printed object may end

Your AI agent worked in the demo, impressed stakeholders, handled test scenarios, and seemed ready for production. Then you deployed it, and the picture changed. Real users experienced wrong tool calls, inconsistent responses, and failure modes nobody anticipated during testing. The result is a gap between expected agent behavior and actual user experience in production.

Managing costs across multiple AWS accounts often requires finance teams to query data from several sources to get a complete view of spending and optimization opportunities. In this post, you learn how to build a FinOps agent using Amazon Bedrock AgentCore that helps your finance team manage AWS costs across multiple accounts. This conversational agent consolidates

Compliance audits require comprehensive evidence trails, often involving hundreds of screenshots across multiple systems. Your compliance teams likely spend hours manually navigating through GitHub repositories, AWS consoles, and internal applications, capturing screenshots at each step. This manual process is time-consuming, error-prone, and difficult to reproduce consistently across audit cycles. This post demonstrates how we automated

Quality assurance (QA) automation is critical for modern software delivery. It catches regressions before production, validates user journeys at scale, and enables confident feature releases. But traditional QA automation solutions are brittle and demand specialized programming knowledge, decelerating software delivery. Automation frameworks rely on implementation details including UI selectors, element identifiers, and structural references to

I’m excited to announce that AWS Security Agent on-demand penetration testing and AWS DevOps Agent are now generally available, representing a new class of AI capabilities we announced at re:Invent called frontier agents. These autonomous systems work independently to achieve goals, scale massively to tackle concurrent tasks, and run persistently for hours or days without

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.