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Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, we’re looking at the shift from “AI demos” to real systems: agents that need reliable execution, enterprises building durable AI infrastructure, and architectures that survive production constraints. We also cover: A 1-hour practical walkthrough of modern AI engineering, from prompting and RAG to agents, evaluation, and deployment, plus a production lesson on why agent retries quietly break real systems. Why recursive multi-agent […]

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When AMD announced version 4 of its FidelityFX Super Resolution (FSR) graphics upscaling technology early last year, it came with strings attached: The improved hardware-backed image quality would be available only on Radeon RX 9000-series GPUs based on the RDNA4 architecture, not on any older Radeon GPUs. To date, AMD has released only a handful of 90-series graphics cards, including the RX 9070 XT, the RX 9070, the 8GB and 16GB versions of the RX 9060 XT, and […]

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A federal judge reportedly said she will not rubber-stamp a settlement between Elon Musk and the Securities and Exchange Commission, saying the deal raises red flags and needs scrutiny over whether Musk is getting special treatment from the Trump administration. As we reported last week, the Trump administration agreed to let Musk pay a $1.5 million fine to settle a lawsuit that originally sought at least $150 million. In 2022, before buying Twitter outright, Musk purchased a 9 […]

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Improving bot accuracy in Amazon Lex starts with handling how customers communicate naturally. Your customers express the same request in dozens of different ways, combine multiple pieces of information in one sentence, and often speak ambiguously. The Assisted NLU (natural language understanding) feature in Amazon Lex helps you improve bot accuracy by handling these natural language variations. Traditional natural language understanding systems struggle with this variability, which can lead customers to repeat themselves or abandon conversations. The challenge: […]

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This post was co-authored with Neevash Ramdial, Technical Marketing leader at Stream Building production-grade voice agents that feel natural and responsive is a complex engineering challenge. You must orchestrate speech-to-speech models, manage low-latency audio streaming, and handle connection lifecycle. You also need to deliver consistent experiences across web, mobile, and desktop applications. In this post, you learn how to combine Stream’s Vision Agents open-source framework with Amazon Bedrock and Amazon Nova 2 Sonic to build real-time voice agents […]

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Amazon Quick is an AI-powered unified intelligence service that brings together an organization’s data, structured data and unstructured enterprise content like documents, emails, and knowledge bases into a single service where anyone can explore, analyze, and take action. With over 40 application integrations, Quick bridges the last-mile gap between insights and action so users can understand their data and act on it directly. Amazon Quick Sight, the business intelligence (BI) capability of Amazon Quick, is a unified BI […]

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AI agents with unrestricted web access pose significant security risks. Without Chrome enterprise policies to control browser behavior, an agent might navigate to unauthorized domains, store credentials in the browser’s password manager, or download files outside approved workflows. Organizations with internal services that use a private certificate authority (CA) face an additional barrier. Every HTTPS connection to those services fails with certificate validation errors. Amazon Bedrock AgentCore Browser now supports Chrome enterprise policies and custom root CA certificates […]

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