Last week, Signal, a messaging app that puts privacy first, went offline briefly. The cause was an outage at Amazon Web Services (AWS), which hosts Signal’s servers. Many users and critics questioned why Signal depends so heavily on a single cloud provider. CEO Meredith Whittaker explained that there aren’t many options available right now. Whittaker
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Cloud Computing
As AI tasks grow more complex and resource-intensive, many organizations are searching for better alternatives to conventional cloud providers. While giants like AWS and Azure still dominate, a new wave of decentralized compute platforms is emerging. These marketplaces connect companies needing GPU power with providers who have spare hardware, all through decentralized systems. They can
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Recently, Anthropic announced a huge deal with Google Cloud that’s capturing a lot of attention in the tech world. The company plans to deploy up to one million TPUs, which amounts to a multi-billion dollar investment. This move signals a big change in how large companies are building their AI infrastructure and what they prioritize
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Even though cloud providers like Amazon Web Services (AWS) are considered industry leaders, they can’t prevent all outages. This week, AWS experienced a major disruption that caused widespread problems. Websites went down, business systems froze, and productivity stopped for hours. If you rely on cloud services or work in IT, you probably felt the impact
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Early Monday morning, users relying on Amazon Web Services in the US-EAST-1 region faced a rough start. A DNS issue caused the DynamoDB API to become unreliable, which then affected many other AWS services and a wide range of customers. While the problem was isolated to a single API in one region, the ripple effects
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The cloud industry is shifting quickly, and a new term is catching everyone’s attention: neoclouds. These are cloud platforms built specifically for artificial intelligence (AI) and machine learning workloads. They focus on delivering raw power, lower costs, and faster deployment for AI tasks. This shift could challenge the dominance of the big three cloud providers:
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Oracle has launched a fresh data lakehouse that aims to give businesses more freedom when managing their data. This new platform, called Autonomous AI Lakehouse, is designed to work smoothly across different clouds and on-premises systems. It supports Apache Iceberg, a popular open table format, to help companies improve how they analyze data and share
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More companies are turning to specialized cloud solutions to handle the growing demands of artificial intelligence and compliance rules. These custom clouds are designed for specific tasks, industries, or applications rather than offering a one-size-fits-all setup. They give businesses the ability to tweak hardware, software, and tools to better suit their needs. The Rise of
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Amazon Web Services (AWS) has introduced a new AI platform called Amazon Quick Suite. This system is designed to help businesses manage their massive amounts of data more easily. It can do everything from deep research and answering questions to creating reports and automating tasks. The goal is to save time and make complex data
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Oracle’s Java Management Service (JMS), part of Oracle Cloud Infrastructure, just got a big upgrade to help businesses better manage their Java apps. The new features aim to make it easier to understand how Java applications are performing and to keep everything running smoothly. The biggest addition is called Analyze Applications. This tool lets developers
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