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Navigating the cloud maze: A 5-phase approach to optimizing cloud strategies

CIO

In todays fast-paced digital landscape, the cloud has emerged as a cornerstone of modern business infrastructure, offering unparalleled scalability, agility, and cost-efficiency. As organizations increasingly migrate to the cloud, however, CIOs face the daunting challenge of navigating a complex and rapidly evolving cloud ecosystem.

Cloud 147
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Agentic AI design: An architectural case study

CIO

An agent is part of an AI system designed to act autonomously, making decisions and taking action without direct human intervention or interaction. With all this talk, you would think it is easy to define what qualifies as agentic AI, but it isn’t always straightforward. Let’s start with the basics: What is an agent?

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Why GreenOps will succeed where FinOps is failing

CIO

This surge is driven by the rapid expansion of cloud computing and artificial intelligence, both of which are reshaping industries and enabling unprecedented scalability and innovation. On average, financial services clients weve worked with on cloud migration have had cloud bills 2-3 times the original expectations.

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Overcoming the 6 barriers to IT modernization

CIO

For instance, Capital One successfully transitioned from mainframe systems to a cloud-first strategy by gradually migrating critical applications to Amazon Web Services (AWS). It adopted a microservices architecture to decouple legacy components, allowing for incremental updates without disrupting the entire system.

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How ML System Design helps us to make better ML products

Xebia

Table of Contents What is Machine Learning System Design? Design Process Clarify requirements Frame problem as an ML task Identify data sources and their availability Model development Serve predictions Observability Iterate on your design What is Machine Learning System Design?

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Extend large language models powered by Amazon SageMaker AI using Model Context Protocol

AWS Machine Learning - AI

We will deep dive into the MCP architecture later in this post. Using a client-server architecture (as illustrated in the following screenshot), MCP helps developers expose their data through lightweight MCP servers while building AI applications as MCP clients that connect to these servers.

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Nvidia debuts new products for robotics developers, including Jetson Orin Nano

TechCrunch

Isaac Sim, Nvidia’s robotics simulation platform, will soon be available in the cloud, the company said. And Nvidia’s Jetson lineup of system-on-modules is expanding with Jetson Orin Nano, a system designed for low-powered robots. Any device will be able to set up, manage and review the results of simulations.”