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5 things CIOs must understand about AI infrastructure

CIO

But getting from potential to profitability does not come without risks, such as assuming that your established processes for deploying mainstream enterprise IT infrastructure will work in the new era of complex AI superclusters. A solid technology infrastructure has always been essential.

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Want AI? Here’s how to get your data and infrastructure AI-ready

CIO

CIOs are responsible for much more than IT infrastructure; they must drive the adoption of innovative technology and partner closely with their data scientists and engineers to make AI a reality–all while keeping costs down and being cyber-resilient. Artificial intelligence (AI) is reshaping our world.

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Choosing a cloud infrastructure provider: A beginner’s guide

TechCrunch

Deploying cloud infrastructure also involves analyzing tools and software solutions, like application monitoring and activity logging, leading many developers to suffer from analysis paralysis. These companies are worried about the future of their cloud infrastructure in terms of security, scalability and maintainability.

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You can’t grow trust on a rocky infrastructure

CIO

But not all organizations that store and process sensitive customer data are fully aware that a chink in infrastructure can break our digital trust. A trusted, distributed infrastructure must be flexible and scalable, allowing for agility without compromising on security. It is not just about building a robust infrastructure.

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MLOps 101: The Foundation for Your AI Strategy

Machine Learning Operations (MLOps) allows organizations to alleviate many of the issues on the path to AI with ROI by providing a technological backbone for managing the machine learning lifecycle through automation and scalability. What are the core elements of an MLOps infrastructure? Why do AI-driven organizations need it?

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Infrastructure as Code: The Evolution of Cloud Infrastructure Management

Dzone - DevOps

Businesses are increasingly depending on cloud-based services to improve efficiency, increase scalability, and streamline operations in the quickly developing digital age. The requirement for efficient resource management has multiplied as the cloud has become a crucial part of contemporary IT infrastructures.

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Software infrastructure 2.0: a wishlist

Erik Bernhardsson

Software infrastructure (by which I include everything ending with *aaS, or anything remotely similar to it) is an exciting field, in particular because (despite what the neo-luddites may say) it keeps getting better every year! Anyway, I feel like this applies to like 90% of software infrastructure products. Ephemeral resources.

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The Ultimate Embedded Analytics Guide

Ensure the solution is built on scalable, cost effective infrastructure. However, in order to successfully expose analytics to customers and partners, companies are faced with three main challenges: Manage complex data (big and disparate datasets) quickly. Share data and insights securely.