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AI market evolution: Data and infrastructure transformation through AI

CIO

The majority (91%) of respondents agree that long-term IT infrastructure modernization is essential to support AI workloads, with 85% planning to increase investment in this area within the next 1-3 years. While early adopters lead, most enterprises understand the need for infrastructure modernization to support AI.

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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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Automate Amazon Bedrock batch inference: Building a scalable and efficient pipeline

AWS Machine Learning - AI

To address this consideration and enhance your use of batch inference, we’ve developed a scalable solution using AWS Lambda and Amazon DynamoDB. Conclusion In this post, we’ve introduced a scalable and efficient solution for automating batch inference jobs in Amazon Bedrock. This automatically deletes the deployed stack.

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IT resiliency: Running two different hypervisors

CIO

Many are reframing how to manage infrastructure, especially as demand for AI and cloud-native innovation escalates,” Carter said. While Boyd Gaming switched from VMware to Nutanix, others choose to run two hypervisors for resilience against threats and scalability, Carter explained.

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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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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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Color raises $167 million funding at $1.5 billion valuation to expand ‘last mile’ of US health infrastructure

TechCrunch

This brings the total raised by Color to $278 million, with its latest large round intended to help it build on a record year of growth in 2020 with even more expansion to help put in place key health infrastructure systems across the U.S. including those related to the “last mile” delivery of COVID-19 vaccines.

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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.