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9 IT skills where expertise pays the most

CIO

Cloud computing Average salary: $124,796 Expertise premium: $15,051 (11%) Cloud computing has been a top priority for businesses in recent years, with organizations moving storage and other IT operations to cloud data storage platforms such as AWS.

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Gartner projects major IT spending increases for 2025

CIO

Device spending, which will be more than double the size of data center spending, will largely be driven by replacements for the laptops, mobile phones, tablets and other hardware purchased during the work-from-home, study-from-home, entertain-at-home era of 2020 and 2021, Lovelock says. growth in device spending.

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EnCharge AI emerges from stealth with $21.7M to develop AI accelerator hardware

TechCrunch

EnCharge AI , a company building hardware to accelerate AI processing at the edge , today emerged from stealth with $21.7 Speaking to TechCrunch via email, co-founder and CEO Naveen Verma said that the proceeds will be put toward hardware and software development as well as supporting new customer engagements.

Hardware 216
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AI chip startup Axelera lands $27M in capital to commercialize its hardware

TechCrunch

Unlike conventional chips, theirs was destined for devices at the edge, particularly those running AI workloads, because Del Maffeo and the rest of the team perceived that most offline, at-the-edge computing hardware was inefficient and expensive. The edge AI hardware market is projected to grow from 920 million units in 2021 to 2.08

Hardware 240
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Microsoft acquires Fungible, a maker of data processing units, to bolster Azure

TechCrunch

In December, reports suggested that Microsoft had acquired Fungible, a startup fabricating a type of data center hardware known as a data processing unit (DPU), for around $190 million. ” A DPU is a dedicated piece of hardware designed to handle certain data processing tasks, including security and network routing for data traffic. .”

Azure 282
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Navigating the future of national tech independence with sovereign AI

CIO

Core challenges for sovereign AI Resource constraints Developing and maintaining sovereign AI systems requires significant investments in infrastructure, including hardware (e.g., Many countries face challenges in acquiring or developing the necessary resources, particularly hardware and energy to support AI capabilities.

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Accelerating generative AI requires the right storage

CIO

In generative AI, data is the fuel, storage is the fuel tank and compute is the engine. All this data means that organizations adopting generative AI face a potential, last-mile bottleneck, and that is storage. Novel approaches to storage are needed because generative AI’s requirements are vastly different.