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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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10 most in-demand enterprise IT skills

CIO

Oracle Oracle offers a wide range of enterprise software, hardware, and tools designed to support enterprise IT, with a focus on database management. Java Java is a programming language used for core object-oriented programming (OOP) most often for developing scalable and platform-independent applications.

UI/UX 203
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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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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.

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Nvidia points to the future of AI hardware

CIO

Blackwell will also allow enterprises with very deep pockets to set up AI factories, made up of integrated compute resources, storage, networking, workstations, software, and other pieces. But Nvidia’s many announcements during the conference didn’t address a handful of ongoing challenges on the hardware side of AI.

Hardware 148
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Pliops lands $100M for chips that accelerate analytics in data centers

TechCrunch

Part of the problem is that data-intensive workloads require substantial resources, and that adding the necessary compute and storage infrastructure is often expensive. As a result, organizations are looking for solutions that free CPUs from computationally intensive storage tasks.” Marvell has its Octeon technology.