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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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From edge to cloud: The critical role of hardware in AI applications

CIO

All this has a tremendous impact on the digital value chain and the semiconductor hardware market that cannot be overlooked. Hardware innovations become imperative to sustain this revolution. So what does it take on the hardware side? For us, the AI hardware needs are in the continuum of what we do every day.

Hardware 245
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ASUS unveils powerful, cost-effective AI servers based on modular design

CIO

That means hardware designed from the ground up for maximum performance, data center integration, AI development support, optimal cooling, and easy vertical and horizontal scaling. That architecture lets ASUS servers exploit the latest NVIDIA advances in GPUs, CPUs, NVME storage, and PCIe Gen5 interfaces.

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Prioritizing AI? Don’t shortchange IT fundamentals

CIO

Fundamentals like security, cost control, identity management, container sprawl, data management, and hardware refreshes remain key strategic areas for CIOs to deal with. But rapid hardware advances may mean CIOs need to budget for much shorter hardware refresh cycles in future to stay up to date.

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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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Why Purpose-Built Infrastructure is the Best Option for Scaling AI Model Development

CIO

Developers find that a training job now takes many hours or even days, and in the case of some language models, it could take many weeks. Paikeday says it occurs if they choose to build such infrastructure themselves or repurpose existing IT infrastructure instead of going to a purpose-built architecture designed specifically for AI.

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Avoid generative AI malaise to innovate and build business value

CIO

Capturing the “as-is” state of your environment, you’ll develop topology diagrams and document information on your technical systems. Next craft a “to-be” blueprint of what you need to support your strategic vision, including targeted capabilities, future IT architecture, and talent required to facilitate the work. Cleanse your data.