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Cloud AI Means Someone Else Has Your Data, MINISFORUM Fixes That

Running a serious AI model at home usually means renting someone else’s cloud server and hoping your data stays private along the way. MINISFORUM built its newest pairing to remove that trade-off entirely. The AI Agent NAS N5 MAX-P495 and AI Mini Workstation MS-S1 MAX-P495 combine for up to 131 TOPS of AI compute performance, 192GB of memory at 8533 MT/s, and up to 160GB of graphics memory, enough headroom to keep the heavy lifting on a desk instead of in a data center.

The N5 MAX-P495 takes the shape of a compact black cube, but what it holds inside matters more than how it looks sitting on a shelf. It combines powerful AI computing with up to 200TB of local storage, enabling users to store, manage, and process large volumes of data within a single AI platform. That capacity turns a spare corner of an office into a private archive large enough to hold years of project files, footage, or research without ever touching a third-party server.

Designer: MINISFORUM

Storage alone doesn’t make an AI system useful, so MINISFORUM built the N5 to run the AI itself. From RAG knowledge bases and AI models to embeddings, databases, and AI agents such as OpenClaw and Hermes, N5 MAX-P495 keeps data and AI workloads local, enabling continuous and private AI operations. A small business could lean on that setup to run its own customer-support agent without routing conversations through an outside company’s servers.

That local-first approach extends to how the N5 fits into a larger setup. Designed to work alongside AI computing devices, N5 MAX-P495 serves as a centralized backend for data, models, knowledge, and long-running AI workloads, bringing storage and computing together at the edge. It’s less a standalone gadget and more a quiet engine room, built to keep working in the background while something faster handles the parts people actually interact with.

That faster half of the pairing is the MS-S1 MAX-P495, a compact tower wrapped in a ventilated, diamond-textured front panel that looks more like a piece of desk sculpture than a workstation. It delivers powerful local AI computing for demanding model inference, AI development, and computationally intensive workloads, built for intensive local AI tasks, engineering, and workflows in an ultra-compact footprint. Developers get workstation-class muscle without giving up desk space to a full tower case.

Speed matters just as much as raw power for certain jobs, and MINISFORUM designed the MS-S1 with that in mind. Designed for low-latency AI workloads, MS-S1 MAX-P495 enables responsive local inference for AI agents, computer vision, generative AI, and other real-time applications. A security camera system or a live creative tool built on generative AI benefits directly from that kind of immediate response instead of waiting on a round trip to the cloud.

Connectivity rounds out the workstation’s role in a larger setup. With extensive connectivity and expansion capabilities, MS-S1 MAX-P495 serves as a powerful AI compute frontend, supporting models, applications, and connected devices across flexible edge AI environments. That flexibility means the same box can sit at the center of a home lab or plug into a small studio’s existing hardware without forcing a rebuild.

Paired together, the two devices split the work the way a good team would. The MS-S1 MAX-P495 and N5 MAX-P495 form a complete edge AI computing system, delivering high-performance AI compute at the frontend while integrating compute, massive storage, data, and AI knowledge at the backend, providing a powerful foundation for real-time inference, persistent AI workloads, and scalable local AI applications. It’s a compact answer to a question more households and small teams are starting to ask: whether AI still needs to live somewhere else at all.

The post Cloud AI Means Someone Else Has Your Data, MINISFORUM Fixes That first appeared on Yanko Design.

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NVIDIA confirms RTX Spark configurations and availability: First devices expected to begin shipping as soon as next month, with two N1X configs on offer

NVIDIA has confirmed new details and availability info about its upcoming RTX Spark SoC for Windows 11 devices. At IFA 2026, the company announced that it expects the first RTX Spark laptops to begin shipping as soon as next month, sometime in October depending on the OEM. Additionally, two new devices are joining the launch lineup; the Lenovo Yoga 9n laptop and Acer SFF desktop PC.

Alongside availability news, NVIDIA has also confirmed configuration details for the upcoming RTX Spark chips. There will be two different configurations of the RTX Spark N1X, with configurable RAM and storage based on what OEMs wish to offer. The high-end RTX Spark will be targeted at desktops and laptops, with support for up to 128GB unified memory, 20 CPU cores, and 6144 Blackwell RTX cores.

There will also be a less powerful RTX Spark configuration exclusively for laptops, which can only be configured with 24GB or 32GB unified memory, a 5120-Core Blackwell RTX GPU, and an 18-core CPU. While still a high-end chip, this should allow RTX Spark to ship in laptops that cost closer to $2,000, significantly lower priced than the high-end SoC.

Category

Specification 1

Specification 2

GPU Cores

6144-core Blackwell RTX GPU

5120-core Blackwell RTX GPU

CPU Cores

20-core Grace CPU

18-core Grace CPU

Memory

24-128 GB Unified Memory

24-32 GB Unified Memory

Form Factors

Laptops and Compact Desktops

Laptops

NVIDIA is touting RTX Spark as the best SoC for AI development on Windows. It supports NVIDIAs full AI stack, as well as the Windows Agent Framework and 120B parameter agents. It also supports hardware accelerated 4:2:2 video for video editing professionals.

It's also good for gaming, with expected 100 frames per second in many games at 1440p with RT and DLSS. In fact, NVIDIA has announced that many popular and mainstream gaming developers have committed to supporting RTX Spark with native games and frameworks so that there are no compatibility issues with the RTX Spark's Arm architecture.

While the first RTX Spark devices are expected to begin shipping in October, it's not yet clear which OEMs will be first out the gate. All major Windows hardware makers, including Dell, Lenovo, HP, ASUS, and Microsoft have all announced RTX Spark devices that are expected to ship by the end of this year. Devices like the Surface Laptop Ultra have not yet been given a release date, though Microsoft typically does aim to ship new Surface PCs in October.

We'll be sure to keep you updated on all the RTX Spark device availability as more information is revealed by OEMs. In the meantime, are you considering an RTX Spark device as your next Windows PC? Let us know in the comments!

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NVIDIA reinforces itself as an AI-first company nowadays with an almost $13 billion acquisition of Hugging Face

If you're not a keen follower of the AI space, then the name Hugging Face may not mean anything to you. But the company has just been acquired by NVIDIA, which continues to reinforce its new identity as an AI company.

Announced today by NVIDIA CEO Jensen Huang, Hugging Face will be joining the company in an acquisition priced at just under $13 billion.

Hugging Face is an open platform that has been likened to GitHub, except for local, open AI models that anyone can use. NVIDIA's plans are to keep Hugging Face the same as it is today but to scale. Because if you're not scaling AI these days, what are you even doing?

"Hugging Face will remain an open platform for the entire AI ecosystem. Developers will choose the models they want, the frameworks they want, the clouds and inference service providers they want and the computing platforms they want. NVIDIA compute will not be required to build on or deploy through Hugging Face.

Hugging Face will continue to support open source and open weight models from across the ecosystem, from every model builder. It will continue to support multi-cloud and multi-accelerator development and deployment, so builders can use the hardware and infrastructure that best fit their work."

Keeping personal opinions about AI aside, I'm certainly more in favor of real people being able to use AI models without having to rely on massive, un-evironmentally friendly data centers from the likes of Microsoft and OpenAI.

AI is very much here to stay, whether we choose to embrace it or not. But I'm definitely on the side of being able to use it however you want to use it and without feeding all your data to companies that don't necessarily deserve it.

NVIDIA is very much AI-first these days, though. Gone are the days we'd all look at its shiny new GPUs, and our only thoughts would be about gaming. It does make you ponder what the future holds for gamers, though.

I've got an RTX 5090, for example, and it's still overkill for gaming. But with 32GB of VRAM and a ton of compute horsepower, it's pretty damn good for local AI use. But is this where future products will be aligned first? Everything's getting more expensive, and AI is definitely to blame for a good chunk of it.

Alas, here we are. If you use Hugging Face currently, it doesn't sound like anything's going to change. But if you're a gaming customer of the company, as I am, I am starting to wonder how important we're going to be in the future.

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