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GIGABYTE Brings Supercomputer Power to Your Desktop with AI TOP ATOM

GIGABYTE launches AI TOP ATOM on October 15th—a compact personal AI supercomputer powered by NVIDIA Grace Blackwell GB10. Delivers 1 petaFLOP performance for on-premises AI development, supporting models up to 200B parameters on your desktop.

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Last Updated on October 15, 2025 by Daily News Staff

Global Launch Set for October 15th as Tech Giant Democratizes AI Development

GIGABYTE AI TOP ATOM personal AI supercomputer featuring NVIDIA Grace Blackwell GB10 Superchip in compact desktop chassis
GIGABYTE Announces its Personal AI Supercomputer AI TOP ATOM Will be Available Globally on October 15

GIGABYTE is making a bold move to put enterprise-level AI computing power directly into the hands of developers, researchers, and students. The company’s latest innovation, AI TOP ATOM, launches globally on October 15th, promising to transform how we think about on-premises AI development.

Desktop Supercomputing Becomes Reality

What makes AI TOP ATOM remarkable isn’t just its specs—though those are impressive—it’s the promise of bringing supercomputer performance into a compact form factor that fits on your desk. Powered by NVIDIA’s Grace Blackwell GB10 Superchip, this personal AI supercomputer delivers up to 1 petaFLOP of FP4 AI performance. To put that in perspective, we’re talking about the kind of computational muscle that can handle large-scale models with up to 200 billion parameters right in your office.

The system comes equipped with 128GB of unified system memory and supports up to 4TB SSD storage, giving users the resources they need for serious AI workloads without the traditional infrastructure headaches.

Scale When You Need It

Here’s where things get interesting for power users: GIGABYTE designed AI TOP ATOM with scalability in mind. Need to tackle even larger models? Connect two units using the built-in NVIDIA ConnectX-7 NIC, and you can handle models up to 405 billion parameters. It’s like having a modular supercomputer that grows with your ambitions.

Software That Actually Makes Sense

Hardware is only half the story. AI TOP ATOM ships with NVIDIA’s complete AI software stack preinstalled—the full suite of tools, frameworks, and libraries designed specifically for generative AI workloads. But GIGABYTE didn’t stop there. They’ve integrated their exclusive AI TOP Utility, which provides an intuitive interface for the tasks that matter most: model fine-tuning, inference, and deployment across large language models (LLMs), large multimodal models (LMMs), and modern machine learning applications.

This approach addresses one of the biggest pain points in AI development—getting everything configured and working together. With AI TOP ATOM, you’re ready to start prototyping and developing from day one.

Who’s This For?

GIGABYTE is positioning AI TOP ATOM as a solution for anyone serious about AI development, from individual developers and academic researchers to students and educational institutions. The compact chassis means it works in environments where traditional server infrastructure simply isn’t practical—dorm rooms, small offices, research labs with limited space.

The “personal AI supercomputer” concept represents a significant shift in accessibility. What once required cloud computing budgets or dedicated data center space can now happen on-premises, giving developers more control over their data, faster iteration cycles, and potentially lower long-term costs.

The Bigger Picture

As AI development continues to accelerate across industries, tools like AI TOP ATOM signal an important trend: the democratization of high-performance AI computing. When powerful AI development tools become more accessible, innovation happens in unexpected places—and that’s exactly what GIGABYTE seems to be betting on.

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AI TOP ATOM launches globally on October 15th. For complete specifications, pricing, and availability in your region, visit the official GIGABYTE website.


Source: GIGABYTE.com

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Tech

When ‘Head in the Clouds’ Means Staying Ahead

Head in the Clouds: Cloud is no longer just storage—it’s the intelligent core of modern business. Explore how “cognitive cloud” blends AI and cloud infrastructure to enable real-time, self-optimizing operations, improve customer experiences, and accelerate enterprise modernization.

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Last Updated on February 7, 2026 by Daily News Staff

Head in the Clouds: Cloud is no longer just storage—it’s the intelligent core of modern business. Explore how “cognitive cloud” blends AI and cloud infrastructure to enable real-time, self-optimizing operations, improve customer experiences, and accelerate enterprise modernization.

When ‘Head in the Clouds’ Means Staying Ahead

(Family Features) You approve a mortgage in minutes, your medical claim is processed without a phone call and an order that left the warehouse this morning lands at your door by dinner. These moments define the rhythm of an economy powered by intelligent cloud infrastructure. Once seen as remote storage, the cloud has become the operational core where data, AI models and autonomous systems converge to make business faster, safer and more human. In this new reality, the smartest companies aren’t looking up to the cloud; they’re operating within it. Public cloud spending is projected to reach $723 billion in 2025, according to Gartner research,  reflecting a 21% increase year over year. At the same time, 90% of organizations are expected to adopt hybrid cloud by 2027. As cloud becomes the universal infrastructure for enterprise operations, the systems being built today aren’t just hosted in the cloud, they’re learning from it and adapting to it. Any cloud strategy that doesn’t account for AI workloads as native risks falling behind, holding the business back from delivering the experiences consumers rely on every day. After more than a decade of experimentation, most enterprises are still only partway up the curve. Based on Cognizant’s experience, roughly 1 in 5 enterprise workloads has moved to the cloud, while many of the most critical, including core banking, health care claims and enterprise resource planning, remain tied to legacy systems. These older environments were never designed for the scale or intelligence the modern economy demands. The next wave of progress – AI-driven products, predictive operations and autonomous decision-making – depends on cloud architectures designed to support intelligence natively. This means cloud and AI will advance together or not at all.

The Cognitive Cloud: Cloud and AI as One System

For years, many organizations treated migration as a finish line. Applications were lifted and shifted into the cloud with little redesign, trading one set of constraints for another. The result, in many cases, has been higher costs, fragmented data and limited room for innovation. “Cognitive cloud” represents a new phase of evolution. Imagine every process, from customer service to supply-chain management, powered by AI models that learn, reason and act within secure cloud environments. These systems store and interpret data, detect patterns, anticipate demand and automate decisions at a scale humans simply cannot match. In this architecture, AI and cloud operate in concert. The cloud provides computing power, scale and governance while AI adds autonomy, context and insight. Together, they form an integrated platform where cloud foundations and AI intelligence combine to enable collaboration between people and systems. This marks the rise of the responsive enterprise; one that senses change, adjusts instantly and builds trust through reliability. Cognitive cloud platforms combine data fabric, observability, FinOps and SecOps into an intelligent core that regulates itself in real time. The result is invisible to consumers but felt in every interaction: fewer errors, faster responses and consistent experiences.

Consumer Impact is Growing

The impact of cognitive cloud is already visible. In health care, 65% of U.S. insurance claims run through modernized, cloud-enabled platforms designed to reduce errors and speed up reimbursement. In the life sciences industry, a pharmaceuticals and diagnostics firm used cloud-native automation to increase clinical trial investigations by 20%, helping get treatments to patients sooner. In food service, intelligent cloud systems have reduced peak staffing needs by 35%, in part through real-time demand forecasting and automated kitchen operation. In insurance, modernization has produced multi-million-dollar savings and faster policy issuance, improving both customer experience and financial performance. Beneath these outcomes is the same principle: architecture that learns and responds in real time. AI-driven cloud systems process vast volumes of data, identify patterns as they emerge and automate routines so people can focus on innovation, care and service. For businesses, this means fewer bottlenecks and more predictive operations. For consumers, it means smarter, faster, more reliable services, quietly shaping everyday life. While cloud engineering and AI disciplines remain distinct, their outcomes are increasingly intertwined. The most advanced architectures now treat intelligence and infrastructure as complementary forces, each amplifying the other.

Looking Ahead

This transformation is already underway. Self-correcting systems predict disruptions before they happen, AI models adapt to market shifts in real time and operations learn from every transaction. The organizations mastering this convergence are quietly redefining themselves and the competitive landscape. Cloud and AI have become interdependent priorities within a shared ecosystem that moves data, decisions and experiences at the speed customers expect. Companies that modernize around this reality and treat intelligence as infrastructure will likely be empowered to reinvent continuously. Those that don’t may spend more time maintaining the systems of yesterday than building the businesses of tomorrow. Learn more at cognizant.com.   Photo courtesy of Shutterstock collect?v=1&tid=UA 482330 7&cid=1955551e 1975 5e52 0cdb 8516071094cd&sc=start&t=pageview&dl=http%3A%2F%2Ftrack.familyfeatures SOURCE: Cognizant
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The Knowledge

Beneath the Waves: The Global Push to Build Undersea Railways

Undersea railways are transforming transportation, turning oceans from barriers into gateways. Proven by tunnels like the Channel and Seikan, these innovations offer cleaner, reliable connections for passengers and freight. Ongoing projects in China and Europe, alongside future proposals, signal a new era of global mobility beneath the waves.

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Train traveling through underwater tunnel
Trains beneath the ocean are no longer science fiction—they’re already in operation.

For most of modern history, oceans have acted as natural barriers—dividing nations, slowing trade, and shaping how cities grow. But beneath the waves, a quiet transportation revolution is underway. Infrastructure once limited by geography is now being reimagined through undersea railways.

Undersea rail tunnels—like the Channel Tunnel and Japan’s Seikan Tunnel—proved decades ago that trains could reliably travel beneath the ocean floor. Today, new projects are expanding that vision even further.

Around the world, engineers and governments are investing in undersea railways—tunnels that allow high-speed trains to travel beneath oceans and seas. Once considered science fiction, these projects are now operational, under construction, or actively being planned.

image 3

Undersea Rail Is Already a Reality

Japan’s Seikan Tunnel and the Channel Tunnel between the United Kingdom and France proved decades ago that undersea railways are not only possible, but reliable. These tunnels carry passengers and freight beneath the sea every day, reshaping regional connectivity.

Undersea railways are cleaner than short-haul flights, more resilient than bridges, and capable of lasting more than a century. As climate pressures and congestion increase, rail beneath the sea is emerging as a practical solution for future mobility.

What’s Being Built Right Now

China is currently constructing the Jintang Undersea Railway Tunnel as part of the Ningbo–Zhoushan high-speed rail line, while Europe’s Fehmarnbelt Fixed Link will soon connect Denmark and Germany beneath the Baltic Sea. These projects highlight how transportation and technology are converging to solve modern mobility challenges.

The Mega-Projects Still on the Drawing Board

Looking ahead, proposals such as the Helsinki–Tallinn Tunnel and the long-studied Strait of Gibraltar rail tunnel could reshape global affairs by linking regions—and even continents—once separated by water.

Why Undersea Rail Matters

The future of transportation may not rise above the ocean—but run quietly beneath it.

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CES 2026

Inside the Computing Power Behind Spatial Filmmaking: Hugh Hou Goes Hands-On at GIGABYTE Suite During CES 2026

Inside the Computing Power Behind Spatial Filmmaking: Hugh Hou Goes Hands-On at GIGABYTE Suite During CES 2026

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Spatial filmmaking is having a moment—but at CES 2026, the more interesting story wasn’t a glossy trailer or a perfectly controlled demo. It was the workflow.

According to a recent GIGABYTE press release, VR filmmaker and educator Hugh Hou ran a live spatial computing demonstration inside the GIGABYTE suite, walking attendees through how immersive video is actually produced in real-world conditions—capture to post to playback—without leaning on pre-rendered “best case scenario” content. In other words: not theory, not a lab. A production pipeline, running live, on a show floor.

Inside the Computing Power Behind Spatial Filmmaking: Hugh Hou Goes Hands-On at GIGABYTE Suite During CES 2026
Inside the Computing Power Behind Spatial Filmmaking: Hugh Hou Goes Hands-On at GIGABYTE Suite During CES 2026

A full spatial pipeline—executed live

The demo gave attendees a front-row view of a complete spatial filmmaking pipeline:

  • Capture
  • Post-production
  • Final playback across multiple devices

And the key detail here is that the workflow was executed live at CES—mirroring the same processes used in commercial XR projects. That matters because spatial video isn’t forgiving. Once you’re working in 360-degree environments (and pushing into 8K), you’re no longer just chasing “fast.” You’re chasing:

  • System stability
  • Performance consistency
  • Thermal reliability

Those are the unsexy requirements that make or break actual production days.

Playback across Meta Quest, Apple Vision Pro, and Galaxy XR

The session culminated with attendees watching a two-minute spatial film trailer across:

  • Meta Quest
  • Apple Vision Pro
  • Newly launched Galaxy XR headsets
  • Plus a 3D tablet display offering an additional 180-degree viewing option

That multi-device playback is a quiet flex. Spatial content doesn’t live in one ecosystem anymore—creators are being pulled toward cross-platform deliverables, which adds even more pressure on the pipeline to stay clean and consistent.

Where AI fits (when it’s not the headline)

One of the better notes in the release: AI wasn’t positioned as a shiny feature. It was framed as what it’s becoming for a lot of editors—an embedded toolset that speeds up the grind without hijacking the creative process.

In the demo, AI-assisted processes supported tasks like:

  • Enhancement
  • Tracking
  • Preview workflows

The footage moved through industry-standard software—Adobe Premiere Pro and DaVinci Resolve—with AI-based:

  • Upscaling
  • Noise reduction
  • Detail refinement

And in immersive VR, those steps aren’t optional polish. Any artifact, softness, or weird noise pattern becomes painfully obvious when the viewer can look anywhere.

Why the hardware platform matters for spatial workloads

Underneath the demo was a custom-built GIGABYTE AI PC designed for sustained spatial video workloads. Per the release, the system included:

  • AMD Ryzen 7 9800X3D processor
  • Radeon AI PRO R9700 AI TOP GPU
  • X870E AORUS MASTER X3D ICE motherboard

The point GIGABYTE is making is less “look at these parts” and more: spatial computing workloads demand a platform that can run hard continuously—real-time 8K playback and rendering—without throttling, crashing, or drifting into inconsistent performance.

That’s the difference between “cool demo” and “reliable production machine.”

The bigger takeaway: spatial filmmaking is moving from experiment to repeatable process

By running a demanding spatial filmmaking workflow live—and repeatedly—at CES 2026, GIGABYTE is positioning spatial production as something creators can depend on, not just test-drive.

And that’s the shift worth watching in 2026: spatial filmmaking isn’t just about headsets getting better. It’s about the behind-the-scenes pipeline becoming stable enough that creators can treat immersive production like a real, repeatable craft—because the tools finally hold up under pressure.

Source:PRNewswire – GIGABYTE press release

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Welcome to the Consumer Corner section of STM Daily News, your ultimate destination for savvy shopping and informed decision-making! Dive into a treasure trove of insights and reviews covering everything from the hottest toys that spark joy in your little ones to the latest electronic gadgets that simplify your life. Explore our comprehensive guides on stylish home furnishings, discover smart tips for buying a home or enhancing your living space with creative improvement ideas, and get the lowdown on the best cars through our detailed auto reviews. Whether you’re making a major purchase or simply seeking inspiration, the Consumer Corner is here to empower you every step of the way—unlock the keys to becoming a smarter consumer today!

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