Track market-moving stories before they get noisy

Integration of NVIDIA Jetson Edge Computing and RTX Accelerators Establishes High-Performance Foundation for Commercial Human-and-Robot Workforces

Workforce OS Leverages NVIDIA Project GR00T, Isaac Sim, Isaac ROS, and TensorRT to Accelerate Sim-to-Real Deployments Across Enterprise Hospitality with Unitree Humanoid Robotics

, /PRNewswire/ -- YYFORCE Inc. (NASDAQ: YFOR) ("YYForce" or the "Company"), a technology-enabled provider of workforce solutions and integrated facility management services, today announced its strategic plans to develop and scale its modular robotics operating architecture, Workforce OS. Designed to integrate human workforces with embodied artificial intelligence, the software stack leverages NVIDIA compute and robotics technologies to power commercial autonomous deployments, including integrations with Unitree humanoid robots and specialized service automation platforms. 

Rather than building isolated software for single-purpose hardware, YYForce is architecting Workforce OS as a standardized, hardware-agnostic platform spanning computer vision, high-precision SLAM navigation, multi-axis manipulation, natural language interaction, and multi-agent fleet orchestration. 

High-Performance Physical AI Architecture Powered by NVIDIA
To establish a resilient foundation for real-time edge autonomy and scalable model training, Workforce OS integrates full-stack NVIDIA robotics and AI platforms:

Edge and Acceleration Hardware: Real-time onboard perception, sensor fusion, and low-latency motor control will be driven by NVIDIA Jetson edge AI modules deployed on robotic bodies, backed by high-performance NVIDIA RTX GPUs for accelerated inference and local edge processing.

Embodied AI & Humanoid Foundations: YYForce is adopting the NVIDIA Project GR00T foundation model framework alongside NVIDIA Isaac Sim—powered by Omniverse—to execute rapid simulation-to-real (Sim-to-Real) training, synthetic data generation, and digital-twin task validation before physical rollout.

Operational Acceleration: By utilizing NVIDIA Isaac ROS for hardware-accelerated VSLAM and navigation, as well as NVIDIA TensorRT for deep learning inference optimization, the platform is designed to maximizes computational efficiency across both stationary manipulators and Unitree bipedal humanoid platforms.

Pragmatic Execution: Phased Roadmaps from Structured Operations to Full Humanoid Integration
To minimize the prolonged research cycles typical of unstructured automation tasks (such as autonomous wet-facility cleaning), YYForce is executing a phased commercialization roadmap that is designed to validate real-world stability across controlled enterprise hospitality environments: 

Phase 1 (Months 0–2): Foundation & Intelligent Concierge — Establishing real-time navigation, guest-facing conversational workflows, and front-desk integration using Jetson edge modules and Isaac ROS. 
Phase 2 (Months 2–4): Mobile Manipulation & Beverage Service — Deploying stationary and wheeled robotic arms equipped with fine-motor grasping, dynamic load balancing, and handover mechanics for banquet and food & beverage environments. 
Phase 3 (Months 4–6): Banquet & Hospitality Event MVP — Orchestrating multi-robot collaborative operations—combining mobile bases, arm manipulation, and pilot-stage Unitree humanoid robots for live hotel banquet and event operations. 
Long-Term Target: Autonomous IFM & Humanoid Field Operations — Transitioning mature Vision-Language-Action (VLA) models, learned humanoid locomotion, and system orchestration layers into complex, unstructured physical tasks, including automated facility maintenance and industrial cleaning. 

Expanding Core Engineering Strength
"Our strategic objective is to own the software intelligence layer that makes diverse commercial robots truly useful in live business environments," said Mike Fu, Chief Executive Officer of YYForce. "By combining NVIDIA's industry-defining physical AI computing stack with versatile hardware like Unitree humanoid platforms, we aim to bridge the gap between simulation and real-world execution. Our existing footprint across hotels and enterprise facilities can provide a valuable real-world testbed and data-flywheel engine, turning bleeding-edge robotics into practical human workforce augmentation." 

To spearhead this technical roadmap, the Company is deploying a specialized core engineering task force comprising domain leads across Autonomous Navigation, Perception & Multimodal Interaction, Motion & Manipulation Control, Embodied VLA Models, and Distributed Systems Architecture. We expect that this focused engineering structure will prioritize continuous fleet orchestration, dynamic labor allocation, and deep interoperability with YYForce's operational network.

About YYFORCE
YYForce Inc. (Nasdaq: YFOR) is an AI-enabled workforce management and integrated facility management provider headquartered in Singapore and operating across Asia and beyond. Through its workforce technology and IFM businesses, YYForce provides workforce deployment, management and facility services solutions across multiple service industries.

The Company's workforce platform, YY Circle, supports workforce deployment and management across sectors including hospitality, food and beverage, retail and other service industries. Within its IFM operations, YYForce combines frontline facility services with technology solutions designed to improve workforce productivity and operational efficiency.

YYForce's long-term strategy is centered on building an integrated future workforce ecosystem in which human workers, intelligent software, automation and robotics increasingly work together to deliver services more efficiently.

Forward-Looking Statements
This press release contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. The Company bases these forward-looking statements on its expectations and projections about future events, which the Company derives from the information currently available to it. You can identify forward-looking statements by those that are not historical in nature, particularly those that use terminology such as "may," "should," "expects," "anticipates," "contemplates," "estimates," "believes," "plans," "projected," "predicts," "potential," or "hopes" or the negative of these or similar terms. Statements regarding the planned development, features, timelines and commercialization of the Workforce OS platform and related robotics applications are forward-looking statements. Forward-looking statements involve inherent risks and uncertainties, and the forward-looking events discussed in this press release may not occur, and actual events and results may differ materially and are subject to risks, uncertainties, and assumptions about the Company and a number of factors. These factors include, but are not limited to, the Company's goals and strategies; the Company's ability to successfully develop, test and commercialize Workforce OS and related robotics offerings on the anticipated timeline or at all, including risks associated with transferring simulation-based training to real-world environments; the Company's dependence on third-party hardware, software and technology providers, including NVIDIA and Unitree, and the availability and terms of such technologies; the Company's ability to recruit and retain qualified engineering personnel; the Company's ability to obtain sufficient capital to fund its robotics initiatives; safety, liability, privacy and regulatory risks associated with deploying robotics in customer-facing environments; competition from other robotics and automation providers; the Company's future business development, financial condition and results of operations, including the introduction of new products and services, expected changes in the Company's revenues, costs and expenditures, anticipated customer growth, and demand for and market acceptance of the Company's products and services; and industry, market and regulatory conditions, including competition, government policies and regulations affecting the Company's industry, and other factors that may affect the Company's financial condition, liquidity and results of operations. For a more detailed discussion of risk factors, please refer to the Company's filings with the Securities and Exchange Commission, including the "Risk Factors" section of the Company's most recent annual report on Form 20-F, as amended. Readers should also consider the risks described in the Company's filings with the U.S. Securities and Exchange Commission. YYForce undertakes no obligation to update these statements except as required by applicable law.

Investor Contact
Jason Zhi Yong Phua, Chief Financial Officer
YYForce Inc.
[email protected]

Investor Relations Contact
Piacente Financial Communications
[email protected]

SOURCE YYForce Inc.

Bullish signals from three different links of the AI chain help the Nasdaq Composite undo most of Friday's selloff.

Nvidia NVDA shares climbed 2.44% on Wednesday at around 1:20 PM EST after the chipmaker unveiled a new reference design intended to speed up the construction of AI data centers, as the company looks to address infrastructure constraints that have slowed the expansion of computing capacity. The stock's advance came amid a broader recovery in chipmakers following last week's weakness.

French AI company, Pigment has raised $250 million at a $2.3 billion valuation as it aims to take on the dominance of Microsoft's Excel and PowerPoint. Co-CEO Eléonore Crespo explains why backing from Nvidia is a particular validation of the startup and how it's looking to investors in Asia to help expand into that region.

Nvidia just posted triple-digit revenue growth and guided even higher, yet the stock sits barely above where it started the year. The question of whether shares can surge another 63% by 2027 comes down to three things that all have…

NVIDIA (NASDAQ:NVDA | NVDA Price Prediction | NVDA Price Prediction) just reported $96.22B in quarterly revenue, up 105.8% year over year. It guided to $108B for the current quarter. Annualize that guide and you get a $432B run rate.

A path to far larger annual revenue is starting to show. Even so, the stock is up only 15.08% year to date. So can NVIDIA hit $350 in 2027?

What’s Holding NVIDIA Back Right Now
Investors are worried about funding. Shares fell 6.61% last week and are up just 0.11% over the past month. CNBC reported that Nvidia, AMD and Dell sank in a global tech rout on AI funding worries. Supply commitments have climbed to $279B, and guidance includes no China Data Center compute revenue.

Management also expects gross margins to bottom in the 71% to 72% range in Q4. With a beta of 2.216, the stock tends to swing harder than the market whenever confidence in AI spending slips.

Analysts Are Bullish, and I Think They Are Still Too Cautious
Wall Street’s consensus target is $328.72. Analyst ratings break down to 10 Strong Buys, 49 Buys, 2 Holds and 1 Sell. Our model’s central estimate is $258.42, which is 20.68% upside, and its full range runs from $225.15 to $269.13. The model’s confidence level is high at 0.9.

I think the model understates the upside. It applies a 50% mega-cap penalty, so 95% bullish analyst sentiment and 127.8% earnings growth add only slightly to the target. Earnings growth contributes just 0.03 to the factor.

Here’s What It Takes for NVIDIA to Reach $350
A climb to $350 from the current price of $214.13 would require a gain of 63.5%.

With forward EPS of $13.1768, a price of $350 implies a forward P/E of 27x. Our central forecast already implies 20x, so the bold target requires about 7x of additional multiple expansion.

I think that is possible. Earnings are growing fast enough to shrink the multiple: the trailing P/E of 43 drops to 16 on forward numbers. Revenue per gigawatt rises from $25 billion with Blackwell to $40 billion with Vera Rubin. Top hyperscaler capex is expected to reach $1.3 trillion in 2027. Jensen Huang also said CoreWeave is improving and no backstop is needed.

On the earnings call, he put it simply: “AI has reached its inflection point. It’s doing useful work. Its tokens are productive and profitable. Now, compute is revenue.” He added that “the unconstrained would be a lot higher” than the roughly 70% growth outlook for fiscal 2028.

A key risk is that AI financing dries up before Vera Rubin capacity reaches customers.

That financing question is also why the picks-and-shovels names around NVIDIA matter so much right now; we rounded up seven suppliers driving the data-center expansion, from electricity to cooling, which you can read here: 7 Stocks Powering the AI Boom (That Aren’t Chipmakers).

Where NVIDIA Trades Today vs Its Earnings Power
At 16x forward earnings, NVIDIA looks cheap for a company growing revenue at triple-digit rates. Shares trade between a 52-week bottom of $163.90 and a peak of $243.37.

Over 10 years, the stock has returned 13,002.9%. At today’s multiple, investors pay little for the growth the bull case depends on.

$350 Is a Stretch, but Here’s Why It’s Possible
Hitting $350 requires a 63.5% gain. My verdict: it’s a stretch, but a credible one. Three things need to go right. Vera Rubin has to ramp as the fastest launch in NVIDIA’s history.

Supply has to ease enough to let revenue follow demand. And the market has to stop pricing in a funding scare. A prolonged freeze in AI capital markets would halt it. Returns at this level shouldn’t be expected every year, but we’ve outlined the plan for how NVIDIA could reach $350 in 2027.

Contact [email protected] for any questions or corrections.

NVIDIA Corporation (NASDAQ:NVDA) is in the spotlight this week as its GTC Berlin conference runs Oct. 20 to Oct. 22. The event didn't lift Nvidia's stock price much, but one market expert is excited for what's to come.

The debate over whether Advanced Micro Devices (AMD +2.76%) or Nvidia (NVDA +1.55%) is the better GPU stock has raged on for ages. At the start of the artificial intelligence (AI) arms race in 2023, it was Nvidia all day. In 2026, that narrative shifted in AMD's favor as its stock has risen about 150%, well above Nvidia's comparatively tame 16% return.

But all of that is in the past; what matters more is what each one will do in the future. I think there's one metric that points to which stock will be the better performer, and it clearly favors Nvidia.

Image source: The Motley Fool.

Nvidia's revenue growth is superior to AMD's
In 2026, AMD has made significant strides toward becoming more competitive in its product offerings. Several AI hyperscalers are starting to deploy more AMD products, which has caused many investors to assume that AMD is winning some ground in data centers versus Nvidia. But that's not the case.

During Q2, AMD's data center revenue rose 107% year over year to $6.7 billion, so clearly it's trending in the right direction. However, AMD has a much more diversified business than Nvidia, and right now, diversification is hurting AMD. Data center products are the only place to be right now, and AMD's 50% overall revenue growth rate to $11.5 billion shows just how slowly the other parts of its business are growing compared to data center.

AMD Advanced Micro Devices$549.49+$14.75 (+2.76%)

NASDAQ · As of 12:30 PM ET 10/21/26

Nvidia is a much larger company, and its data center business grew 117% to $89 billion in its most recent quarter. Nvidia is both larger and growing faster, so the AMD-catching-up thesis isn't entirely accurate. AMD may be getting to the point where it's somewhat even with Nvidia, but the AI community still prefers Nvidia hardware. Overall, Nvidia's revenue grew at a 106% pace to $96.2 billion.

Nvidia is still the stronger company overall due to its focus on data centers. With both AMD and Nvidia projecting that the AI build-out will last through at least 2030, we're still in the early stages of the massive spending spree. So, Nvidia's positioning will help it thrive as a company overall versus AMD. However, this isn't reflected in their valuations, and this is the metric that points to Nvidia being the far better buy.

AMD has a ton of growth baked into the stock price
If we utilize next year's earnings projections to value the companies, a clear pattern emerges.

AMD PE Ratio (Forward 1y) data by YCharts

If both companies hit next year's earnings projections, Nvidia will trade at 13 times earnings, while AMD will trade at 33.5 times earnings. I would argue that about 30 times earnings represents a fair stock price to trade at, and AMD would be hovering around that level. However, to get there, AMD's stock price would need to stay flat between now and then.

On the flip side, Nvidia's stock would need to more than double. In fact, Nvidia's stock trades at 27 times earnings right now. Because AMD hasn't reported Q3 results yet, this essentially tells investors that there is more than a year and a half's worth of growth baked into AMD's stock price relative to Nvidia's.

That's a huge premium to pay for a company that frankly isn't doing as well as Nvidia. I think this clearly tips the favor in Nvidia's favor, and it is by far the better stock to buy right now.

NVDA Nvidia$219.83+$3.36 (+1.55%)

NASDAQ · As of 12:27 PM ET 10/21/26

We'll see if AMD's revenue growth continues accelerating, as it reports Q3 earnings on Nov. 3. AMD's growth rate needs to continue rapidly accelerating; otherwise, it risks being left behind by Nvidia. Furthermore, it really needs to outgrow Nvidia to show the market why it deserves the premium. If it cannot, I wouldn't be surprised to see the stock sell off as investors dump AMD and rotate into Nvidia.

SEATTLE--(BUSINESS WIRE)-- #absolutesecurity--During NVIDIA GTC Berlin, Absolute Security, a leader in Autonomous Cyber Resilience, announced it is collaborating with NVIDIA to deliver firmware-embedded security, endpoint management, and resilience solutions for advanced AI enterprise workstations. This integration will help enterprise security and IT leaders ensure their AI developers' autonomous agents function within the boundaries of security and compliance policies, and that their devices remain defended agai.

EMERYVILLE, Calif.--(BUSINESS WIRE)--Tanium, a leader in Autonomous IT, today announced a collaboration with NVIDIA to extend its enterprise-grade endpoint management to NVIDIA's local AI infrastructure — including RTX Spark, NVIDIA's new Windows AI PC platform; DGX Station, NVIDIA's most powerful deskside AI supercomputer; the newly announced DGX Station for Windows, NVIDIA's Windows deskside AI supercomputer; and DGX Spark, NVIDIA's compact AI supercomputer. Enterprises can now manage these A.

BERLIN – NVIDIA GTC--(BUSINESS WIRE)--Red Hat, the world's leading provider of open source solutions, today announced expanded updates in its ongoing collaboration with NVIDIA to accelerate security-focused, enterprise-grade agentic AI across the open hybrid cloud using Red Hat AI Factory with NVIDIA. By combining agent security capabilities, optimized model deployment architectures and deep hardware enablement, Red Hat and NVIDIA are empowering organizations to build, deploy and scale autonomo.

MADRID--(BUSINESS WIRE)--Amadeus and NVIDIA have been collaborating to explore how accelerated computing and travel-specific AI could support faster, more scalable and more efficient flight search. Building on this work, the companies have now signed a Memorandum of Understanding (MoU) to deepen their collaboration and accelerate further exploration. As AI assistants increasingly search on behalf of travelers, they are changing both the volume and complexity of demand placed on travel technolog.

Nvidia CEO Jensen Huang pushed Europe to adopt artificial intelligence more quickly. “For Europe to benefit from AI, and to have really created an AI ecosystem and AI economy, you need all of the end markets, the end industries to adopt AI,” Huang said Wednesday at his company's GTC conference in Berlin.

The person shouted something that could not be heard on the company's livestream about 20 minutes into the address, before being removed from the auditorium.

Chip Stocks Have Pulled Back—Here's How 3 Semiconductor ETFs Stack Up for InvestorsNVIDIA NASDAQ: NVDA outlined a broad plan to expand Europe’s artificial intelligence economy at its GTC event in Berlin, highlighting investments, AI infrastructure, agent security, physical AI systems and new computing platforms.

The company said it has operated in Europe for 33 years and has invested nearly $10 billion across startups and partnerships in the region during the past year. NVIDIA said it has more than 12,000 partnerships across Europe and recently announced investments in 14 startups during visits to France, the U.K., Sweden and Germany.

Get NVIDIA alerts:

ServiceNow Orchestrates AI's Next Act—Can Earnings Deliver?The presentation framed AI as an industrial system rather than solely a software technology. NVIDIA described a five-layer AI economy comprising energy, advanced computing, AI factories, AI models and applications. The company said Europe is building capacity across those layers through partnerships with organizations including Schneider Electric, Siemens Energy, neocloud providers and telecommunications companies.

Vera Rubin Systems and DSX Pods
NVIDIA said its Vera Rubin platform is in full production and represents the next generation of its AI computing architecture. The company said Vera Rubin combines GPUs, CPUs, networking, storage acceleration and software intended to support the full range of agentic AI workloads, including model inference, data processing and accelerated tools.

The AI Buildout Is Only 15% Complete—Here Is Where the Next Dollar Actually GoesAccording to NVIDIA, the Vera Rubin NVLink system connects 72 GPUs into a single computing system. The company said each GPU delivers 20 petaflops of performance. NVIDIA also described its Spectrum-X networking hardware as incorporating co-packaged optics, which directly connects silicon photonics to the chip.

NVIDIA said Vera Rubin is designed to be fully liquid cooled and can be assembled in less than five minutes per node, compared with roughly two hours for a Grace Blackwell node. It also said Vera Rubin provides another 30-fold performance increase over Blackwell for large-language-model processing, while Blackwell was about 30 times faster than Hopper for that workload.

The company also introduced NVIDIA DSX Pod, a factory-integrated AI infrastructure system based on Vera Rubin NVL72 systems. NVIDIA said the pods are fully cabled, factory tested and delivered in transportable containers, with the aim of reducing on-site deployment time from several months to days once site utilities are ready.

NVIDIA said the DSX reference architecture encompasses computing, networking, storage, software, power and cooling. It added that its DSX MaxLPS power-management system can use 30% less power for the same output, while the platform’s liquid-cooling design can reduce water use in suitable climates.

OpenShell for AI Agent Security
A central focus of the event was AI agents, which NVIDIA described as systems that can reason, plan, use tools and access enterprise knowledge. The company introduced OpenShell, an open-source secure runtime designed to control what agents can access and execute.

OpenShell uses isolated sandboxes, policy enforcement for system calls, file access and network connections, and formal verification intended to ensure agents do not receive more access than permitted. NVIDIA Sentry, an optional product running on BlueField-4 hardware, adds monitoring and policy enforcement in a hardware-isolated environment, according to the company.

NVIDIA said OpenShell is available under the Apache 2.0 license and can be used from edge systems to cloud infrastructure. It also announced a partnership with Anthropic to develop Claude OpenShell agents.

The company said businesses will increasingly use a mix of closed, open and customized AI models. NVIDIA highlighted its open-model portfolio, including Nemotron for language applications, Cosmos for world models, GR00T for robotics, Alpamayo for autonomous navigation, Ising for quantum-classical computing and Earth-2 for physics AI.

NVIDIA also described an “Agent Knowledge Foundation,” including Nemotron Parse, Nemotron Embed, Nemotron Rerank and Kumo, intended to help organizations use both unstructured documents and structured databases with AI agents. The company said CUDA-X libraries remain a core part of its strategy, providing accelerated tools for workloads such as fluid dynamics, quantum chemistry, data processing and rendering.

Physical AI, Vehicles and Robotics
NVIDIA said physical AI will be a major next phase of AI development, including telecommunications, medical applications, autonomous vehicles and humanoid robots. The company said it completed its first commercial phone call using CUDA-based technology on T-Mobile’s network with Nokia after nearly eight years of work.

In autonomous vehicles, NVIDIA said its Hyperion reference architecture includes 14 cameras, nine radar systems, three lidars and other sensors, supported by dual NVIDIA GPU systems. It announced that the Volkswagen van, Jaguar Land Rover’s new vehicle, Volvo’s fleet and Mercedes’ next-generation vehicles will be Hyperion compatible.

For humanoid robotics, NVIDIA said it is developing a reference robot called NVIDIA Agile ONE with Agile Robots. The company said the system will be available in the first quarter of next year and will arrive preassembled with integrated computing and software.

RTX Spark Personal AI Computers
NVIDIA also introduced RTX Spark, a new line of desktops, laptops and workstations developed with Microsoft and the broader PC industry. The company said RTX Spark is based on its N1X chip and delivers 1 petaflop of performance with 128 GB of memory. NVIDIA said a DGX Station running Windows will offer 20 petaflops and 754 GB of memory and is expected to be available by the end of the year.

The event concluded with a demonstration in which an AI agent used an RTX Spark system, cloud-based training resources, Omniverse digital-twin software and NVIDIA tools to train a small robot called Microduck to navigate a course.

NVIDIA said its broader objective is to provide the infrastructure, models, security software and development tools needed for European companies to deploy AI agents and physical AI systems across their operations.

About NVIDIA (NASDAQ:NVDA)NVIDIA Corporation NASDAQ: NVDA is a technology company that designs graphics processing units (GPUs), accelerated computing platforms, networking products and related software. Its technologies support artificial intelligence, machine learning, scientific computing, data analytics, professional visualization and computer graphics.

The company's products include GeForce GPUs for gaming and personal computing, data center GPUs and systems for AI and high-performance computing, and networking solutions used to connect and manage large-scale computing infrastructure.

This instant news alert was generated by narrative science technology and financial data from MarketBeat in order to provide readers with the fastest reporting and unbiased coverage. Please send any questions or comments about this story to [email protected].

Should You Invest $1,000 in NVIDIA Right Now?Before you consider NVIDIA, you'll want to hear this.

MarketBeat keeps track of Wall Street's top-rated and best performing research analysts and the stocks they recommend to their clients on a daily basis. MarketBeat has identified the five stocks that top analysts are quietly whispering to their clients to buy now before the broader market catches on... and NVIDIA wasn't on the list.

While NVIDIA currently has a Buy rating among analysts, top-rated analysts believe these five stocks are better buys.

View The Five Stocks Here

Tesla, Nvidia, and Google helped shape the last era of market growth, but the next wave could come from a new group of companies. Inside this report, you’ll find 7 stocks that could play a major role in the next tech-driven market boom.

Get This Free Report

Continue following MarketBeat

Add MarketBeat as your preferred source on Google to see our latest stories in your feed.

News Summary: 

NVIDIA DSX reference designs use closed-loop liquid cooling and dry coolers to enable near-zero facility cooling water consumption, with potential savings of 54 million liters a day for a 2-gigawatt deployment — equivalent to the daily water use of 180,000 households.AI clouds in Europe are building and operating NVIDIA DSX-based AI factories, expanding access to accelerated computing for the continent’s enterprises, developers and governments.NVIDIA DSX MaxLPS software helps operators use up to 30% less power to generate the same number of tokens, with CoreWeave, Firmus, Google Cloud, IREN, Lambda, Nebius, Nscale and Sharon AI planning to use the technology, while DSX Flex software turns AI factories into flexible power loads to support grid reliability and enable faster grid connection.NVIDIA SimReady Central, a hub for simulation-ready digital models of physical equipment, launches on Hugging Face with validated power and cooling assets, helping operators build and simulate DSX AI factory digital twins faster.New NVIDIA DSX OS open source software automates infrastructure lifecycle and improves health automation as well as resiliency capabilities to help operators run AI factories at scale.An expanding ecosystem — including technology and industrial AI leaders AVEVA, Dassault Systèmes and Siemens, and energy and cooling providers ABB, Eaton, GE Vernova, Hitachi Energy, Schneider Electric, Siemens Energy, Trane Technologies and Vertiv — is connecting AI factory design, power, cooling and operations to support Europe’s accelerated computing buildout. BERLIN, Oct. 21, 2026 (GLOBE NEWSWIRE) -- GTC Berlin -- NVIDIA today announced that Europe’s leading ecosystem partners are adopting the NVIDIA DSX™ AI Factory Platform to build AI factories that minimize water consumption for cooling and use less power for the same AI output. The platform also helps partners bring new capacity online faster and adapt workload power consumption to support grid reliability.  

NVIDIA DSX is a full-stack AI factory reference architecture, co-innovated with the world’s leading infrastructure companies. Compute, networking, storage, software, power and cooling are codesigned as one system — optimized from design to operation. 

AI clouds and leading design, construction, energy and cooling providers are using DSX to build and operate infrastructure serving Europe’s enterprises, developers and governments.

“Europe’s technology leadership depends on how efficiently we turn power and infrastructure into intelligence,” said Warren Barkley, vice president of DSX product management at NVIDIA. “NVIDIA DSX brings together the technologies and ecosystem expertise operators need to build responsibly, operate efficiently at scale and bring intelligence to the market faster.”

The NVIDIA DSX platform includes DSX MaxLPS™ for dynamic power allocation, DSX Flex for coordinating workload power consumption with grid conditions, DSX Reference Design for validated infrastructure architectures, DSX Sim™ for simulation, DSX OS™ for infrastructure management and DSX Exchange™ for connecting computing and facility systems. These technologies help operators design, deploy and run AI factories that save valuable resources. 

NVIDIA DSX Rethinks Cooling
Conventional cooling towers remove heat by evaporating water, requiring a continual supply of replacement water. NVIDIA DSX reference designs connect liquid-cooled computing with dry-cooler-based heat rejection that avoids evaporation: Cooling liquid absorbs heat from computing equipment and circulates in a closed loop, while outdoor dry coolers, similar to large radiators, release that heat into the air without evaporating water.

NVIDIA Vera Rubin infrastructure supports 100% liquid cooling with coolant temperatures of up to 45 degrees Celsius. With dry-cooler-based designs, this architecture can reduce facility cooling water consumption to near zero. At 2-gigawatt scale, NVIDIA DSX can save 54 million liters of water a day compared with conventional cooling-tower-based systems — equivalent to the daily water use of 180,000 households. Local climate determines whether supplemental mechanical cooling is needed during the hottest periods.

Delivering the Same AI Output With Less Power
Power availability defines how much capacity operators can bring online. DSX MaxLPS and DSX Flex address this constraint.

DSX MaxLPS dynamically allocates power within an AI factory’s provisioned budget, helping operators generate the same number of tokens with up to 30% less power. Operators can also use this efficiency to support more GPU capacity and higher throughput within existing power budgets. CoreWeave, Firmus, Google Cloud, IREN, Lambda, Nebius, Nscale and Sharon AI are exploring the software.

In a proof of concept across NVIDIA HGX™ B200 systems with DSX MaxLPS, Lambda demonstrated 24% more cluster token throughput and 19% more GPU capacity within a fixed power budget.

Coordinating AI Factory Power Demand With the Grid
DSX Flex helps AI factories become flexible assets for the power grid, enabling operators to adapt workload power consumption to utility needs, demand-response events and energy prices. It can also coordinate electricity from the grid, onsite renewables and energy storage, helping AI factories operate as flexible power loads that support grid reliability and enable faster grid connection. 

In an early trial, Emerald AI, EPRI, Nebius, the U.K. National Grid and NVIDIA demonstrated reductions of up to 40% in the cluster’s power draw on an NVIDIA Blackwell Ultra GPU cluster in response to simulated grid events, while critical workloads continued running.

Nscale Advances AI Factory Efficiency With NVIDIA DSX
Using DSX MaxLPS, DSX Flex and DSX Sim, Nscale is demonstrating how the NVIDIA DSX platform connects power optimization, grid-responsive operations and design.

Based on an evaluation run in Nscale AI factory in Iceland, using DSX MaxLPS across four NVIDIA GB300 NVL72 racks, Nscale demonstrated 49% higher inference throughput and 37% more managed GPU capacity within the same 264-kilowatt provisioned power budget. The results demonstrate how dynamic power allocation can unlock additional capacity from existing infrastructure.

Nscale is also exploring DSX Flex to align workload power consumption with grid conditions. 

“Europe’s AI ambitions demand that we make every megawatt count,” said Josh Payne, founder and CEO of Nscale. “With NVIDIA DSX, we’re building AI factories that deliver more compute from available power, respond to grid conditions and move faster from design to deployment.”

For its facilities in Portugal and Iceland, Nscale is using DSX Sim to create digital twins that help evaluate power, cooling and infrastructure configurations before deployment. By validating designs virtually, Nscale can identify potential issues earlier, reduce deployment risk and accelerate the path from planning to productive capacity.

Accelerating AI Factory Design With DSX Sim and SimReady Central Library
NVIDIA is launching SimReady Central Library with validated power and cooling equipment assets from partners like Vertiv, accelerating the creation of DSX AI factory digital twins.

Used with DSX Sim, ecosystem partners including PTC are helping create these simulation-ready assets with computer-aided design to enable SimReady workflows that let builders model infrastructure configurations and evaluate power and cooling decisions before equipment is installed. Operators can validate designs earlier, reduce deployment risk and move faster from planning to construction.

Driving Production Readiness With NVIDIA DSX OS
To help operators turn installed infrastructure into productive capacity, NVIDIA is expanding its modular, open source DSX OS portfolio with three components in developer preview:

NVIDIA Config Manager automates AI factory network configuration.NVIDIA Rack Management Service provides rack-level power, inventory, firmware and switch management.NVIDIA Cluster Readiness Engine runs distributed workloads to validate GPU clusters before production workloads arrive and isolate failures to specific nodes. Together with NVIDIA Infrastructure Controller, NVIDIA AI Cluster Runtime and NVSentinel, these components help operators automate infrastructure lifecycle management, maintain consistent runtime environments and strengthen health validation, fault attribution and recovery.

Cloud partners including Aleria, Cassava, CoreWeave, Crusoe, Firmus, Firebird, G42, GMI Cloud, IREN, Lambda, Nebius, Nscale, Radiant, Sharon AI and Volta are exploring the latest components of NVIDIA DSX OS to automate infrastructure lifecycle management, and improve resiliency and reliability.

Connecting Design, Power and Cooling Across Europe’s AI Factory Ecosystem
NVIDIA’s industrial software, power and cooling partners are advancing Europe’s AI factory buildout with DSX reference designs, lifecycle digital twins and qualified equipment that connect facility infrastructure with accelerated computing.

Schneider Electric has developed power and cooling reference designs for NVIDIA Vera Rubin infrastructure and is working with AVEVA on digital twins spanning infrastructure design, construction and operations. Procore is helping manage AI factory builds with its construction management platform, integrated with DSX Sim. Siemens is using DSX Sim to simulate power, cooling and acoustics, while Dassault Systèmes and Vertiv are developing digital twin models of Vertiv’s OneCore infrastructure, enabling simulation and optimization through model-based systems engineering.
ABB is developing SimReady assets with NVIDIA DSX Sim, enabling engineers to evaluate source-to-rack architectures before construction while advancing 800 VDC development through its newly announced Infinitus Direct Current portfolio.
Partners are also delivering coordinated power and cooling infrastructure aligned with DSX reference designs. Trane Technologies and Eaton recently collaborated with NVIDIA to help boost data center efficiency and cut installation costs with an integrated design built for the NVIDIA Vera Rubin DSX AI Factory Reference Design, bringing together Eaton’s Beam platform and power infrastructure with Trane Continuum cooling and coordinated controls in a grid-to-chip architecture.

Trane Technologies has published seven thermal management system reference designs, including three 250-megawatt DSX-based cooling reference designs to support thermal infrastructure planning at scale.

Through the NVIDIA DSX Ready program, builders can select equipment qualified under applicable DSX categories. Trane Technologies’ LiquidStack GigaModular and Vertiv’s 2.3-megawatt CoolChip — both coolant distribution units — have qualified under their applicable categories, while Hitachi Energy’s battery energy storage system has earned NVIDIA DSX Ready BESS qualification.

For energy supply and grid integration, GE Vernova, Hitachi Energy and Siemens Energy are collaborating with NVIDIA on power infrastructure and digital twin initiatives that connect energy-system engineering and grid planning based on the facility’s requirements. Hitachi Energy is developing an integration between its energy management system and DSX Flex to optimize grid, generation and storage resources with workload demand.

Watch the GTC Berlin keynote from NVIDIA founder and CEO Jensen Huang and explore sessions.

About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in AI and accelerated computing. 

For further information, contact:
Kristin Uchiyama
Corporate Communications
NVIDIA Corporation
[email protected]  

Certain statements in this press release including, but not limited to, statements as to: expectations with respect to growth, performance, availability, and benefits of NVIDIA’s products, services and technologies, and related trends and drivers; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners, and related deployments and timing; expectations with respect to technology developments, and related trends and drivers; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, which are subject to the “safe harbor” created by those sections based on management’s beliefs and assumptions and on information currently available to management and are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing products and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; NVIDIA’s ability to realize the potential benefits of business investments or acquisitions; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its Annual Report on Form 10-K and Quarterly Reports on Form 10-Q. Copies of reports filed with the SEC are posted on NVIDIA’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances. 

Many of the products and features described herein remain in various stages and will be offered on a when-and-if-available basis. The statements above are not intended to be, and should not be interpreted as a commitment, promise, or legal obligation, and the development, release, and timing of any features or functionalities described for our products is subject to change and remains at the sole discretion of NVIDIA. NVIDIA will have no liability for failure to deliver or delay in the delivery of any of the products, features or functions set forth herein.

© 2026 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, and other NVIDIA product and service names are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries and regions. Other company, product, and service names may be trademarks of the respective companies with which they are associated.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/9ff4492c-3cd2-4987-aa36-a96a00eb56b4

News Summary:

Leading global telecom operators are expanding NVIDIA-powered computing across their networks to deliver advanced services closer to people and businesses, improve wireless experience and automate network operations.T-Mobile completes the world’s first AI-RAN call on a commercial network, while BT, Deutsche Telekom and Elisa announce AI-RAN pilots on live networks using Nokia’s CUDA-accelerated anyRAN software on NVIDIA Aerial RAN Computer, and NVIDIA introduces new Aerial RAN Computer configurations for high-capacity sites.Nine EMEA telecom operators are building and expanding NVIDIA-powered infrastructure across centralized and distributed locations.Operators and software partners are adopting NVIDIA Nemotron open models to deliver agentic services and develop agents for autonomous network operations. BERLIN, Oct. 21, 2026 (GLOBE NEWSWIRE) -- GTC Berlin -- NVIDIA today announced that leading global telecom operators are turning their networks into distributed intelligence platforms, adding NVIDIA accelerated computing to centralized data centers, metro sites and cell sites so they can serve models and applications closer to the people, businesses and machines that use them.

T-Mobile has completed the world’s first AI-RAN call on a live network in Bellevue, Washington, with NVIDIA and Nokia. Deutsche Telekom is advancing physical AI for industries, and Orange is introducing new voice intelligence services for enterprises and emergency responders. Elisa has completed Europe’s first field trial of AI-RAN, running voice, mobile data and vision AI together on a single accelerated computing platform over 5G, and BT is preparing live AI-RAN trials in the U.K. Nokia is bringing its anyRAN software on NVIDIA Aerial RAN Computer (ARC) for trials at BT, Deutsche Telekom, Elisa and Orange.

Nine operators across Europe, the Middle East and Africa (EMEA) are building or expanding NVIDIA-powered infrastructure, while Nokia and Cisco are incorporating NVIDIA Nemotron™ open models into the software operators use to run autonomous networks.

“Telecom networks were built to carry the world’s conversations. Now, they will also carry the world’s intelligence,” said Jensen Huang, founder and CEO of NVIDIA. “Leading global operators are turning their land, power and connectivity into a distributed AI infrastructure — bringing intelligence closer to the industries, people and robots that use it. With Nokia, we’re extending accelerated computing into the radio network itself, creating the foundation for AI-native 5G.”

Intelligence is built in five layers: land, power and shell, chips, infrastructure, models and applications. Telecom operators already own sovereign infrastructure at the first layer, with data centers, regional sites and cell sites that have power, fiber and spectrum.

By adding NVIDIA accelerated computing, open models and applications on top, operators are building the full intelligence stack into their networks. At distributed sites, a common converged platform based on the AI-RAN architecture can serve open models, power robotics, voice and agentic applications, and run intelligent 5G software.

Europe’s Leading Telcos Build Distributed Infrastructure
Infrastructure sits at the foundation of telecom’s transition to distributed service platforms.

Deutsche Telekom plans to expand its NVIDIA-powered Industrial AI Cloud, which hosts open models — including NVIDIA Nemotron and Soofi — and serves robotics companies such as Agile Robots. At distributed sites, Deutsche Telekom is piloting AI-RAN trials with Nokia and NVIDIA, and demonstrating NVIDIA ARC to run inference between the device and the network edge.

A GTC Berlin demonstration with Agile Robots shows the approach: on-robot intelligence handles real-time perception and action, a model at the distributed edge supports fine-tuning and coordination across robots, and the central infrastructure provides capacity for larger training workloads.

Orange is hosting open models, including NVIDIA Nemotron, as a managed service on top of its Live Intelligence trusted AI platform, enabling new advanced services for enterprises. At distributed sites, Orange is deploying NVIDIA ARC for voice intelligence applications using Nemotron Speech, demonstrating new services to help emergency and field services teams translate across multiple languages in real time with low latency and reliability.

Elisa has deployed NVIDIA ARC at a distributed network location, running a voice intelligence application that serves as an enterprise assistant, and is using open models to build edge applications.

EMEA telcos are building or expanding NVIDIA-powered infrastructure:

New infrastructure: CRA in the Czech Republic, etisalat in the United Arab Emirates, Silknet in Georgia and TIM in Italy.Expansions: Cassava in Africa, Deutsche Telekom in Germany, Fastweb + Vodafone in Italy, Kazakhtelecom in Central Asia and Orion Telecom in Serbia. AI-RAN Brings Accelerated Computing Into the Radio Network
AI-RAN extends accelerated computing into the radio access network (RAN), turning it into an intelligence workload that runs on the same platform as advanced services, so operators can get more out of their spectrum while serving demand from sites close to users.

Globally, nearly 20 telecom operators have publicly announced AI-RAN collaborations using Nokia anyRAN software and NVIDIA ARC.

T-Mobile recently marked the world’s first AI-RAN call on its commercial network in Bellevue, Washington, running on commercial ARC servers, Nokia’s NVIDIA CUDA-accelerated RAN software and massive multiple-input multiple-output radios, and connected to an existing 5G Standalone core and a commercial smartphone.BT is planning live AI-RAN trials in Birmingham, England, with Nokia and NVIDIA in 2027.Deutsche Telekom has validated Nokia and NVIDIA’s commercial AI-RAN platform in Bonn and Oulu labs, including AI-enhanced uplink channel estimation to improve uplink user throughput, with plans to move to field trials in 2027.Elisa simultaneously ran voice, mobile data and video analytics on the NVIDIA ARC platform, marking a European first in Elisa’s over-the-air field environment using 5G spectrum. The trial clears the way for distributed deployment and commercial AI-RAN services in 2027.Orange is testing Nokia 5G software on NVIDIA ARC, focusing on AI-RAN spectral efficiency improvements and support for edge services in live networks. NVIDIA is introducing two ARC configurations — MGX 2U and MGX 4U — designed for dense, high-capacity intelligence and radio workloads, typically deployed at centralized RAN sites. Powered by NVIDIA RTX PRO™ 6000 Blackwell Server Edition GPUs, the configurations will offer x86 and NVIDIA Vera CPU options. Dell Technologies, Quanta Cloud Technology and Supermicro will offer ARC-ready servers.

Open Models Power Autonomous Network Operations
Leading telcos are using open models and agents to speed progress toward fully autonomous network operations. NVIDIA Nemotron open models and NVIDIA Agent Toolkit software are now integrated into leading partners’ commercial software, powering specialized agents built for telecom network workflows.

Nokia is integrating NVIDIA Nemotron into its Autonomous Networks Suite and using NVIDIA Agent Toolkit software to build and deploy trusted agents that manage operations across fixed, radio, core and transport networks.

Cisco has fine-tuned NVIDIA Nemotron models and integrated them into Crosswork AI, creating a common agentic layer across its Crosswork Network Automation software to manage IP and optical transport networks. The company is also using NVIDIA Agent Toolkit to help telcos operate agents safely.

TCS is working with telcos to fine-tune NVIDIA Nemotron models and use NVIDIA Agent Toolkit to build specialized agents that validate radio-site builds, detect, diagnose and auto-remediate network issues, and deliver multilingual voice experiences. BT is adopting Nemotron to build agents that inspect field-installation photos, detect problems and help reduce repeat site visits.

NTT DATA is extending its NextGenOSS platform with fine-tuned NVIDIA Nemotron models and NVIDIA Agent Toolkit to build agents that detect early network degradation, identify likely root causes and recommend next actions.

Watch the GTC Berlin keynote from Huang and explore sessions.

About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in AI and accelerated computing.

For further information, contact:
Olivia Wright
Corporate Communications
NVIDIA Corporation
[email protected] 

Certain statements in this press release including, but not limited to, statements as to: expectations with respect to growth, performance, availability, and benefits of NVIDIA’s products, services and technologies, and related trends and drivers; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners, and related trials, deployments and timing; expectations with respect to technology developments, and related trends and drivers; expectations with respect to the transformation of telecommunications networks into distributed computing platforms and related benefits; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, which are subject to the “safe harbor” created by those sections based on management’s beliefs and assumptions and on information currently available to management and are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing products and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; NVIDIA’s ability to realize the potential benefits of business investments or acquisitions; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its Annual Report on Form 10-K and Quarterly Reports on Form 10-Q. Copies of reports filed with the SEC are posted on NVIDIA’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

Many of the products and features described herein remain in various stages and will be offered on a when-and-if-available basis. The statements above are not intended to be, and should not be interpreted as a commitment, promise, or legal obligation, and the development, release, and timing of any features or functionalities described for our products is subject to change and remains at the sole discretion of NVIDIA. NVIDIA will have no liability for failure to deliver or delay in the delivery of any of the products, features or functions set forth herein.

© 2026 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, and other NVIDIA product and service names are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries and regions. Other company, product, and service names may be trademarks of the respective companies with which they are associated.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/3e77f346-831f-4576-bbb6-04bfc306e4c3

NVIDIA-Powered Telecom Networks Leading global telecom operators are expanding NVIDIA-powered computing across their networks to del...

News Summary:

Bolt with Lucid, Mercedes-Benz, Volkswagen Commercial Vehicles and Einride are showcasing selected autonomous-mobility use cases on the NVIDIA Hyperion computing platform, demonstrating potential applications for level 3 and level 4 vehicles as well as future robotaxi fleets, with Volvo Cars adopting Hyperion and NVIDIA Alpamayo Stack for safe automated driving.NVIDIA introduces Halos SAFE, a new framework within the NVIDIA Halos safety system, which combines simulation and physical testing to help developers generate measurable, traceable AV safety evidence.NVIDIA announces Alpamayo 2 Edge, Alpamayo Agentic Factory and new Cosmos 3 Nano model variants to help developers build, customize and evaluate autonomous-driving for diverse vehicles, operating conditions and regions.
BERLIN, Oct. 21, 2026 (GLOBE NEWSWIRE) -- GTC Berlin -- NVIDIA today announced that leading automakers in Europe and mobility providers, including Bolt with Lucid, Mercedes-Benz, Volkswagen Commercial Vehicles and Einride, are showcasing selected autonomous-mobility use cases on the NVIDIA Hyperion computing platform, demonstrating potential applications for level 3 and level 4 vehicles as well as future robotaxi fleets.

In addition, Volvo Cars is adopting Hyperion and NVIDIA Alpamayo Stack software for safe automated driving. NVIDIA also introduced new AI and safety technologies to help developers build, validate and deploy autonomous vehicles (AVs) at scale.

Autonomous transportation represents a multitrillion-dollar opportunity, with robotaxis leading the move to commercial level 4 deployment. NVIDIA Hyperion and the NVIDIA Halos full-stack safety system give automakers and mobility providers the computing performance, safety foundation and long-term support to bring AVs and robotaxi fleets to market at scale.

“Robotaxis are the first mass-market application of robotics and physical AI, reinventing how people and goods move,” said Jensen Huang, founder and CEO of NVIDIA. “NVIDIA Hyperion, together with our Halos safety operating system, gives our partners a full-stack robotaxi platform designed to achieve full autonomy and the highest levels of safety, bringing us closer to a future where everything that moves is autonomous.”

Mobility Leaders in Europe Build on NVIDIA Hyperion
Automakers and mobility providers in Europe are pursuing various paths to autonomy, from passenger vehicles and robotaxi fleets to autonomous freight trucks. NVIDIA Hyperion’s modular architecture supports all of these programs, compatible with NVIDIA Alpamayo Stack autonomous driving software as well as partners’ own driving software.

Bolt has selected NVIDIA Alpamayo Stack for its European robotaxi program, beginning with future Lucid vehicles built on Hyperion. Bolt and NVIDIA will adapt the software for European roads and integrate it into vehicles from multiple manufacturers, combining NVIDIA’s driving and safety technologies with Bolt’s fleet-management systems, operations and local market expertise.

Bolt plans to begin gathering real-world driving data to support the development and validation of the autonomous driving technology — subject to regulatory approval — in Madrid in 2027, with Germany being a priority for future deployment as part of a planned European rollout of at least 25,000 level 4-capable future Lucid vehicles built on NVIDIA Hyperion.

At GTC Berlin, Volkswagen Commercial Vehicles is presenting its autonomous ID. Buzz AD vehicle platform with Hyperion to support multiple autonomous-driving systems. Hyperion provides a common computing and sensor architecture designed to simplify integration and validation, helping developers and mobility operators bring robotaxi and commercial transport services to market.

Volvo Cars is combining its industry-leading vehicle safety systems and engineering expertise with Hyperion, Halos OS and Alpamayo Stack to enable future Volvo cars to safely navigate complex real-world environments from door to door.

Mercedes-Benz is extending its partnership with NVIDIA on Hyperion and Alpamayo Stack to support the development of the automaker’s L3 and L4 capabilities. The company also announced that MB.DRIVE ASSIST PRO, developed in partnership with NVIDIA, will soon get approval for urban point-to-point urban driver assistance in Germany, helping drivers navigate journeys through complex city traffic.

Beyond passenger vehicles and robotaxis, Einride is building its next-generation Einride Driver on Hyperion for autonomous freight trucks, using Halos, Alpamayo and NVIDIA Cosmos™ open world models to develop and validate its driving system, while TIER IV and the Technical University of Munich plan to integrate Hyperion to develop and validate systems for autonomous public transportation in Germany.

NVIDIA technology and manufacturing partners are also helping expand the AV ecosystem, with Aptiv, Valeo and Schaeffler building Hyperion-based computing platforms that can be integrated by vehicle manufacturers for L4 AVs and robotaxis.

Scaling Safe Autonomy With NVIDIA Halos
Halos provides the safety foundation for NVIDIA’s AV platform, bringing together AI computing, safety software and validation from development through deployment.

To give developers repeatable ways to evaluate driving behavior and simulation accuracy, NVIDIA today introduced Halos SAFE — the Safety Assurance Framework for Evaluation — with dSPACE, IVEX and TÜV Rheinland collaborating on evaluation workflows. Halos SAFE connects simulation, software- and hardware-in-the-loop evaluation, on-road testing and fleet monitoring through defined scenarios, tests and measurable performance criteria to generate traceable safety evidence that supports deployment.

The Halos SAFE ecosystem also includes JLR, Mercedes-Benz, Volvo Cars, 51Sim, aiMotive, AVL, Deepen AI, Foretellix and Synopsys.

Accelerating AV Development
Developing AVs means teaching AI to handle the diversity of real-world driving, then bringing that intelligence into the vehicle. NVIDIA’s latest models, tools and blueprints help developers prepare driving data, improve models and evaluate performance:

Alpamayo 2 Edge, a 2-billion-parameter reasoning model built on NVIDIA Cosmos 3 Edge’s NVIDIA Nemotron™-based foundation, is optimized for the NVIDIA DRIVE AGX Thor™ platform and designed to run at 10Hz for in-vehicle scene understanding and motion planning.AlpaJudge, a human-calibrated evaluation and reward model, scores driving explanations to assess reasoning quality, filter weak annotations and reduce manual review of training data.Foundation4D labels multicamera video without lidar input, supporting perception-model training and NVIDIA Omniverse™ NuRec scene reconstruction.New Cosmos 3 Nano model variants expand synthetic data generation and closed-loop simulation for autonomous driving through synchronized multiview, multi-camera and lidar generation across diverse driving scenarios.Cosmos Data Factory’s AV dataset-generation blueprint turns driving video and vehicle signals into curated, searchable, labeled data, using synthetic data to expand scenario coverage.Alpamayo Agentic Factory, an open blueprint expected to become available in early 2027, uses AI agents to connect data preparation, model post-training and simulation evaluation, reducing integration work.NVIDIA NIM™ microservices for Alpamayo 1.5 and NuRec Harmonizer deliver both models as optimized inference containers, giving AV reasoning and scene harmonization a simplified deployment path.
Uber and NVIDIA are developing a data factory powered by Cosmos to curate and process data for AV development. The effort is part of a broader partnership spanning AI development infrastructure, Hyperion-based vehicles and Uber’s global ride-hailing network.

Porsche is leading the development of a data flywheel workflow across Volkswagen Group brands through Voxel51, using NVIDIA Cosmos Data Factory and Omniverse NuRec on Microsoft Azure to turn fleet data into datasets and simulations for evaluating autonomous-driving models. This is expected to reduce repeated physical test drives by up to 90% and shorten development cycle duration by up to 85%.

Watch the GTC Berlin keynote from Huang and explore sessions.

About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in AI and accelerated computing.

For further information, contact:
Corporate Communications
NVIDIA Corporation
[email protected]

Certain statements in this press release including, but not limited to, statements as to: expectations with respect to growth, performance, availability, and benefits of NVIDIA’s products, services and technologies, and related trends and drivers; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners, and their plans to develop and deploy autonomous vehicles and robotaxi fleets, and related timing; expectations with respect to technology developments, and related trends and drivers; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, which are subject to the “safe harbor” created by those sections based on management’s beliefs and assumptions and on information currently available to management and are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing products and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; NVIDIA’s ability to realize the potential benefits of business investments or acquisitions; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its Annual Report on Form 10-K and Quarterly Reports on Form 10-Q. Copies of reports filed with the SEC are posted on NVIDIA’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

Many of the products and features described herein remain in various stages and will be offered on a when-and-if-available basis. The statements above are not intended to be, and should not be interpreted as a commitment, promise, or legal obligation, and the development, release, and timing of any features or functionalities described for our products is subject to change and remains at the sole discretion of NVIDIA. NVIDIA will have no liability for failure to deliver or delay in the delivery of any of the products, features or functions set forth herein.

© 2026 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, and other NVIDIA product and service names are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries and regions. Other company, product, and service names may be trademarks of the respective companies with which they are associated.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/6facbac6-d80f-4d4b-b166-891b08cf8ec4

European Mobility Leaders Build on NVIDIA Hyperion NVIDIA today announced that leading automakers in Europe and mobility providers, including Bolt with...

News Summary:

Substrate agreements with IBIDEN, Samsung Electro-Mechanics and Unimicron Technology Corporation will, in aggregate, drive a 2.5x increase in capacity over the next three years.Amkor plans to increase its advanced packaging capacity by more than 300% by the end of 2028.KYEC will build new facilities in the U.S., supported by a $1.1 billion capacity reservation advance from NVIDIA.SPIL is targeting to increase its optical-engine capacity for co-packaged optics by 15x by mid-2027, with aims for another doubling by the end of 2028. BERLIN, Oct. 21, 2026 (GLOBE NEWSWIRE) -- GTC Berlin-- NVIDIA today announced plans with a group of supply chain partners to expand global manufacturing capacity to meet growing demand for its accelerated computing and full-stack AI factory platform.

Working with Amkor Technology, IBIDEN, King Yuan Electronics (KYEC), Samsung Electro-Mechanics, Siliconware Precision Industries (SPIL) and Unimicron Technology Corporation, NVIDIA is enabling new and existing suppliers to expand critical manufacturing capabilities across substrates, advanced packaging, testing and optical engines, strengthening the resiliency and redundancy of NVIDIA’s global supply chain.

“We are in the midst of the largest infrastructure buildout in human history. Demand is extraordinary. Capacity is the constraint,” said Jensen Huang, founder and CEO of NVIDIA. “Our supply chain partners are the world’s best manufacturers. I’m grateful they are expanding capacity around the globe to scale production and help us deliver the AI supercomputing systems powering this new industrial revolution.”

Expanding Substrate Capacity to Support Volume Growth
NVIDIA plans to increase substrate capacity for its products by 2.5x over the next three years. The agreements below will contribute to this capacity expansion, with more underway.

Under an agreement signed and announced earlier this year by IBIDEN, NVIDIA is providing a multibillion-dollar capacity reservation advance to support IBIDEN’s Ono Plant in Japan. The expansion targets capacity reaching 3x current levels at the plant, with additional capacity expected to begin ramping in the first quarter of 2028.

Samsung Electro-Mechanics is joining NVIDIA’s substrate supply chain, bringing immediate capacity from its existing operations in South Korea. The collaboration also supports facility upgrades and new factories in Sejong and Busan, South Korea. By 2028, production allocated to NVIDIA is projected to account for a significant portion of Samsung Electro-Mechanics’ total annual package substrate production capacity.

NVIDIA is supporting Unimicron’s KF substrate manufacturing expansion in Taiwan with a capacity reservation agreement. The expansion is expected to begin adding capacity in the second quarter of 2027 and reach full capacity by mid-2028.

Scaling Advanced Packaging for Next-Generation Platforms
NVIDIA and Amkor plan to expand advanced packaging capacity in South Korea, targeting a greater than 300% increase in interposer wafer capacity by the end of 2028. The planned capacity expansion, alongside Amkor’s development of new manufacturing facilities in South Korea, will support higher production volumes for NVIDIA’s current and next-generation platforms.

Expanding Semiconductor Testing and Strengthening US Manufacturing
NVIDIA expects its total semiconductor testing capacity to double from calendar 2026 to 2027, supported by buildouts in the U.S., Taiwan and Singapore.

NVIDIA’s $1.1 billion capacity reservation advance to KYEC will support new U.S. testing facilities and equipment, with high-volume production targeted for April 2027.

In Singapore, expanded testing operations are expected to begin high-volume production in February 2027.

Creating the Infrastructure for Co-Packaged Optics
NVIDIA and SPIL plan to expand manufacturing capacity in Taiwan for optical engines used in co-packaged optics, supporting the growing connectivity requirements of large-scale computing infrastructure. The expansion targets an increase of 15x by mid-2027, with aims for another doubling by the end of 2028.

About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in AI and accelerated computing.

For further information, contact:
Corporate Communications
NVIDIA Corporation
[email protected]

Certain statements in this press release including, but not limited to, statements as to: expectations with respect to growth, performance, availability, and benefits of NVIDIA’s products, services and technologies, and related trends and drivers; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners; expectations with respect to technology developments, and related trends and drivers; expectations with respect to AI infrastructure demand and buildout, manufacturing capacity expansion, production volumes and supply chain resiliency, and related timing and benefits; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, which are subject to the “safe harbor” created by those sections based on management’s beliefs and assumptions and on information currently available to management and are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing products and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; NVIDIA’s ability to realize the potential benefits of business investments or acquisitions; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its Annual Report on Form 10-K and Quarterly Reports on Form 10-Q. Copies of reports filed with the SEC are posted on NVIDIA’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

© 2026 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, and other NVIDIA product and service names are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries and regions. Other company, product, and service names may be trademarks of the respective companies with which they are associated.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/081c8dd7-3f9f-4c8f-9da1-d699dd5750ee

NVIDIA and Supply Chain Partners
NVIDIA today announced plans with a group of supply chain partners to expand global manufacturing ca...

Nvidia CEO Jensen Huang unveiled plans for modular, quickly-deployed data centers to begin AI work while permanent infrastructure is being built. These component stocks could be winners.

NVIDIA supplies the simulation, world models and agent skills. Nebius runs them on its Physical AI Workbench. Sereact's Cortex is the robot brain they train. The initial rollout targets Zalando’s returns handling at CEVA Logistics’ fulfillment center—one of the most variable processes in eCommerce logistics.

BERLIN, Oct. 21, 2026 (GLOBE NEWSWIRE) -- Sereact, NVIDIA, Nebius, CEVA Logistics and Zalando today announced a closed training loop for Cortex, Sereact's robot brain. The first deployment is Zalando returns handling in selected CEVA Logistics fulfillment centers. NVIDIA provides Isaac Sim, Isaac Lab, Cosmos and its Physical AI Data Factory skills. Operated through the company’s EU data centers, Nebius runs them on the Physical AI Workbench, its open-source framework for physical AI. Sereact brings Cortex and the episodes its robots record on the returns line. What a robot gets wrong on Monday can come back as a tested policy update within days, where it used to take weeks.

Returns are among the hardest warehouse processes to automate. Each item arrives in whatever state the customer left it: refolded or crumpled, in its polybag or loose, with or without tags. A robot has to pick it, identify it, check its condition and sort it, while the assortment changes every season. Cortex learns from real picks, but real picks only cover items that have already passed through a station. Improving the policy meant collecting episodes on site, retraining, testing on the robot and starting over. Each cycle took weeks and covered only the cases a team could stage by hand.

The new loop runs as one workflow on one shared data layer. Episodes from the returns stations, video plus kinematics, land in Nebius object storage. NVIDIA Isaac Lab turns them into thousands of simulated variants, and NVIDIA Cosmos re-renders those across garment states, packaging, materials and lighting. The versioned dataset post-trains Cortex on NVIDIA Blackwell GPUs. The new policy is scored on held-out variants against a threshold Sereact sets. A policy that passes goes to the stations for a real-world test. One that fails triggers targeted variants for the cases it missed, and the loop trains again.

An AI agent builds and runs the loop. NVIDIA's Physical AI Data Factory skills are open, versioned instruction files that a coding agent reads directly, and Nebius adds Workbench skills for simulation, training, evaluation and the gate. The agent previews GPU cost before each run, launches the stages, checks the gate and, after a failed run, decides which cases to augment. Sereact engineers state the goal, such as "validate the policy for the autumn assortment", and approve any run above a set cost limit.

Sereact brings Cortex, its vision-language-action model and robot brain, along with the dual-arm returns stations and the real episodes they record.NVIDIA brings Isaac Sim and Isaac Lab for simulation, Cosmos world foundation models for re-rendering, and the Physical AI Data Factory skills that let an agent operate the loop.Nebius brings its open-source framework, Physical AI Workbench, with shared object storage, CLI, SDK and format contracts at every handoff, and the GPUs behind it: RTX-class for simulation and Blackwell for training, all operated through EU data centers.CEVA Logistics manages eCommerce logistics operations, including returns handling, for Zalando and hosts the Sereact stations in its fulfillment centers.Zalando provides the use case. Its returns are where every new policy has to prove itself.
The closed-loop pipeline is available today as a Workbench reference architecture, with the NVIDIA Physical AI Data Factory skills pre-installed, for any robotics team on Nebius AI cloud. It runs in Nebius EU regions, and customers pay only for the compute and storage they use.

About Sereact

Sereact builds physical AI for warehouses and manufacturing. Its Cortex brain runs across single-arm picking cells, dual-arm returns stations, humanoid robots, and Sereact Lens, a 3D perception system for inventory and quality control. Founded in 2021, headquartered in Stuttgart. Customers include IKEA, Arvato, alza.cz, Flaschenpost, Sonapar, Monta part of DHL, Daimler Truck, Mercedes-Benz, BMW, MS Direct, Paxon part of Bnode, DeltiLog, Rohlik Group, and Austrian Post. With Zalando's participation, Sereact has now raised over $145 million to date.

About NVIDIA

NVIDIA (NASDAQ: NVDA) is the pioneer of accelerated computing and a driving force behind the modern AI era, providing the platforms used across industries from cloud computing to robotics. Through its Isaac platform, NVIDIA supports robotics developers with simulation, training, and deployment tools — including NVIDIA Isaac Sim, which enables companies like Sereact to develop and validate robots in physically accurate virtual environments before deploying them in real-world operations.

About Nebius

Nebius, the AI cloud company, is building the full-stack platform for developers and companies to take charge of their AI future — from data and model training to production deployment. Founded on deep in-house technological expertise and operating at scale with a rapidly expanding global footprint, Nebius serves startups and enterprises building AI products, agents and services worldwide. Nebius is listed on Nasdaq (NASDAQ: NBIS) and headquartered in Amsterdam.

About CEVA Logistics

CEVA Logistics, a world leader in third-party logistics, provides global supply chain solutions to connect people, products and providers all around the world. Headquartered in Marseille, France, CEVA Logistics offers a broad range of end-to-end, customized solutions in contract logistics and air, ocean, ground and finished vehicle transport in more than 170 countries worldwide thanks to its approximately 110,000 employees at more than 1,700 facilities. With 2025 revenue of US$18.3 billion, CEVA Logistics is part of the CMA CGM Group, a global player in sea, land, air and logistics solutions.

For more information, please visit www.cevalogistics.com. 

About Zalando

Founded in Berlin in 2008, Zalando is the leading European technology platform for fashion and lifestyle. The Zalando group connects 62 million active customers with more than 7,000 brands across 29 markets. Our operations are built on a unique AI-powered data and infrastructure platform. For our customers, our multi-app approach - comprising Zalando, ABOUT YOU, and Lounge by Zalando - delivers an inspiring, highly personalised shopping experience, serving different customers with different needs. For our partners, we are building the operating system for e-commerce. Through ZEOS, Tradebyte, and SCAYLE, we open our logistics, software, and service capabilities to brands and retailers, enabling them to seamlessly scale their businesses across borders.

For further information, please visit: corporate.zalando.com/en

Press contacts
Sereact: [email protected]        

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/b04b7628-15d9-4304-8ce6-54a40955878b

Sereact, Zalando and CEVA Logistics run AI-powered, automated returns handling Dual-arm robotic systems in live operations, marking the first milestone in a strategic partnership ...

Improve network economics with higher spectral efficiency using AI-RAN platform for 5G today, with software upgradeable path that protects infrastructure investment
Unlock AI monetization by enabling low-latency, critical AI services, enterprise edge inferencing, and practical physical AI applications
Deploy an integrated AI-RAN stack combining Supermicro infrastructure, NVIDIA accelerated computing, and Nokia RAN software
, /PRNewswire/ -- Super Micro Computer, Inc. (NASDAQ: SMCI), an AI, Enterprise, Storage, and 5G/Edge Total IT Solution Provider featuring Data Center Building Block Solutions® (DCBBS), is now working with Nokia to deploy Artificial Intelligence-Radio Access Networks (AI-RAN) from distributed cell sites to centralized network hubs. The solution combines Nokia's RAN technology and network expertise with the NVIDIA Aerial RAN Computer platform, supported by Supermicro's AI-optimized infrastructure. By bringing accelerated compute closer to the access network, it enables radio and AI workloads to run on shared infrastructure, supporting applications which require proximity and predictable service levels-including voice AI, vision AI, physical AI, and internal uses such as autonomous network operations.

AI RAN Solutions for the Network Edge

"AI-RAN is redefining networks for AI, turning mobile infrastructure into a shared foundation for connectivity, AI for RAN, AI on RAN, and broader distributed AI services," says Charles Liang, president and CEO, Supermicro. "Together with Nokia and NVIDIA, we are bringing accelerated computing to every layer of the network, enabling operators to maximize infrastructure efficiency, deploy new AI services, and prepare for AI-native 6G. Our DCBBS approach delivers the flexibility and performance to accelerate deployment and turn network infrastructure into a platform for innovation." For more information on the latest AI-RAN solutions, click here.

Embedding accelerated compute into the RAN enables operators to run network and AI workloads on the same infrastructure, improving spectral efficiency, automating network operations, and optimizing energy use while creating new opportunities for edge AI services. Combining Supermicro systems with Nokia's RAN technology and software, the NVIDIA Aerial RAN Computer platform provides modular, right-sized CPU and GPU configurations for deployment from cell sites to MSO and aggregation locations, with NVIDIA ConnectX technology providing high-speed, software-defined networking. Together, these capabilities give operators a flexible foundation for low-latency AI applications today and a software-driven evolution path towards 6G networks.

"AI-RAN represents an important step towards more intelligent and adaptable mobile networks," said Emma Falck, President of Mobile Infrastructure at Nokia. "By combining Nokia's leadership in radio networks with NVIDIA accelerated computing and Supermicro's flexible infrastructure, we are giving operators a practical way to bring RAN and AI workloads together across their networks. This will help operators improve network performance and automation today while creating a foundation for new edge AI services and AI-native 6G."

"AI-RAN brings together networking, accelerated computing, and intelligence to help operators make better use of their infrastructure while opening new opportunities for edge AI services," said Soma Velayutham, VP of Telecoms, NVIDIA. "Nokia and Supermicro are helping operators deploy NVIDIA Aerial RAN Computer solutions across diverse network environments, from distributed cell sites to centralized RAN locations, with the flexibility to scale intelligence capabilities as demand grows."

Supermicro's modular, right-sized systems for NVIDIA ARC span distributed cell sites, aggregation locations, and core hubs, enabling operators to precisely deploy AI capacity where it is needed.

Distributed cell sites: The ARC MGX 2U Short-depth platform brings inference closer to radios, users, and applications. NVIDIA MGX is a modular reference architecture for accelerated computing, helping system builders design future-compatible systems faster, reducing costs, accelerating time to market, and improving ROI. Supermicro's dual-node ARC-Pro combines an NVIDIA Grace C1 CPU and NVIDIA RTX PRO 4500 Blackwell Server Edition GPU per node in a 429 mm chassis, delivering up to 1.6 PFLOPS of FP4 AI performance. For edge networking functions such as Service Management and Orchestration, the ARC-Compact delivers high efficiency compute performance in a 1U, short-depth form factor.
Centralized MSO and aggregation sites: The ARC MGX 2U supports higher-throughput, coordinated inference. This system class comes with a choice between dual NVIDIA Vera CPUs or dual x86 processors and two NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs. These systems support multi-cell workloads, including coordinated scheduling and beamforming, as well as voice, vision, and physical AI.
Core network hubs: The ARC MGX 4U provides high-density, air-cooled inference with up to eight NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs. Supermicro's 4U AI servers deliver dual x86 CPUs and up to 6 TB of DDR5 memory to support large-scale inference and model update workloads. This configuration comes with the option for an NVIDIA ConnectX-8 switchboard, providing PCIe Gen 6 for even faster GPU-GPU interconnectivity.
Supermicro's servers for NVIDIA ARC are generally available now. The ARC MGX 2U with dual Vera processor is on display on Supermicro's booth at NVIDIA GTC Berlin, October 20–22, 2026, and will be available later this year. The 2U ARC-Pro is planned for customer testing later this year, with general availability in the first half of 2027.

About Super Micro Computer, Inc.

Supermicro (NASDAQ: SMCI) is a global leader in Application-Optimized Total IT Solutions. Founded and operating in San Jose, California, Supermicro is committed to delivering first-to-market innovation for Enterprise, Cloud, AI, and 5G Telco/Edge IT Infrastructure. We are a Total IT Solutions provider with server, AI, storage, IoT, switch systems, software, and support services. Supermicro's motherboard, power, and chassis design expertise further enables our development and production, enabling next-generation innovation from cloud to edge for our global customers. Our products are designed and manufactured in-house (in the US, Taiwan, and the Netherlands), leveraging global operations for scale and efficiency and optimized to improve TCO and reduce environmental impact (Green Computing). The award-winning portfolio of Server Building Block Solutions® allows customers to optimize for their exact workload and application by selecting from a broad family of systems built from our flexible and reusable building blocks that support a comprehensive set of form factors, processors, memory, GPUs, storage, networking, power, and cooling solutions (air-conditioned, free air cooling or liquid cooling).

Supermicro, Server Building Block Solutions, and We Keep IT Green are trademarks and/or registered trademarks of Super Micro Computer, Inc.

All other brands, names, and trademarks are the property of their respective owners.

SOURCE Super Micro Computer, Inc.

Going back to work at 68 scrambles a retirement plan built around drawing down savings, and the paycheck creates decisions most financial guides never cover. Getting the order right matters more than picking the funds.

This post may contain links from our sponsors and affiliates, and Flywheel Publishing may receive compensation for actions taken through them.

You retired, settled into a withdrawal routine, and then went back to work. Maybe it was the money, maybe the structure, maybe plain restlessness. Now, at 68, a paycheck lands again, even though your financial plan was built for life without one. Put the new income to work in the right order before choosing funds. After that, three ETFs can handle what’s left over: Schwab U.S. Large-Cap Growth ETF (NYSEARCA:SCHG) for growth, Avantis International Equity ETF (NYSEARCA:AVDE) for stocks outside the U.S., and Avantis Core Fixed Income ETF (NYSEARCA:AVIG) for bond income.

Let the Paycheck Replace Your Portfolio Withdrawals If you’ve been selling investments to cover living costs, the paycheck’s first job is to end those sales. Every month earned income pays the bills; your portfolio sits untouched and keeps compounding. You don’t need to buy anything to capture this benefit, and for many people who unretire, it is the biggest benefit.

Your Retirement Account Contributions Can Restart Many retirees assume their contribution years ended with their last job. The IRS notes in Publication 590-A that contributions to a traditional IRA require taxable compensation, and for tax years after 2019, there is no age limit on making them. The IRS counts wages, salaries, tips, professional fees, bonuses, and net self-employment earnings as compensation. If your new employer offers a workplace retirement plan, you may be able to participate as well, so ask HR about eligibility.

Expect the Tax Side Effects A paycheck raises your total income. That can increase how much of your Social Security benefit is taxable. If you sit near the thresholds, it can also raise the income-related surcharge on Medicare premiums, which is set using a prior year’s tax return. Build both into your planning before the first tax bill arrives. (We mapped out the four tax traps that catch people who unretire in a free semi-retirement guide: Retire Twice.)

SCHG Puts Surplus Dollars Behind America’s Biggest Growth Companies Once withdrawals stop and contributions resume, the leftover money needs a job. SCHG, a passive Schwab fund launched in 2009, tracks the Dow Jones U.S. Large-Cap Growth Total Stock Market Index and held about $61.1 billion in net assets as of May 31, 2026.

Know what you own. The fund leans on a relatively small group of very large companies. NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) alone made up 11.01% of assets in that filing, followed by Apple (NASDAQ:AAPL) at 9.83%, with other mega-cap tech names close behind. That concentration helped drive a 450.3% gain over ten years and 11.4% over the past year. It also cost the fund 4.16% in the week ending October 16. The quarterly dividend is small — $0.0371 per share in September — so SCHG’s job is growth. Income comes from elsewhere.

AVDE Takes Your Stock Money Beyond U.S. Borders AVDE, from Avantis Investors, owns developed-market stocks outside the U.S. Its managers actively tilt the portfolio toward companies with lower valuations and higher profitability, and toward smaller companies, so the fund holds more of those stocks than a simple size-weighted index would. The May 2026 filing shows holdings across Canada, the United Kingdom, Japan, Switzerland, France, Germany, and other markets, heavy in banks, energy, mining, and health care. The largest positions visible in that filing each sit below 1% of assets, which offsets SCHG’s tech concentration.

Net assets stood at about $16.9 billion, and the fund returned 17.04% over the past year and 62.85% over five years. Distributions follow a semi-annual schedule and swing widely in size: $1.1657 per share in June, then $0.3251 in September.

AVIG Adds Monthly Income From a Broad Bond Portfolio AVIG is an actively managed bond fund. Its portfolio combines government-backed mortgage securities from Ginnie Mae and Fannie Mae with corporate bonds from insurers, banks, utilities, and industrial companies. It held about $1.87 billion in net assets as of May 31.

This fund distributes monthly. The October distribution came to $0.1514 per share, and the trailing 12-month total reached $1.7806 per share, though amounts change month to month. With the 10-year Treasury yield at 5.10% as of October 15, bond income matters again for your plan.

Understand one structural point. A bond fund holds bonds, but the fund itself never matures, so no date exists when your original investment comes back to you. Its price moves with interest rates, and its price performance shows a 1.96% decline over the past year.

Trade-Offs to Weigh Before the First Deposit Each fund has a real cost. SCHG’s concentration means a rough stretch for a handful of tech giants hits the whole fund. AVDE adds currency swings and lumpy payouts. AVIG tends to fall when rates rise. And a paycheck at 68 may end sooner than you expect, so keep enough cash outside these funds that you never have to sell during a downturn.

The order still works in your favor: stop the withdrawals, reopen your retirement accounts, then send the surplus to growth, international stocks, and bonds. SCHG, AVDE, and AVIG each cover one of those jobs, which makes them a reasonable set to research for money you never expected to earn again.

Contact [email protected] for any questions or corrections.

Exclusive

By

You're currently following this author!
Click to unsubscribe from email alerts.

Amazon CEO Andy Jassy

David Paul Morris/Bloomberg via Getty Images

Amazon is racing to secure AI hardware earlier than before, even as data center power shortages leave some GPU systems waiting in warehouses.

Under a new Early Rack Receipt process, AWS expected to receive roughly $5 billion in Nvidia's GB300 server racks at US facilities before final deployment, according to August internal emails reviewed by Business Insider. The company projected roughly $3 billion more in GB300 racks each month "for the foreseeable future," one of the emails said.

Some AWS sites had room for more racks but not enough available power to turn them on, people familiar with the effort said, leaving finished equipment to be staged at intermediary warehouses until the facilities were ready.

At least one AWS team did not have "a clear forecasted path" for getting the incoming racks into data centers at the time, according to one of the emails.

Dark GPUsA lack of new electricity capacity is one of several bottlenecks slowing the buildout of some AI data centers. This has led to a phenomenon known as dark GPUs, where AI chips and servers are purchased but can sit idle due to power supply issues or other challenges. (Dark GPUs can also refer to system design flaws that mean this gear isn't fully used after being plugged in).

This is partly why financial pressure is mounting on big data center projects. Money must be spent upfront to secure supplies of Nvidia GPUs and other valuable AI components. But if some data centers aren't ready to run, those early investments can tie up huge amounts of cash. Debt financing can fill in the gaps, but the market has become less willing to lend against some of these projects lately.

Trade-offAmazon's early-rack program is one piece of the cloud leader's broader AI buildout, which is putting new pressure on its cash flow, as Business Insider exclusively reported this week. Amazon expects roughly $220 billion in capital expenditures this year — more than any Big Tech peer. Its free-cash-flow turned negative last quarter for the first time since 2023, and could stay negative for a while.

For AWS, the trade-off is securing scarce GPU racks before competitors do, even if some data centers are not yet ready to turn them on. But taking ownership earlier can tie up billions in equipment before it starts generating cloud revenue.

Previously, AWS took ownership of a finished rack only upon delivery to a data center, according to internal documents. Under the new approach, it can pay for and record certain racks earlier in the supply chain.

An Amazon spokesperson said the company routinely stages finished hardware near deployment sites so it can install it once capacity becomes available, calling the practice "best business practice." The spokesperson added that Amazon has long-established systems for tracking infrastructure assets and disputed that the broader company lacked a path for getting racks into data centers.

Amazon CEO Andy Jassy previously said the company has a "clear line of sight" to strong returns from its AI investments, calling the technology a "once in a lifetime opportunity."

"We've been through this cycle with the first big AWS growth wave, and liked the results," Jassy wrote in Amazon's annual shareholder letter. "We expect to feel similarly about this next wave."

Have a tip? Contact this reporter via email at [email protected] or Signal, Telegram, or WhatsApp at 650-942-3061. Use a personal email address, a nonwork WiFi network, and a nonwork device; here's our guide to sharing information securely.

Read next

Business Insider tells the innovative stories you want to know

Business Insider tells the innovative stories you want to know

Business Insider tells the innovative stories you want to know

Business Insider tells the innovative stories you want to know

Eugene Kim

You're currently following this author!
Click to unsubscribe from email alerts.

Eugene is Business Insider’s Chief Tech Correspondent, where he leads coverage of Amazon. His reporting spans the company’s retail and logistics operations to AWS, Alexa, and its internal culture.Previously, he worked at CNBC, Fortune Magazine Korea, and Japan's Yomiuri Shimbun. He holds degrees from NYU and Columbia University’s Graduate School of Journalism.In 2022, Eugene reported on internal documents indicating that Amazon allegedly used deceptive tactics to enroll customers in Prime and made cancellation difficult. The Federal Trade Commission sued Amazon the following year, citing his reporting. The case ended in a record $2.5 billion settlement in 2025.His work has received multiple honors, including the SF Press Club’s Bay Area Journalism Award and SPJ NorCal’s Excellence in Journalism Award.Eugene lives in the Bay Area. Contact him via email at [email protected], or Signal, Telegram, or WhatsApp at 650-942-3061. Use a personal email address, a nonwork WiFi network, and a nonwork device; here's our guide to sharing information securely.

Amazon

Data Centers

AWS

More

Cloud Computing

AI Insider

Exclusive

Anthropic, the company behind Claude, is reportedly in talks with the British neocloud provider Nscale to expand an already massive compute deal, adding roughly $45 billion in contract value as both companies prepare to go public in the coming months.

Anthropic's Nscale deal could reach $90 billionCNBC reported this morning that the frontier AI lab is in talks to rent computing capacity in a second building at Monarch, Nscale's data center campus in West Virginia. The deal would see Anthropic tap an additional 460 megawatts of compute capacity from Nvidia's latest Vera Rubin chips and would provide the company a right of first refusal on a planned third Monarch building.

Image source: Getty Images.

While the deal has not closed, the proposed agreement would bring Anthropic's total Nscale commitment to roughly $90 billion.

Nscale's growth comes with major customer risksBacked by Nvidia, Nscale is a rapidly growing "neocloud" -- essentially a smaller, leaner, AI-focused version of a traditional hyperscaler. It filed for a U.S. IPO in September.

Of course, that growth comes with a couple of pretty substantial asterisks. Just two companies account for roughly 85% of the company's contract value: Microsoft and Anthropic. That is an extreme level of customer concentration.

And Microsoft recently walked away from a planned Nscale data center in Loughton, England, after power connection delays pushed expected electricity availability into the 2030s. Microsoft reassured investors that the trouble was contained to the specific site and its other commitments remained intact, but it's a stark reminder of just how fragile Nscale's position is and how little leverage it has with the much bigger fish it relies on.

Anthropic's IPO puts its spending under scrutinyThe proposed expansion also comes as Anthropic prepares for what could be the largest initial public offering (IPO) in history. Potentially bigger than the recent record-setting SpaceX (SPCX -0.11%) IPO. Anthropic is reportedly targeting a November listing with a valuation between $1.5 trillion and $2 trillion, although a firm date hasn't been set.

SPCX Space Exploration Technologies$147.79-$0.17 (-0.11%)

NASDAQ · As of 4:00 PM ET 10/20/26

According to Reuters, which reviewed Anthropic's draft IPO prospectus, revenue reached roughly $4.6 billion in 2025, about 12 times its 2024 level, but Q3 sales were recently reported to have reached $16.8 billion, up 45% from the previous quarter.

Of course, it takes a lot of capital to scale a business like this, and delivering that growth is expensive. Anthropic spent $7.33 billion on computing and infrastructure in 2025 and recorded an operating loss of more than $8 billion. Over the next decade, Anthropic is committed to spending over $500 billion on deals just like this one.

The company has said it reached positive adjusted profit in the second quarter. That's an encouraging sign, but until its full, audited financials are released, I would take that claim with a major grain of salt. What exactly "adjusted" means is crucial.

The Nscale expansion is worth paying attention to. It's a big potential contract that would provide the computing power Anthropic needs to grow. It also adds another enormous commitment to an already enormous list of commitments Anthropic has to fund somehow.

Four planned startup investments sit within a broader European commitment approaching $10 billion.

Summary

The German initiative expands potential industrial customers without establishing a new chip-order total.

Nvidia, the AI computing supplier NVDA, targets Germany's industrial businesses as its next source of AI demand; shares traded at $215.25, down 0.85%, at 8:23 a.m. ET in October 20 premarket trading. The Associated Press reported that CEO Jensen Huang urged manufacturers to put their engineering expertise and factory data to work with AI. The investor pitch is straightforward: more industrial applications could mean more demand for Nvidia's computing systems. Turning that pitch into orders is the real test.

Nvidia's October 19 announcement detailed a declaration of intent with Germany's government to advance physical AI, alongside planned investments in Agile Robots, Avelios Medical, Mirelo and Reflex Aerospace. Those investments sit within a broader European commitment approaching $10 billion across businesses, universities and research institutions. That figure covers Europe, rather than Germany alone, and the company did not disclose individual investment amounts. The initiative opens doors across robotics, healthcare, audio generation and satellites. It does not establish how much revenue will follow.

The GF Score graphic shows a strong business with a valuation question: Nvidia scores 95 out of 100, with profitability and growth leading while GF Value trails the other categories. That gap suggests business quality deserves more confidence than the entry price. Germany's industrial push gives Nvidia another potential growth avenue, but investors still need evidence of customer spending, deployed systems and recurring workloads. A bigger ecosystem can support future sales. The commercial proof comes when customers pay.

Disclosures
I/we have no positions in any stocks mentioned, and have no plans to buy any new positions in the stocks mentioned within the next 72 hours.

Click for the complete disclosure