GPU Infrastructure

Elon Musk warned that more than 200 ‘neocloud’ providers could die or consolidate as debt markets shut out companies without revenue independent of AI data centers, while Bloomberg questioned his claim that SpaceX has closed a $40bn debt deal.

After a severe vulnerability was found in PHP, cybersecurity leaders warned that AI will expose deeper weaknesses in internet infrastructure and accelerate both the discovery and exploitation of flaws.

Researchers introduce modded-nanoRT, the first speedrun leaderboard for Relational Transformers, where the task is fixed, the stack is open, and entries are ranked by wall-clock time to a quality target on a single GPU. Their opening recipe combines typed trilinear attention with Muon and SIGReg, reaching the target in 305.63 seconds on one NVIDIA H200 — 8.11x faster than the reference implementation — and winning 13 of 15 pairs outside the development database.

Kazakhstan's AI ecosystem is shifting from infrastructure planning to real-world deployment across the full AI stack, from compute to models to applications. Kazakhtelecom has already deployed 400 NVIDIA H200 and 480 NVIDIA B300 GPUs in Astana and Almaty, with plans for more than 1,000 additional GPUs in the Data Center Valley and over 1,000 Vera Rubin GPUs in the Ekibastuz region next year. Meanwhile, inDrive and Pony.ai are exploring robotaxi services in the country.

AI-related stocks fell sharply on Thursday, dragging major global indexes lower amid concerns over datacenter and chip costs, while worries about the war with Iran pushed oil prices to their highest levels since May. The S&P 500 dropped 1.2% for its worst day since July and the Nasdaq composite tumbled 2.6%, though the tech weakness masked broader strength in the US market, where most stocks rose and the Dow Jones Industrial Average added 11 points.

AWS announced the general availability of training sessions within Amazon SageMaker AI serverless model customization. Users write and coordinate their own post-training loop, including custom loss functions, reward signals, and multi-turn reinforcement learning, while SageMaker AI handles GPU allocation, distributed execution, fault recovery, and checkpoint storage. The feature supports gpt-oss-20b, gemma-4-31B-it, Qwen3.6-27B, and Qwen3.8-27B, and billing is based on tokens processed.

Amazon SageMaker AI introduces training session APIs that let developers write custom LLM training loops (SFT, RL, or custom objectives) in Python while the service manages GPU infrastructure. The APIs provide operations like forward_backward(), optim_step(), and sample(), are billed per token, and come with a cookbook of SFT and RL examples.

In this interview, Modal CEO Erik Bernhardsson explains how the company pools demand to offer elastic GPU capacity, now serving over $1 billion annualized run rate and having raised a $750 million Series D at a $16 billion valuation. He discusses why GPU demand isn't rectangular, the unexpected growth of sandboxes, and fast startup as an infrastructure feature.

After a $750M Series D at a $16B valuation, Modal CEO Erik Bernhardsson joins Latent Space to explain how the company turns fixed 'rectangular' GPU contracts into elastic capacity, how sandboxes unexpectedly grew to about a third of revenue, and the economics and engineering culture behind AI infrastructure.

Paris-based voice AI company Gradium, spun out of Kyutai, has open-sourced Phonon, a family of on-device text-to-speech models. English Phonon 31m has 31M parameters and ships as a 64.5 MB file under Apache 2.0, requiring no cloud calls, GPU, or per-character billing. Gradium's evaluations report 1.70% WER on a hard sentence set versus 3.50% for Kokoro, and about 7 ms to first audio on a laptop CPU.

Teams deploying custom text-to-speech models on Amazon SageMaker AI often guess at autoscaling thresholds, and a wrong guess either wastes GPU spend or breaches a latency SLO. This post deploys Kokoro-82M as a custom container and derives a measured autoscaling policy from two live-endpoint measurements, Q_max and T_total, instead of guesswork.

Federal disclosures show that Anthropic, OpenAI, and Nvidia each posted their highest-spending lobbying quarter between July and September, with Nvidia leading at $2.2 million, followed by Anthropic at $2.1 million and OpenAI at $1.5 million. The sums are modest next to Microsoft and Google, but signal that the AI firms see policy shaping as increasingly important.

NVIDIA has launched Minerva, an AIOps platform that unifies telemetry from infrastructure and AI workloads and applies purpose-built AI models to surface timely, actionable insights, helping teams detect problems earlier and keep AI factories productive. IREN is among the early users, with Aolani, Bitdeer AI, IBM, Jio, Lambda, Quake AI and Tesla also planning deployments and Dell Technologies, Lenovo and Supermicro offering it in their AI factory operations portfolios.

Call of Duty: Modern Warfare 4 launches day-one on GeForce NOW with its campaign, multiplayer, and DMZ extraction mode, while Ultimate members gain ray-traced visuals via RTX 5080-class cloud performance. Fire TV Stick users can now buy memberships directly through Amazon, and six games join the library, including FINAL FANTASY RESONANCE and The Elder Scrolls Online’s new season.

Modal launches Spindle, an open-source, Tinker-compatible training server that runs in your own Modal workspace. It lets teams pay for GPU time instead of tokens and customize the models and features they train, with deployment via a single command.

At GTC Berlin, European banks, payment companies and financial data providers showcased production-scale AI built on NVIDIA accelerated computing, open weight models and their own infrastructure. Revolut is rebuilding its stack on the PRAGMA foundation model, while Starling Bank, Lloyds, bunq, NatWest, Santander, LSEG, HSBC and Stripe reported gains in sovereign cloud training, transaction modeling, agentic assistants, speech recognition and fraud detection.

NVIDIA's blog details how European retailers are applying open models and physical intelligence: Shopify post-trained Nemotron to cut inference costs 90% and deliver 7x faster responses, Zooplus reached 86% search accuracy in a production-ready prototype, Otto Group simulates its largest German fulfillment center in Omniverse, and Nebius showcased three retail blueprints at GTC Berlin.

This tutorial walks through using NVIDIA Nsight Python, an open-source Python interface to NVIDIA's kernel profilers, to profile GPU kernels directly in Python. By marking code regions with nsight.annotate and decorating benchmark functions with nsight.analyze.kernel, developers receive a pandas DataFrame of hardware metrics per annotation, configuration, and run instead of digging through Nsight Compute command-line reports. The walkthrough runs on a free Colab T4 and covers installation, a first kernel profile, how many runs a measurement needs, cache and clock control, matrix-size sweeps in fp32 and fp16, using hardware counters to distinguish compute-bound from memory-bound work, measuring kernel fusion, and comparing the experimental CUPTI backend with Nsight Compute.

GPUs power today's most advanced AI workloads, from cutting-edge language models...

Every enterprise company is currently trying to figure out how to have its AI tools work with its data. Meanwhile, The post Nvidia bets open models can give enterprise AI agents the context they’re missing appeared first on The New Stack.

Nvidia wants new AI capacity to show up at the data center fully built. At its GTC Berlin conference on The post Nvidia wants AI factories built in real factories appeared first on The New Stack.

At GTC Berlin, NVIDIA is showcasing its full lineup of local AI hardware. RTX Spark, which launched last week, powers personal agents on Windows PCs; DGX Spark supports developers building and scaling applications on Linux; and DGX Station serves enterprise teams running frontier workloads on Linux, with a Windows version arriving in December. Announcements include: […]

General availability of the instances is coming next month, with planned expansion of availability to Europe — bringing an integrated platform for training, inference and large-scale reinforcement learning to cloud customers. A5X instances bring together NVIDIA Vera Rubin NVL72, NVIDIA ConnectX-9 SuperNICs, Google Cloud Virgo Network and Google Cloud’s fourth-generation advanced liquid-cooling technology for demanding […]

Demand from AI-natives is pulling the European AI cloud ecosystem forward faster than ever. Developers need compute closer to their data, open models they can customize and serve at scale, and full-stack infrastructure that is secure by design. NVIDIA Cloud Partners across Europe, the Nordics, Africa, and Central Asia are expanding regional compute capacity for […]

To increase productivity, accelerate innovation and create new opportunities for economic growth, Europe’s industrial leaders are tapping NVIDIA CUDA-X and Omniverse libraries, as well as NVIDIA Cosmos and Nemotron open models, across the engineering and manufacturing lifecycle. Bringing those capabilities together on the factory floor, the NVIDIA Factory Operations Blueprint (FOX) is now available in […]

NVIDIA cuDSS, launched today in general availability, is an NVIDIA CUDA-X library that shifts a critical part of engineering and scientific simulations onto GPUs. Complex engineering feats — from advanced chips to aircraft to industrial systems —– depend on simulation to predict how designs will perform before they’re built. As designs become more complex, simulations […]

NVIDIA builds tools to enable safe agents across the stack. The NVIDIA OpenShell Reference Architecture, announced today, is part of NVIDIA’s growing portfolio of technologies that enables organizations to safely deploy agents at scale. NVIDIA Confidential Computing is the infrastructure layer that protects the models and data those agents depend on while running. Today, NVIDIA […]

Agents are only as useful as what they know, and only as trustworthy as the boundaries they run within. Leading enterprises are using the open source NVIDIA Agent Toolkit — now expanded with new tools — to customize and control agents, use company data to inform their answers and actions, monitor what they do and […]

An open source “bomb” drops from China

An open source “bomb” drops from China

Bring RFD4-Proteina to your research data with AI-assisted development and serverless NVIDIA GPU compute....

Google, Red Hat and IBM released llm-d 1.0, an open-source Kubernetes-native stack for distributed LLM inference. It adds multi-tenant flow control, zero-downtime upgrades and agent-aware routing across vLLM, SGLang, TPUs and GPUs. The post Google Cloud Ships llm-d 1.0 With Cache-Aware Routing for TPU and GPU Fleets appeared first on MarkTechPost.

arXiv:2610.27199v1 Announce Type: new Abstract: The Jetson AGX Orin is a common computer for robots and vehicles, yet measured accuracy, speed and energy of current depth estimators on it are hard to find. We benchmark nine model families as of October 2026: the monocular Depth Anything V2 and 3, Depth Pro, MoGe-2, Metric3D v2 and UniDepth V2, and the stereo methods libSGM, NVIDIA ESS and Fast-FoundationStereo. Every method runs on the Orin as a TensorRT FP16 engine or native CUDA code at up to three input sizes, up to the full 5.7 MP, and is scored for metric accuracy against Middlebury 2014 ground truth (non-occluded pixels of the 10 scenes whose disparity stays below 256 px), GPU time, energy and licence. Stereo is far more accurate. At 30 fps, NVIDIA's ESS reaches 0.70% AbsRel in 8.6…

arXiv:2610.26915v1 Announce Type: new Abstract: Online action detection (OAD) identifies ongoing actions in streaming videos. Many existing OAD systems combine RGB appearance with optical flow, but dense-flow extraction remains a major computational bottleneck. Codec motion vectors (MVs) are available during decoding, avoiding a separate optical-flow computation. On THUMOS'14, optical flow exceeds MVs by 11.2 mAP points with motion-only inputs, whereas the gap narrows to 3.7 points after RGB fusion, with the largest reduction in action-category discrimination. We propose CodecMotion-OAD, which replaces optical flow with decoder-provided MVs while retaining existing temporal detector architectures. Its two-stage training first aligns MV features with a pretrained flow-feature interface wit…

arXiv:2610.26937v1 Announce Type: new Abstract: Large clinical language models often require multi-GPU infrastructure, limiting local deployment. We introduce CERTA, a decision-level statistical certificate that determines when a quantized model may substitute for its native BF16 reference and escalates decisions that cannot be certified to it. Across eleven instruction-tuned models, both general-purpose and domain-adapted, from three families (7-72B), we evaluated 2,500 clinical-verification decisions from de-identified patient contexts (2,484 patients), with patient-disjoint calibration and testing. In the higher-power operational analysis, round-to-nearest 8-bit quantization at BF16 storage served 99.8-100% of held-out decisions across all eleven models; formal finite-sample guarantees…

arXiv:2610.26913v1 Announce Type: new Abstract: The adoption of Large Language Models for radiology report structuring has been largely dominated by either proprietary cloud-based models or large open models requiring high-end GPUs for deployment, which is a critical bottleneck for clinical adoption in radiology workflows that demand data privacy and offline operation. To address this, we present MedPAO-Assist, an edge-deployable agentic framework that generates structured radiology reports directly from radiologist dictation and voice commands, requiring only $\approx3.3$ GB peak RAM and achieving an average end-to-end latency of $\approx31$ seconds on a standard laptop CPU through an asynchronous, multi-threaded execution pipeline. The system currently supports four major imaging modali…

From GPU trading to physical settlement, independent markets, and programmable compute

From GPU trading to physical settlement, independent markets, and programmable compute

The midterms will be a referendum on the GOP’s alignment with tech overlords over the public they’re meant to serve Welcome back to How We Win, a Guardian opinion series with leading thinkers, offering bold ideas for America’s political future. Last week, Robert Reich highlighted the link between corruption and affordability. Today’s edition was written by Guardian US columnist Rebecca Solnit. Sign up for future editions here. “The world should accept some bad things happening,” Sam Altman, the head of OpenAI, said recently, “for the benefits of this technology and people having the agency.” Like so many things tech oligarchs say, it’s incoherent, since Altman would like to deny the world and the people in it the agency to decide whether or not we should accept his bad things. Surveys sho…

DeepSeek has open-sourced the inference engine it uses to serve its models in production, a step it said last year The post DeepSeek open-sources the inference engine behind its API. And Huawei gets equal billing with Nvidia. appeared first on The New Stack.

DeepSeek has open-sourced DeepInfer, the Apache 2.0 inference framework that serves DeepSeek-V4.1-Flash in production. It targets NVIDIA SM100 GPUs and Huawei Ascend 950 NPUs, and ships offline inference only. The post DeepSeek Open-Sources DeepInfer, the Inference Framework Behind DeepSeek-V4.1-Flash appeared first on MarkTechPost.

As SpaceX impacts Ukraine and AI-generated music divides artists and fans, critics are asking what happens when technology has too much control over our lives This was originally published in TechScape, a newsletter about how technology shapes our lives. Sign up to receive it here Hello, and welcome to TechScape. I’m Blake Montgomery, US tech editor at the Guardian, writing to you while sitting in front of Roy Lichtenstein’s monumental Drowning Girl, on view in New York City. Today in tech, we’re discussing the perils of Elon Musk’s one-man global infrastructure, AI-generated music, and a Guardian AI conference in Paris. Continue reading...

Nebius and Nscale are among global technology partners looking to NVIDIA Vera CPUs to build the next wave of infrastructure. Their momentum reflects rapid advancements in agentic computing. Agents do more than generate answers: they retrieve information, run software tools, execute code and evaluate results. Each step depends on fast CPU processing. Vera accelerates that […]

The Barcelona Supercomputing Center (BSC)’s AI Factory Accelerator Programme, now in full operation following a pilot initiative, gives startups access to sovereign compute, technical support and training to support innovation across industries. Many of these companies are also members of the NVIDIA Inception program for cutting-edge startups — and as of today, access to some […]

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In the cavernous hall of Kraftwerk, a former power station in Berlin, German Chancellor Friedrich Merz and NVIDIA founder and CEO Jensen Huang sat down to discuss Germany’s AI roadmap, and in particular, the industrial applications of AI. Huang opened by tracing NVIDIA’s longstanding relationship with German industry, beginning with gaming systems, workstations and automotive […]

At a creative industry event that took place today in Berlin — hosted in collaboration with Adobe, Bertelsmann, NVIDIA and UFA — the latest advancements in intelligent media were on display. Key to the news: the European Broadcasting Union (EBU) is collaborating with NVIDIA to expand its sovereign framework with cloud, open models and integration […]

Today, I’m talking with Illinois Governor JB Pritzker, who has a lot of thoughts about AI, tech, and privacy. If you’ve been listening to the show, you know that one of my running theories is that those issues are driving a big and maybe kind of unexpected political realignment — and with the midterms coming up next month, and early voting already underway in a lot of places, the stakes are pretty high right now. So I asked Gov. Pritzker about all that, and he was surprisingly willing to dive right into the absolute existential weeds of what government is even for. You’ll hear him say — and it’s hard to disagree — that some problems are just collective action problems that require the government to do a lot of work. We can’t solve all these problems one at a time, or even one state at a t…

arXiv:2610.22380v1 Announce Type: new Abstract: Continuous diffusion treats the forward process as a design space; discrete language diffusion often uses absorbing corruption, leaving context fully trusted throughout generation. This makes trust binary: corrupted context is copied as ground truth, propagating errors into generated spans. We reopen this design space by combining absorbing and uniform-mixing kernels with region-dependent rates. Missing positions follow absorbing dynamics, while context undergoes low-rate random substitution, exposing the model to observed but uncertain tokens during training. At inference, a heuristic sampler re-injects noise into suspicious context under an annealed intensity and freezes context updates late in the trajectory. An 8,000-step finetune of a p…

arXiv:2610.22446v1 Announce Type: new Abstract: Neural operators approximate solution operators of partial differential equations at a fraction of the cost of numerical solvers. Efficient grid-based architectures such as the Fourier neural operator (FNO) assume uniform rectangular grids, whereas engineering simulations use large, irregular, and locally refined meshes. We introduce L-SplineFNO, a memory-efficient neural operator that couples an FNO backbone with a sparse, learnable tensor-product B-spline transfer between unstructured meshes and a latent Cartesian grid. A local normalised scatter avoids the geometry-dependent solve of analytic spline transformation while preserving compact support, partition of unity, and spline smoothness by construction. The neural operator, conditioned…