AI/ML News & Innovations Hub

Nvidia boosts share buyback program by record $150B

Nvidia Corp. today announced plans to spend an additional $150 billion on share buybacks through January 2028. The move represents the largest-ever expansion of a stock repurchase program. Furthermore, Nvidia plans to boost its current dividend of $0.25 per share. The company didn’t specify the size or timing of the planned increase. Nvidia says that the […] The post Nvidia boosts share buyback program by record $150B appeared first on SiliconANGLE .

Nvidia adds $150 billion to its historic stock buyback

The record buyback is CEO Jensen Huang’s bet that he can fund huge swaths of the AI buildout while still rewarding his own shareholders.

Apple, Nvidia, TSMC on Philippines wish list as New Clark City eyes ‘Silicon Valley’ future

Nvidia unveils tools to keep rogue AI agents in check

The new software platform can monitor the behavior of agents and quarantine suspicious ones, the company said.

Thieves stole an Nvidia-branded trailer filled with nothing but 20,000 pounds of sand

Thieves stole two trucks, including an Nvidia-branded trailer, as AI hardware thefts rise. Their haul: 20,000 pounds of sand per truck.

Nvidia: Rekord-Aktienrückkauf im Wert von 150 Milliarden US-Dollar

Während der KI-Boom Nvidias Gewinne befeuert, startet der Konzern ein rekordverdächtiges Aktienrückkaufprogramm. Dies könnte auf langsameres Wachstum hindeuten.

Nvidia launches new platform for reining in rogue AI agents

As the debate rages over whether the recent spate of rogue AI agents is a step toward AGI or a more conventional engineering problem, Nvidia is offering its own answer to problem. Nvidia CEO Jensen Huang on Monday introduced a toolkit of software and hardware products that add independent security layers around AI agents to […]

Nvidia launched a tool designed to stop AI agents from going rogue. Here’s how it works.

Nvidia has unveiled a two-layer safety system that monitors AI agents and cuts them off when they stray beyond set rules. Here's how it works.

Physical AI company SiMa.ai raises $150 Mn in Series C round

Physical AI company SiMa.ai has raised $150 million in a Series C financing round, bringing its total capital raised to $500 million and valuing the company at $1.45 billion. The round was co-led by Fidelity Management & Research Company and Amplify, with participation from Alter Venture Partners, Dell Technologies Capital and StepStone Group. AllianceBernstein, Baron Capital and J.P. Morgan also joined the round as new investors. The proceeds will be used to scale Palette Neat, an agentic software environment for Physical AI, and develop next-generation hardware capable of delivering 1,000 TOPS of compute through purpose-built Physical AI silicon, SiMa.ai said in a press release. Founded in 2018 by Krishna Rangasayee, SiMa.ai provides a software-centric platform for Physical AI applications. The company focuses on robotics, automotive, drones, industrial automation, aerospace and defence, smart vision and healthcare. SiMa.ai said it serves more than 150 customers across automotive, drones and robotics, including ARK Electronics, AVerMedia, Bosch, Emerson, Intrinsic, Kontron, L&T Technology Services, Mistral, STIGA, Synopsys and Virya Autonomous Tech, among others. According to market research cited by the company, the global Physical AI devices market, including robotics, automotive and drones, is projected to reach 145 million cumulative shipments by 2035. SiMa.ai said Physical AI applications have traditionally relied on NVIDIA GPUs, which can be expensive and power inten…

Architecting infrastructure to optimize Day 2 tokenomics

The gap between simply running AI models and running them profitably is widening fast. Early production architectures can buckle under the relentless demands of multi-agent autonomous workloads and real-time fine-tuning. Moving forward requires a fundamental shift toward a unified AI factory infrastructure engineered to optimize token-per-watt efficiency. As organizations scale up multi-turn agentic workflows and persistent inference clusters, the hidden tax of early-stage setups becomes clear. Standard data pipelines, static file stores, and legacy network topologies cannot sustain heavy deep-learning traffic. When GPUs sit idle waiting for data packets, operational costs increase with a quiet drain on profits. Learning from the front lines: Customer-led AI factory case studies To better understand how an industrialized approach stabilizes Day 2 tokenomics, technology leaders need to evaluate how peer organizations have solved these scaling, bottleneck, and cost problems. The following three real-world deployments highlight how global leaders are leveraging the HPE AI Factory with NVIDIA to turn infrastructure complexity into competitive advantage. 1. KDDI: Industrializing large-scale data center operations for advanced inference As one of Japan’s telecommunications giants, KDDI operates at the epicenter of massive, continuous digital traffic. Supporting next-generation localized large language models (LLMs) requires a massive compute framework that doesn’t buckle under the…

Nvidia stellt Sicherheitsnetz für autonome KI-Agenten vor

Nvidia baut seine Sicherheitsarchitektur für KI-Agenten aus: OpenShell begrenzt bereits Zugriffe per Software, Sentry wacht nun zusätzlich auf Hardwareebene.

How the University of Utah built a sovereign AI factory to accelerate breakthroughs and slash cloud costs

The scaling of artificial intelligence has forced IT leaders to re-evaluate infrastructure. While public clouds offer rapid deployment for general applications, they introduce steep trade-offs for highly regulated, data-intensive workloads. Issues like high latency, unpredictable operational costs, and diminished data control complicate the development of proprietary intellectual property. To bypass these limitations, leading institutions are pioneering a new approach: the sovereign AI factory. At the University of Utah, leadership confronted this issue directly. The institution needed to boost its computational capacity to accelerate clinical and academic work without compromising safety. Because these research avenues rely heavily on sensitive patient records, genomic profiles, and highly regulated healthcare data, a public cloud architecture was insufficient. The university required complete data control, strict compliance, and high performance. By collaborating with HPE and NVIDIA, the University of Utah designed and deployed an integrated, full-stack sovereign AI factory . This public-private-philanthropic co-investment—championed by the university, the State of Utah, and the Huntsman Family Foundation—serves as an example for CIOs managing high-stakes data environments. The challenge: Balancing computational scale with data sovereignty For any organization handling protected information, public cloud environments introduce significant regulatory compliance risks. For t…

The sovereign imperative: Why enterprise AI mandates a new infrastructure playbook

For enterprise Chief Information Officers, the honeymoon phase of artificial intelligence is over. As organizations move past baseline experimentation and begin anchoring generative AI and agentic workflows into core operational stacks, we are hitting a collective wall. That wall isn’t defined by a lack of use cases or algorithmic capability; it is defined by the harsh realities of data gravity, compliance, and foundational infrastructure. When scaling models that manipulate proprietary IP, sensitive financial data, or highly protected personal health information (PHI), standard public clouds introduce existential risks. The moment data crosses international borders or becomes subject to foreign legal frameworks—such as the U.S. CLOUD Act—data sovereignty evaporates. As technology leaders, we cannot close our productivity gaps by consuming AI built entirely on someone else’s terms, governed by someone else’s rules. To capture the real economic returns of this technology, enterprise intellectual property must remain local, secure, and under domestic control. This is the exact challenge that triggered a massive architectural shift, leading to the creation of Canada’s first fully sovereign AI factory. Developed by TELUS in close strategic partnership with HPE and NVIDIA , this initiative provides a powerful example of how IT leaders can balance computational capacity with uncompromised data integrity. The infrastructure challenge: Beyond virtual machines Building an enterprise-…

Nvidia wants to keep AI agents on a short leash with a watchdog built into its chips

Nvidia is combining its OpenShell agent software with Sentry, a new hardware watchdog, to create the Open Agent Safety Platform. Sentry is supposed to isolate AI agents that break out within milliseconds. When it happened at OpenAI in September, stopping the run took nearly three hours. Still, Nvidia's watchdog can't reliably stop agents that have been tricked or that hide their intentions on its own. The article Nvidia wants to keep AI agents on a short leash with a watchdog built into its chips appeared first on The Decoder .

Comment on NVIDIA’s GameGAN Uses AI to Recreate Pac-Man and Other Game Environments by 1red3

This is the kind of AI project that actually impresses me, recreating Pac-Man just by watching gameplay and keypresses is wild. It's not really "understanding" the game though, more like a really good mimic, which is the part people always oversell. Still, imagine where this goes in a few years. Honestly the way it learns patterns from repetition kind of reminds me of how 1red3 keeps you coming back, just pure loop psychology at work. Do you think GameGAN could eventually generate whole new games from scratch or is that still a long way off?

Nvidia says its new AI safety platform can contain rogue agents within ‘milliseconds’

Nvidia is launching a new safety platform designed to contain and monitor AI agents, a move that comes in response to a wave of rogue hacking incidents, as reported earlier by Reuters. In an announcement on Monday, Nvidia says its new Open Agent Safety Platform can quarantine agents that attempt to escape their boundaries within […]

Nvidia just greenlit the biggest buyback in stock market history

Nvidia said on Monday that it would it had approved plans to expand its overall buyback program to $235 billion, the biggest in stock market history.

Nvidia launches platform to quarantine rogue AI agents in 'milliseconds'

The platform is designed to control what an agent can access and isolate it within milliseconds if it crosses those limits, according to the US chipmaker.

Nvidia’s Answer to Rogue Agents Is an Open-Source AI Security System

In the wake of a series of high-profile AI safety incidents, Nvidia is introducing a new software tool that helps keep agents from escaping containment.

Comment on NVIDIA’s Minimal Video Instance Segmentation Framework Achieves SOTA Performance Without Video-Based Training by IPTV Portugal

IPTV Portugal brings live television, sports, movies, series, and entertainment together in one convenient streaming experience for viewers across Portugal.

heise+ | Bit-Rauschen: Huaweis Logic-Folding-Technik und neue KI-Konkurrenz für Nvidia

Huawei stapelt Chiplets, weil man nicht bei TSMC einkaufen darf. Der KI-Boom beschert EU-Firmen Aufwind. Neue KI-Chips rücken dichter an die von Nvidia heran.

Who’s actually paying for Yotta, rivals’ multi-billion-dollar Nvidia orders?

The post Who’s actually paying for Yotta, rivals’ multi-billion-dollar Nvidia orders? appeared first on The Ken .

Nvidia drops a free 100M-parameter model that identifies up to eight speakers in real time

Nvidia released Nemotron 3 Diarization, an AI model that identifies which speaker is talking at any given moment in a conversation. The article Nvidia drops a free 100M-parameter model that identifies up to eight speakers in real time appeared first on The Decoder .

Comment on NVIDIA’s Global Context ViT Achieves SOTA Performance on CV Tasks Without Expensive Computation by tryvideotoprompt

The token generation module carrying the long-range context is the interesting part — most hierarchical ViTs still pay for global attention somewhere. Wonder how it holds up on video, not just stills. Inverse problem: turning video into prompts for Sora or Veo — https://tryvideotoprompt.com/

Solo Dev Runs NVIDIA's DLSS 5 Neural Rendering on AMD Radeon GPUs

An indie modder reimplemented NVIDIA's DLSS 5 Neural Rendering runtime from scratch for Radeon GPUs, and just cut its performance cost by 74% in a day.

Why US chip controls took a back seat at the Xi-Trump summit

There is little question that Jensen Huang and Lisa Su, the heads of US semiconductor chip giants Nvidia and Advanced Micro Devices (AMD), had secured two of the best seats in the house at the White House state dinner on Thursday evening: at the head table alongside the two presidents and their wives. But what remains unclear is how much progress they were able to make on their primary goal of restoring access to the Chinese market, amid entrenched opposition to that happening in both China and...

Comment on NVIDIA’s nGPT: Revolutionizing Transformers with Hypersphere Representation by Daniel Porter

The hypersphere normalization detail is striking—eliminating weight decay entirely while gaining intrinsic stability, plus 4-20x fewer training steps, makes nGPT worth watching. Reading this got me thinking about cognitive training in general; even for humans, consistent practice on memory and focus games can sharpen how quickly you absorb dense material like this paper's summary.

Nvidia's SoL-Pi system cuts coding agent token usage nearly in half by optimizing the harness

SoL-Pi cuts coding agents' token usage by up to 49 percent with little change in performance by optimizing the control layer between the model and its environment. A research agent tested 152 approaches across more than 3,000 runs to develop the system, though the gains were smaller on other benchmarks. The article Nvidia's SoL-Pi system cuts coding agent token usage nearly in half by optimizing the harness appeared first on The Decoder .

NVIDIA Confirms Morocco in Two African AI Compute Projects, Including 500MW Casablanca Factory

NVIDIA has confirmed Morocco’s place in two African AI infrastructure projects, including a Nexus AI Factory now sited near Casablanca with an initial budget of $1.2 billion and a target capacity of 500 megawatts. The confirmation came in an NVIDIA article published on 21 September. Both projects were previously announced; what is new is the [...]

Thieves Stole ‘Nvidia’ Trailers. They Got 20 Tons of Sand

They wanted the silicon. They got the sand.

Ahead of US IPO, British AI neocloud Nscale secures $3.36B in convertible financing

The funding, which comes from Third Point, Nvidia, and others, will fuel the company's massive AI data center buildout.

CoreWeave expands full-stack AI cloud push as inference demand grows

The rise of AI-native cloud provider CoreWeave Inc. is part of the greater story emerging around operationalizing AI. As enterprises shift from training to inference, neoclouds such as CoreWeave are providing cloud infrastructure tailor-made for AI. The company made waves by completing the industry’s first bring-up and validation of Nvidia Vera Rubin NVL72 on CoreWeave […] The post CoreWeave expands full-stack AI cloud push as inference demand grows appeared first on SiliconANGLE .

Moondream Shrinks Parakeet Redux Speech Recognition to 178 MB

Moondream shrank NVIDIA's Parakeet speech model from 1.2GB to 178MB using ternary weights, hitting 113x realtime on CPU while matching accuracy.

Larry Yon: Why Africa’s tech ecosystem should be building the next NVIDIA

From a failed venture in South Africa to co-founding an AI cybersecurity powerhouse, CyberAlliance president Larry Yon II sits down with PHATHISANI MOYO for Coffee With… to explain why digital trust and diaspora capital are key to unlocking Africa’s true tech potential. The first time Larry Yon II flew out of South Africa, he sat […]

Nvidia's historic stock boom is turning its golden handcuffs into a ticket out the door

Nvidia's historic stock boom has made some longtime employees wealthy enough to walk away as valuable stock grants finish vesting.

Nvidia CEO Jensen Huang dismisses AI fears as 'distraction'

Nvidia chief Jensen Huang characterized fears over AI’s existential threats as a “distraction” that’s “not grounded on science.

Jensen Huang talks about AI and climate change like a supervillain

As Jensen Huang puts it, AI can help fight climate change - but only if it inflicts "an enormous amount of pain and suffering" first. The Nvidia CEO discussed the future of energy and AI's impact on our planet in the latest episode of The Ezra Klein Show. But his comments boil down to the […]

The 'ChatGPT for doctors,' OpenEvidence, was valued at $15 billion in a new funding round

The startup has raised nearly $800 million over the past year, from investors including Nvidia, Thrive Capital, Kleiner Perkins, a16z, and Sequoia Capital.

The GPU revolution: Redefining the architecture of innovation

For decades, the metric for success in the C-suite of research institutions and enterprise data centers was simple: raw CPU clock speed. In the supercomputing landscape, solving the world’s most complex problems—weather forecasting, aerodynamic modeling, or seismic analysis—means stringing together thousands of traditional processors. However, we have entered a new era. The CPU-only approach has hit a thermal and scaling wall. Today, some of the most powerful supercomputers on Earth share a common DNA: they are GPU-accelerated. The shift is not from CPUs to GPUs in isolation. It is from CPU-centric clusters to accelerated systems where CPUs coordinate control-plane work, GPUs deliver massive parallel throughput, and high-speed networking, storage, and software keep the entire system at peak output. As HPE and NVIDIA continue to push the boundaries of what is possible, the integration of GPUs into the heart of the data center has done more than just speed up calculations. It has fundamentally changed the architecture of discovery, moving supercomputing from a niche academic pursuit into the engine room of innovation and discovery. From graphics to greatness: The architectural shift To understand why GPUs have become more standard for HPC, we have to look at the shift from serial to parallel processing. Traditional CPUs are designed for latency-sensitive tasks. They are like a few highly skilled craftsmen who can do almost anything, one step at a time. This is perfect for runn…

Perplexity Brings Portable Computer to AMD Ryzen AI Max PCs

Perplexity's local-first agent stack now runs on AMD Ryzen AI Max Series chips, expanding beyond NVIDIA RTX and DGX Spark for on-device workflows.

How Open Science Can Help Researchers Prepare for the Next Pandemic

When COVID-19 emerged, scientists had a crucial advantage: Decades of prior research on coronaviruses meant they understood the virus’ key proteins well enough to design vaccines in record time. The next pandemic may not offer the same head start. To help improve the odds, NVIDIA has joined a coalition of global research organizations, including Google […]

Egypt and NVIDIA Prepare AI Cooperation MoU Covering Compute, Skills and Startups

Egypt’s Ministry of Communications and Information Technology is preparing a memorandum of understanding with NVIDIA covering AI, computing, digital skills and innovation support, following a meeting between ICT Minister Raafat Hindi and NVIDIA vice president for Europe, the Middle East and Africa, Paolo Guglielmini. The MoU has not been signed and no value, timeline or [...]

Comment on NVIDIA’s Hybrid: Combining Attention and State Space Models for Breakthrough Performance of Small Language Models by Queens online

The discussion of self-evolving prompts and AI alignment is fascinating. I appreciate how you connect the technical ideas with the practical challenge of keeping systems accountable — a thought-provoking read.

AI drug discovery startup Basecamp Research raises $140M

Basecamp Research Ltd. today announced that it has raised $140 million in funding from a group of prominent investors. S32, a fund affiliated with Google LLC co-founder Bill Maris, led the Series C round. It was joined by more than a dozen other investors. The group included NATO, Nvidia Corp. and the Anthology Fund, a […] The post AI drug discovery startup Basecamp Research raises $140M appeared first on SiliconANGLE .

How to Use NVIDIA Warp and MjWarp to Accelerate Robotics Simulation and Learning Workflows

Jensen Huang Says If We Cannot Align AI, Shut Down the AI Labs

I was very surprised today on a podcast to hear Jensen Huang plainly state that if they cannot align the AIs, then the labs must shut down. The context I have on Huang is that he has run NVIDIA for 30+ years, which has become the most valuable company in the world due to the AI boom. My understanding is that he has repeatedly encouraged the US President (with whom he is on friendly terms) to continue to support AI, and dismissed AI talk as "sci-fi". If you haven't seen, his biographer has incredible quotes of him being pressed on risks from AI, where Jensen gets furious. “This cannot be a ridiculous sci-fi story,” he said. He gestured to his frozen PR reps at the end of the table. “Do you guys understand? I didn’t grow up on a bunch of sci-fi stories, and this is not a sci-fi movie. These are serious people doing serious work!” he said. “This is not a freaking joke! This is not a repeat of Arthur C. Clarke. I didn’t read his fucking books. I don’t care about those books! It’s not– we’re not a sci-fi repeat! This company is not a manifestation of Star Trek! We are not doing those things! We are serious people, doing serious work. And – it’s just a serious company, and I’m a serious person, just doing serious work.” And interviewed by Dwarkesh Patel he says other dismissive things: “If we scare this country into thinking that AI is somehow a nuclear bomb, so that everybody hates AI and everybody’s afraid of AI, I don’t know how you’re helping the United States. You’re doing it…

NVIDIA's Nemotron 3 Beats 12 Rivals With a 14.72% Speaker Error Rate

NVIDIA's 100M-parameter Nemotron 3 Diarization tracks up to 8 speakers in overlapping conversations, topping Voice Arena's benchmark with 14.72% DER.

Sakeena Fiza Helps NVIDIA Hardware Succeed at Scale

When Sakeena Fiza describes her work as a validation engineer at NVIDIA, she does so in terms more befitting a detective story than a world-class engineering lab. “Validation engineers look in the shadows and shine a light into every corner,” Fiza said. “Every time we get a system, our first thought is: how can it […]

Nvidia-backed Nscale keeps its biggest customer, Bytedance, out of its IPO filing

Nscale, the Nvidia-backed AI cloud provider, leaves its most important customer, Bytedance, out of the main prospectus for its planned US IPO. The article Nvidia-backed Nscale keeps its biggest customer, Bytedance, out of its IPO filing appeared first on The Decoder .

Inside Basecamp Research, the AI startup turning evolution into training data

Basecamp Research has raised $140 million from investors including Nvidia and Anthropic's Anthology Fund. The London company trains AI models on genetic material from rainforests, oceans, and hot springs to design antibiotics and tools for cell therapies. In an interview with THE DECODER, CTO Philip Lorenz explains why biology is a far bigger problem for AI than language, and why good scores on paper don't guarantee good molecules. The article Inside Basecamp Research, the AI startup turning evolution into training data appeared first on The Decoder .

**Know Who Spoke When: Build Real-Time, Multi-Speaker AI with NVIDIA Nemotron 3 Diarization**

Comment on Facebook AI & UC Berkeley’s ConvNeXts Compete Favourably With SOTA Hierarchical ViTs on CV Benchmarks by nano-video

No novo artigo Global Context Vision Transformers, uma equipe de pesquisa da NVIDIA propõe o Global Context Vision Transformer (GC ViT), uma arquitetura ViT hierárquica nova e simples, composta por módulos de autoatenção global e geração de tokens. Ela possibilita modelar de forma eficiente dependências de curto e longo alcance sem operações computacionais onerosas, alcançando resultados SOTA em diversas tarefas de visão computacional. nano-video.io

Anthropic with Menlo Ventures and Nvidia back Basecamp Research in $140M Series C

A UK life sciences startup using AI to develop new medicines faster to treat diseases has raised $140m in funding, in an investmentround featuring AI powerhouses Nvidia and new investor Anthropic, who...

Higher Quality Small Synthetic Natural Language Text Generation for Interpretability Research

Introduction Small simple synthetic natural language datasets suitable for end-to-end training of tiny LLMs serve as an important resource for LLM interpretability researchers. Some well know examples include roneneldan/TinyStories , SimpleStories/SimpleStories , and klusai/ds-tf1-en-3m (TinyFabulist). This post solves key problems that degrade the quality of these datasets, while also offering an efficient accessible pipeline that can be run locally on an NVIDIA 5060 Ti (16GB) graphics card. The core problems this post solves, include: True Small Vocabulary. The aforementioned datasets attempt to produce a corpus with a small vocabulary, but arguably fall a bit short of that goal. E.g., TinyStories has 49,187 unique words, SimpleStories has 40,567, and TinyFabulist has 41,502. Guaranteed minimal word frequencies. In the aforementioned datasets, 15 to 24 percent of the unique words occur less than 2 times, while between around 43 to 54 percent occur less than 8 times. This means that most of the unique words are likely not learnable, and mostly contribute to noise and vocabulary bloat. Error free text. The aforementioned datasets, include lots of errors, such as misspelled and mangled words. Reliable Name Disambiguation and Stratification. The aforementioned datasets, have various name management issues, ranging from collision with existing words (e.g., May vs may), name bloat, and no control over gender balance, or bias (e.g., certain names may be more likely to co-occur wi…

At AI Day Singapore, NVIDIA and Partners Showcase AI Advancements Across Southeast Asia

NVIDIA AI Day Singapore, which takes place Sept. 22-23 at the Raffles City Convention Centre, is offering attendees opportunities to explore the hands-on training, expert-led sessions and advanced tools to accelerate their work in AI and high-performance computing. At the event, NVIDIA and its partners are showcasing breakthrough AI advancements across the Southeast Asia region […]

Andreessen Horowitz is launching an ‘academy’ with no homework and partnerships with Palantir, Google, and Meta

Venture capital firm Andreessen Horowitz (a16z) is creating an "academy" positioned as a pipeline for young people to build or join a Silicon Valley startup. The "Horowitz Andreessen Academy" will launch with 10 partners, including Anduril, Anthropic, Coinbase, Google, Meta, Nvidia, OpenAI, Palantir, Replit, and Stripe, along with $42 million in funding led by a16z. […]

‘Fear of the unknown’ drives data center pushback, Nvidia exec says

At Semafor’s The Next 3 Billion, Nvidia’s head of sustainability pushed back against the groundswell of anti-AI sentiment that’s unfurled in the US over the last few weeks.

Five AI safety sessions every founder should have on their TechCrunch Disrupt 2026 agenda

At TechCrunch Disrupt 2026, five sessions across the AI Stage and Real World AI Stage cover AI safety, featuring leaders from Anthropic, Nvidia, AWS, Waabi, and more. Register before September 25 to save up to $200.

Beyond the limits of air: Why liquid cooling is becoming a strategic imperative for AI

In the rapidly evolving information technology landscape, the data center of the future has arrived ahead of schedule. As AI workloads move to become core business drivers, the underlying infrastructure is hitting a thermal wall. For CIOs, the transition from traditional air cooling to liquid cooling is no longer a niche technical choice for supercomputers—it is a critical financial and operational investment in long-term enterprise viability. Working together, HPE and NVIDIA are redefining what’s possible, but realizing the full potential of these advancements requires a fundamental shift in how we cool the infrastructure that powers them. The physics of performance: Why air is no longer enough For decades, air cooling has been the workhorse of the data center. However, the math is changing. Standard CPUs and early-generation GPUs could be kept within operational limits by moving massive volumes of air through the rack. But with the advent of next-generation GPUs like the NVIDIA Blackwell series, power densities are skyrocketing. The power density gap: A fully populated modern GPU rack can draw upwards of 132 kW, with next-generation architectures projected to reach 240 kW per rack—and eventually 1 MW per rack . Thermal limits: As chip density rises, the thermal tolerance of these processors is actually decreasing . Air simply does not have the thermal conductivity required to pull heat away fast enough to prevent thermal throttling. The cooling-to-compute ratio: Traditiona…

Creating AI agents is easier (and faster) than you think

This year, the conversation in the C-suite has shifted from agentic AI to, “How do we make AI work safely, repeatedly, and at scale?” The answer lies in AI agents, autonomous or semi-autonomous systems that don’t just chat, but reason, plan, and execute multi-step tasks across your enterprise ecosystem. For many CIOs, the perceived barrier to agentic AI is a mountain of custom coding and infrastructure complexity. But thanks to the deep co-engineered innovation between HPE and NVIDIA, that mountain has become a molehill. By leveraging the HPE AI factory with NVIDIA, building and deploying production-ready agents is now a matter of clicks, not months. The shift from chatbots to intelligent agents While first-generation AI focused on single-turn interactions, like a basic chatbot answering a question, agentic AI represents a fundamental evolution. An agent can: Reason: Break down a complex goal (“Optimize our Q3 supply chain”) into actionable steps. Use tools: Access your SQL databases, ERP systems, or external APIs to pull real-time data. Act: Execute the final task, such as generating a purchase order or updating a CRM entry. Making it practical: The blueprint approach The secret to speed is not building from scratch; it’s building on what is already proven. NVIDIA’s NIM Agent Blueprints provide preconfigured, reusable reference workflows for common enterprise use cases, with the required microservices sample code and deployment guides built-in. HPE provides the optimized in…

The agentic frontier: A CIO’s guide to securing autonomous AI

While first-wave AI was largely conversational—chatbots that summarized documents or drafted emails—the second wave is operational. AI agents are autonomous entities capable of reasoning, planning, and executing multi-step workflows. They don’t just tell you that your inventory is low. They negotiate with suppliers, update ERP systems, and optimize shipping routes without human intervention. However, this autonomy introduces a paradox. The more useful an agent becomes, the more dangerous it can be if compromised. While we can add humans-in-the-loop, when agents gain the power to act on behalf of the enterprise, they expand the attack surface beyond traditional security frameworks. In fact, current industry data suggests that nearly 90% of IT leaders have already experienced security incidents related to AI pilot programs. To move to a production-ready AI factory, CIOs must move beyond wrapper security and embrace a framework of sovereign AI. HPE and NVIDIA have identified three ways to secure the agentic enterprise: Establishing a silicon-level root of trust, implementing zero-trust identity for non-human actors, and deploying real-time behavioral guardrails. 1. Building on a silicon root of trust Security for autonomous agents cannot exist solely at the software or application layer. If the underlying infrastructure is compromised, every decision the agent makes—and every piece of data it touches—is at risk. In an era where model poisoning and firmware hijacking are real th…

The supercomputing DNA of the AI factory

In the world of high-performance computing (HPC), few symbols carry as much weight as the C shape of the Cray-1. The US $1 Cray-1 coin is more than a tribute to computing history. It is a reminder that breakthrough performance has always depended on system architecture: how compute is arranged, connected, cooled, and operated. AI factories may be relatively new, but the challenge is familiar: orchestrating massive amounts of compute, data, networking, power, and cooling into a single system that consistently delivers outcomes. That’s exactly the problem Cray supercomputing was built to solve, and why its engineering DNA is foundational to today’s AI factories. Co-engineering the HPE AI Factory The collaboration between HPE and NVIDIA is built on a shared philosophy: to handle the massive datasets required for agentic AI and deep scientific simulation, the hardware cannot be a collection of disparate parts. It must be a unified system. By combining HPE’s world-leading supercomputing infrastructure with NVIDIA GPUs and NVIDIA Spectrum-X Ethernet networking, the companies have created a portfolio of AI factory solutions. These dedicated, on-premises engines are designed to turn raw data into actionable intelligence with unprecedented scale and security . Innovation in action The true measure of this collaboration is found in joint customers. These organizations are not just buying servers; they are deploying massive-scale systems to redefine their industries. 1. Leibniz Superco…

Comment on NVIDIA Open-Sources Hyper-Realistic Face Generator StyleGAN by Ryan

Intéressant de voir que NVIDIA ouvre le code de StyleGAN, surtout avec les exigences matérielles élevées comme les GPUs V100. ScoopRYM transforme justement les gros titres tech en chansons, alors un outil comme ça pourrait donner lieu à un bon meme musical.

NVIDIA Launches DSX Ready to Qualify Power and Cooling Products for AI Factories

Every AI factory needs power and cooling that fit its computing architecture. As AI infrastructure expands, power, cooling, water, site and grid constraints are shaping what builders can deploy. Choosing products that fit the complete factory design helps builders turn computing capacity into useful AI output. To help builders make those decisions, NVIDIA is introducing […]

SGLang Squeezes 78% More AI Throughput on NVIDIA's Blackwell GPUs

SGLang, Qwen, and NVIDIA ship 4-bit NVFP4 KV cache on Blackwell, packing 1.78x more context and boosting long-context decode up to 78%.

On theCUBE Pod: Dreamforce unveils the agentic dream, and Nscale files to go public

Salesforce Inc. keeps putting all of its eggs in the agent basket — but the strategy appears to be paying off so far. At Dreamforce 2026, Marc Benioff, chief executive officer of Salesforce, bantered with Nvidia Corp. CEO Jensen Huang and led the announcement of a new artificial intelligence interface layer, AIforce. The event also […] The post On theCUBE Pod: Dreamforce unveils the agentic dream, and Nscale files to go public appeared first on SiliconANGLE .

From Enablement to Execution, Egypt’s AI Ecosystem Reaches Production Scale

Today, Egypt’s AI builders gathered in the Grand Egyptian Museum for a reception that highlighted the nation’s rapidly growing AI ecosystem — spanning AI natives, developers, researchers, startups and enterprises — building applications across industries. The event included a keynote from Paolo Guglielmini, vice president of EMEA at NVIDIA. Ahmed Mostafa, regional AI adoption lead […]

Nvidia boss says there is ‘0% chance’ AI destroys the world by 2030

Jensen Huang dismisses warnings from former Anthropic researcher and others as ‘doomsday narratives’ The boss of the chipmaker Nvidia has said AI will not develop to a point that will lead to the extinction of the human race within a few years, rejecting such assertions as overblown “doomsday narratives”. Jensen Huang, the co-founder and chief executive of the $5tn AI chipmaker, said the claims made on social media by the former Anthropic researcher Jacob Coxon that AI could become “superhuman” and kill off humanity within the decade were “irresponsible”. Continue reading...

5 Companies Using NVIDIA AI for Clean Energy

Clean energy isn’t hard to come by, but the pace of large-scale adoption has historically been slow due to bottlenecks — including out-of-date infrastructure, elongated research and development timelines, and upfront cost barriers. At New York Climate Week, NVIDIA is highlighting five companies pioneering clean energy projects with AI baked into their foundation, accelerating research-to-inception […]

Nvidia's Jensen Huang says AI CEOs have 'ulterior reasons' for warning about doomsday

Nvidia CEO Jensen Huang says current regulations are enough to ensure AI is safe — and profitable.

No one is surprised that Nvidia’s Jensen Huang thinks AI fears are overblown

The man who may stand to make the most money from the AI boom seems to think he knows better than anyone else, including researchers who have studied and worked on AI for decades. In an interview with CBS Sunday Morning, he claimed there was a "0% chance" of AI being the end of the […]

Dario Amodei and other AI leaders want to ‘Pace the Frontier’ but…how?

A week after an Anthropic researcher’s doomsday warning rattled the AI world, the company’s CEO Dario Amodei has outlined his plan to “pace the frontier” of AI development. The proposal leans on independent safety evaluators and coordination between AI labs in democratic countries, and it’s already picked up some industry support, along with some pointed pushback from Nvidia’s Jensen Huang. Watch […]

Practical quantum computers are over a decade away, says NEC

A practical, commercial quantum computer is over a decade away, executives at Japanese IT services company NEC are reported as saying. That’s why, according to Japanese news publication The Mainichi , company has pulled the plug on its plans to develop a quantum computer — although it will still continue research into quantum technology. NEC sources told The Mainichi that it would take at least a decade to build a quantum computing that could be put to practical use, and it would be difficult to monetize the technology. This is quite a turnaround for NEC which three years ago was talking about its advances in quantum and its plans to accelerate investment in the technology . The company is certainly bucking the trend as quantum computing is seen as being very much at the cutting edge of research. Pioneers in the field were awarded the Nobel Prize in Physics last year, while companies such as Nvidia and IBM are keen to boost their quantum credentials. Despite its early successes in the quantum field, The Mainichi reports that NEC is lagging its Japanese competitors such as Fujitsu and Hitachi when it comes to the latest advances. There is also the level of investment required. According to The Mainichi, Japan is set to commit just 10 trillion yen ($65.3 billion) to quantum computing by 2040, far lower than the sums invested by the US and China. We’re talking about a long game. Quantum technology has been talked about for some time, but we’re still a long way from seeing the t…

Open or closed AI? Nvidia’s Nader Khalil and Sydney Sykes take on one of the decisions shaping next-gen startups at TechCrunch Disrupt 2026

Nvidia's Nader Khalil and Sydney Sykes discuss one of the decisions shaping next-gen startups on the Builders Stage at TechCrunch Disrupt 2026.

The Preference Cascade Is Only Getting Started

We are in the midst of a preference cascade about existential risk from AI. A preference cascade is, alas, the best method we have to change the debate. The avalanche has started . There is still time for the pebbles to vote . For now. Mike Solana gave the correct view of why Coxon’s post went viral , which is that enough Americans finally have enough context on AI to care, and there were enough big accounts that were happy to amplify the Tweet quickly to get it initial attention. That is all you need when there is enough dry tinder. What we must realize is that the current preference cascade, on the need to Pace the Frontier, is insufficient. If we are to make it out of this alive, we will have to do better. We have to, as Dan Selsam warns, actually solve the underlying problems. The next step is to continue the cascade. That includes inside the labs, and also among the media and politics. It includes both people who previously focused on other things stepping up and new voices being heard. A lot of that will be overcoming the inevitable political opposition, especially from the likes of Nvidia and a16z , that for now has the rhetorical allegiance of the President and is doing things like planting hack job METR hit pieces in the New York Post. In short fuse news: There will be a quickly thrown together conference, AGI.WTF, at Lighthaven September 22-23 . Table of Contents The Cascade Was a Long Time Coming. The Cascade Has Reached The People. Elon Musk Doubles Down. Matthew…

heise+ | Nvidia RTX Pro 6000 Blackwell im Test: 96 GByte VRAM für KI und Workstations

Mit ihren enormen 96 GByte Grafikspeicher ist die RTX Pro 6000 Blackwell für lokale KI prädestiniert. Nebenbei ist sie auch die schnellste 3D-Grafikkarte.

China to see major shift to Huawei for AI model training in 2027: deputy chair

Huawei Technologies expects a major domestic shift towards its artificial intelligence computing infrastructure for model training next year, as its Ascend processors gain ground on Nvidia in China despite supply constraints, according to rotating chairman Eric Xu Zhijun. “I believe that starting from next year, a lot of the AI model training will be based on the SuperPoD or SuperCluster based on Ascend 950DT,” Xu told reporters during the Huawei Connect 2026 conference in Shanghai on...

Nvidia’s case for taming AI agents

The company’s VP of agentic AI told Semafor he sees AI safety as an engineering challenge, rather than an unprecedented, existential threat.

The AI Slowdown Debate Crashed Salesforce’s Party

The Dreamforce conference became an unlikely battleground for the CEOs of OpenAI, Anthropic, and Nvidia to debate whether AI development should slow down.

Bericht: Apple erwägt Rückkehr ins Servergeschäft mit Nvidia-Technik

Apple will womöglich Server mit M8-Ultra-Prozessoren auflegen. Eine Kombination mit Nvidias Netzwerktechnik wäre möglich.

Huawei plans Q1 2027 launch of new AI chip as it takes on Nvidia

Huawei is accelerating the launch of its next-generation Ascend 960DT AI chip as it pushes to compete with Nvidia and close China’s AI computing gap with the U.S.

Google, Nvidia, and Anthropic want Emerald AI to find space on the grid for more data centers

A new coalition that includes Google, Nvidia, Anthropic, and Emerald AI wants to find 100 GW of grid capacity for new data centers.

Jensen Huang: Don’t regulate AI like social media

Nvidia boss tells summit hosted by King Charles III that lawmakers should 'regulate the products,' not the underlying tech.

Huawei unveils latest tech to boost AI power in push to break China’s Nvidia reliance

Huawei Technologies on Thursday unveiled its latest Atlas 960 SuperPoD computing cluster and an upgraded version of its UnifiedBus interconnect technology, key components of the Chinese tech giant’s strategy to build advanced artificial intelligence systems despite US semiconductor-related restrictions. At the Huawei Connect 2026 conference in Shanghai, the Shenzhen-based firm introduced near-packaged optics (NPOs) – a placement structure enabling higher speeds and lower energy use – to the...

Fault tolerant distributed training on Amazon EKS using NVRx

Integrate NVIDIA Resiliency Extension (NVRx) into PyTorch FSDP training on Amazon EKS to overlap checkpoint I/O with training and recover from GPU faults in seconds. This post covers async checkpointing, in-process restart, and ft_launcher in-job restart, with H100 benchmarks at 2 to 8 nodes showing 99%+ training efficiency and second-scale recovery.

Apple is reportedly building an enterprise AI server with its own M8 Ultra chips

According to The Information, Apple is working on an enterprise server with two or four M8 Ultra chips for the AI inference market, with a possible launch no earlier than 2029. Apple is considering Nvidia's NVLink Fusion technology to connect the chips. The project could get a boost from OpenAI and Anthropic already buying Mac hardware in bulk for AI workloads. The article Apple is reportedly building an enterprise AI server with its own M8 Ultra chips appeared first on The Decoder .

NVIDIA's Axolotl3D Reconstructs Hidden 3D Geometry From Partial Photos

NVIDIA's Axolotl3D fuses images, camera poses, and partial point clouds into one diffusion pipeline that completes occluded 3D shapes faithfully.

Apple might make servers again to cash in on the AI rush

According to The Information, Apple is planning to get back into the server game and might just pair up with Nvidia to make it happen. Apple retired its Xserve line in 2011 and has largely left enterprise machines to other manufacturers since. But the growing demand for compute power as the AI industry continues to […]

Cohere's Model Vault Now Encrypts AI Prompts Even From Cloud Admins

Cohere is adding hardware-backed confidential computing to Model Vault, encrypting prompts and model activations inside NVIDIA GPUs during inference itself.

Trump Goes Full Hoax on AI Existential Risk

This is our reality. I suppose we have to talk about it. Everyone in a position to know is freaking out about AI potentially killing everyone this decade and wants to pace the frontier, and people are finally listening. It only took a few days for the conversation to fully pivot to the counteroffensive, where the Usual Suspects and those they recruited attacked anyone and everyone who dared point out that we are in danger, with every attack they can think of, usually without substance or any attempt at understanding. Sigh. I knew what I signed up for. Table of Contents Hold Your Fire. If You Don’t Like the Weather. Trump Does Not Take Kindly. Trump Goes Full ‘Hoax’. This Is Not About Data Centers, Mr. President. I Am The Hoax Buster, I Am The Hoax Buster, I Am The Walrus. Nvidia CEO Jensen Huang Is a Lying Liar. Trump Quietly Draws Key Distinction. Calling For Pacing the Frontier Is Bad For AI Stock Prices. People On The Internet Sometimes Lie. Origins of Cynicism. Ineffective Egoism. The McCarthyist Faction Attacks METR. Other Key Republicans React. David Sacks Stops Being Plausibly Constructive. Federal Trade Commission Chooses Danger. Chris Lehane Heel Face Turn. A Matter of Trust. China Calls It Fearmongering. Pick Up The Phone. If You Want To Beat China So Badly You Should Act Like It. Never Go Full Hoax. Trump Uses AI For Things. Hold Your Fire The most important thing, as this plays out, remains to not make things worse. Please do not make this any more partisan or pe…

NVIDIA Vera Rubin NVL72 Delivers Leading Performance in MLPerf Inference v6.1 Debut

System performance, efficient infrastructure scaling and continuous software optimization are key levers that determine AI inference economics. Higher system performance means more tokens generated, resulting in higher revenue. Efficient scaling means throughput grows proportionally as hardware gets added, requiring fewer resources to serve users at scale. Continuous optimization means generating more value from infrastructure investments. […]

Robots are waiting for a ChatGPT moment: Nvidia’s Les Karpas explains why at TechCrunch Disrupt 2026

The robotics industry is still waiting for their breakthrough into day-to-day life. Nvidia's Les Karpas has an answer as to why at TechCrunch Disrupt 2026. Register before September 25 to save up to $200 on your pass.

Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers

AI factories are the infrastructure of the intelligence era. Scaling them responsibly will depend as much on innovation across the grid as inside the data center. Today, Emerald AI, Google and NVIDIA announced the launch of the AI Energy Management Alliance (AEMA), a first-of-its-kind coalition advancing data centers that can dynamically manage their electricity use […]

Microsoft lädt zum ersten Windows-Event seit fast 2,5 Jahren

Am 7. Oktober veranstaltet Microsoft ein Event zu Windows und Surface. Auch Nvidia-Chef Jensen Huang nimmt teil.

Jensen Huang said China isn’t spending time debating the AI apocalypse. We are, the Chinese internet says.

Nvidia CEO Jensen Huang's remarks are trending on Weibo, the country's version of X.

University of Manchester Uses NVIDIA Earth-2 to Forecast Air Pollution Across the UK

Air pollution is a serious public health risk, contributing to an estimated 30,000 deaths in the U.K. alone last year. Data-driven insights can help — but computing air quality with traditional chemistry-based models is expensive, which limits how detailed they can be and how regularly they can be run. David Topping, a professor in the […]

Anthropic CEO renews call for AI slowdown as Nvidia’s urges acceleration

At San Francisco conference, OpenAI chief Sam Altman calls for more rigorous security measures Anthropic’s CEO took the stage at a conference in San Francisco on Tuesday to reiterate his call for a slowdown of AI development, while Nvidia’s CEO argued against such deceleration. Dario Amodei used an automotive analogy to make his point: when a competing car company has a safety incident like brake failures, it is a moment for all car companies to stop and review their own practices, he said at Salesforce’s Dreamforce convention on Tuesday. Continue reading...

We don’t need AI regulation — leave safety to us, Nvidia’s Jensen Huang says

AI isn't some new form of "alien mind," according to Jensen Huang. It's just hardware and software, so safety can be engineered by each AI product maker.

AI progress and responsibility: Nvidia, Anthropic and OpenAI CEOs weigh in at Salesforce’s annual event

If a measure of one firm’s impact is based on the company it keeps, then Salesforce Inc. has made a significant leap into the artificial intelligence conversation for 2026. At Dreamforce, the customer relationship management giant’s annual conference that kicked off in San Francisco today, Chief Executive Marc Benioff (pictured) spent much of his time […] The post AI progress and responsibility: Nvidia, Anthropic and OpenAI CEOs weigh in at Salesforce’s annual event appeared first on SiliconANGLE .

‘Now We Can Know Everything and Do Anything,’ Jensen Huang Says at Dreamforce

Know everything. Do anything. That was the message NVIDIA founder and CEO Jensen Huang brought to Salesforce Dreamforce Tuesday, joining CEO Marc Benioff onstage in an appearance that coincided with the announcement of Koa — Salesforce’s first CRM reasoning model, built on NVIDIA Nemotron 3 Super. Huang didn’t just take the stage. He walked into […]

Nvidia boss on AI safety: ‘We don’t need any new laws’

The head of one of the most profitable tech companies pushed arguments voiced by the president at a major AI conference as other industry leaders call for a slowdown.

AI networking startups race to replace Nvidia's NVLink

Intel spin-off Cornelis and newcomer Delos Data pitch open alternatives for scaling AI beyond the rack

AI labs have a data trust problem that their policies haven't solved

OpenAI and Anthropic tell corporate customers their data won't be used for training. But when Anthropic said it would store usage logs from its flagship model Fable for 30 days, Palantir, Nvidia, and Booz Allen Hamilton pulled back from using it for sensitive work. From boardrooms to research labs, AI companies still have a data trust problem. The article AI labs have a data trust problem that their policies haven't solved appeared first on The Decoder .

From Megawatts to Tokens: How NVIDIA Maximizes AI Factory Production

On a sweltering August evening in Silicon Valley, as the sun dropped and air conditioning loads spiked, Silicon Valley Power sent a signal to an AI factory to adjust its power consumption. Varun Sivaram was watching on Zoom with about forty others — his team at Emerald AI in their San Francisco conference room, engineers […]

AI Infra Summit: NVIDIA Vera Rubin and DSX Platform Advancements Showcase Energy Efficiencies of Optimizing Tokens Per Watt for AI Factories

Ian Buck, vice president of hyperscale and high-performance computing at NVIDIA, Tuesday spoke on AI factory efficiency at the AI Infra Summit, the Santa Clara Convention Center event that has morphed into a Coachella of infrastructure tech. Before a packed audience — with more than 8,000 attendees this year, up from 3,500 last year — […]

Salesforce, Nvidia unveil CRM domain-specific reasoning model

Together with partner Nvidia, Salesforce today at Dreamforce Conference 2026 unveiled a new CRM domain-specific reasoning model for Agentforce dubbed Koa. “It’s built on Nvidia’s Nemotron and it brings together 27 years of product development in CRM,” said Rohan Kumar, president and chief platform and engineering officer at Salesforce. Kumar explained that Koa was built by post-training Nvidia Nemotron 3 Super with a synthetic data set modeled on the enterprise knowledge Salesforce gleaned from three decades of CRM deployments, not on customer data. Drawn from synthetic scenarios that simulate real-world enterprise workflows across more than 14 industries — including manufacturing, financial services, healthcare, and travel — the training corpus was designed to reflect the reasoning, tool use, and decision-making skills agents perform across CRM workflows. “The genesis of this was looking at all the things we’ve learned in building out our products, the strategy we’ve created, and asking how could we augment a model to make it very specific to this job,” Kumar said. Under the hood Salesforce post-trained the model by applying Supervised Fine-Tuning (SFT) and reinforcement learning to Group Relative Policy Optimization (GRPO) and Nvidia NeMo RL, NeMo Gym, and NeMo AutoModel. The idea is to leverage Koa agents for complex sales and service tasks. Salesforce said that in its CRM Benchmark, a model benchmark that includes a suite of real-world tasks like updating opportunities,…

Anthropic’s Dario Amodei and Nvidia’s Jensen Huang Take Their AI Safety Fight to Dreamforce

Two of AI's most influential executives are on opposite sides of a debate.

The AI Inference Revolution Is Here

Since about 2020, AI has largely focused on training bigger and better models. Large language models (LLMs) ballooned from millions of parameters to trillions. This proved effective: The largest version of OpenAI’s GPT-3, released in 2020, correctly answered just 43.9 percent of questions on a popular knowledge-and-reasoning benchmark. Just four years later, GPT-4o reached a score of 88.7 percent on the same exam, effectively matching those of human experts. Advanced AI labs are still training ever larger models, but that training has somewhat receded to the background of the AI conversation. In 2026, inference—the use of trained models to produce code, write essays, or make images of ourselves as elves—has come to the forefront. “It’s like training is yesterday’s news,” says Matt Kimball , principal data-center analyst at Moor Insights & Strategy. “All that any chief information officer wants to talk about is inference.” Nvidia CEO Jensen Huang, speaking at the company’s GTC 2026 conference, touted this change as the “ inflection point of inference .” Part of what’s caused the shift is very simple: LLMs are becoming useful, so people are using them. On top of that, many models on the market today are reasoning models. In response to a user’s query, they run inference not just once but multiple times, reprompting themselves in a process called chain of thought . Reasoning models generate longer outputs, and models with high reasoning effort can produce up to 20 times as much…

Salesforce debuts Koa, a specialized model built to reason about CRM data

Salesforce Inc. said today at its annual user conference Dreamforce that it has partnered with Nvidia Corp. to train and release Koa, a specialized artificial intelligence model that’s custom built for reasoning about customer relationship management data. Based on Nvidia’s Nemotron model architecture, Koa is designed specifically to help AI agents reason through complex, multistep […] The post Salesforce debuts Koa, a specialized model built to reason about CRM data appeared first on SiliconANGLE .

Salesforce and Nvidia’s new reasoning model is everything the AI labs should fear

Salesforce Koa is built on Nvidia's open-weight Nemotron model and is trained to do sales, marketing, and customer-support tasks.

Political and business leaders back AI

US President Donald Trump called Nvidia CEO Jensen Huang during a live panel discussion to argue that worries about AI’s impact were “all a hoax.”

Comment on NVIDIA Neural Talking-Head Synthesis Makes Video Conferencing 10x More Bandwidth Efficient by Alesha Gasas

Wedding footage becomes more than a collection of clips when editing gives each moment a natural place in the story. From nervous preparations and heartfelt vows to laughter, speeches, and the final dance, careful pacing helps emotions flow together. Music, transitions, color, and thoughtful scene selection can turn ordinary recordings into a film that feels personal and memorable. Professional editors such as https://www.sem-media.net/ can shape raw footage into polished wedding films while preserving the couple’s unique style. The result is a visual story that brings genuine memories back to life for years.

Nvidia, Palantir und Cisco bauen KI-Stack für Behörden

Palantir, Nvidia und Cisco bieten eine gemeinsame KI-Referenzarchitektur für sensible Daten und regulierte Umgebungen an.

Heart of the Matter: How a Major Children’s Hospital Uses Open Source NVIDIA AI for Cardiac Care

Nvidia hollowed out Groq. Here's what happened to the company left behind.

In a $20 billion deal last year, Nvidia took what made Groq special. The AI cloud startup left behind bets that special doesn't matter anymore.

AI-linked stocks slide after tech bosses call for slowdown in ‘reckless’ development

Donald Trump dismisses attempts to increase controls on artificial intelligence as ‘sick conspiracy’ AI -linked stocks tumbled on Monday after the bosses of Anthropic, OpenAI and SpaceX called for a slowdown in AI “reckless” development , citing fears the technology could soon run out of control. Shares in the semiconductor designer Nvidia – the world’s most valuable company – were down 3.3% by market closing in New York City, while Advanced Micro Devices (AMD) slid 4% and Micron Technology and Sandisk shares slumped by 5%. The tech-heavy Nasdaq index fund was down 0.5% by the end of the day. Continue reading...

Nvidia CEO Jensen Huang tells Trump ‘we’re not going to let [an AI slowdown] happen’

Though Elon Musk and Sam Altman have supported Dario Amodei's calls to slow the pace of AI development, Jensen Huang seems to feel differently.

Trump called Nvidia CEO Jensen Huang mid-interview to rip AI doomerism: 'The robots will not be taking over'

Nvidia CEO Jensen Huang said AI doomer predictions aren't grounded in science and got a call from President Donald Trump to weigh in.

AI infrastructure company Cornelis raises $205M to chip away at Nvidia’s dominance

The company also announced a product called Active Compute Fabric, a network technology that targets the fact that much GPU time is wasted waiting for data to arrive.

Jensen Huang puts Trump on speakerphone onstage to announce robots won’t take over the world

Nvidia CEO Jensen Huang took a call from President Trump on Monday while onstage at the All-In Podcast's All-In Summit. It's not the first time Huang has taken a call from the president during work, but this time he put Trump on speakerphone before a big crowd. During the call, the president launched into his […]

Perplexity Portable Computer Is Now Available on Windows, Powered by NVIDIA RTX

As local models become more capable, AI agents can handle more work directly on a PC while keeping sensitive information on the device. Portable Computer is a local version of the agent Perplexity Computer that plans and carries out multistep tasks. Accelerated by NVIDIA GPUs, it uses local models to analyze data, bring together information […]

How OpenAI Used Its Own LLMs to Design Its Jalapeño Chip

On 25 August, OpenAI fully unveiled Jalapeño, the company’s debut AI accelerator chip. Jalapeño delivers up to 13.4 petaflops of 4-bit compute and accesses 232 gigabytes of the most advanced memory available, linking to it at a blazing 15.4 terabytes per second. Benchmarks cited by OpenAI show that Jalapeño can reduce end-to-end latency (the time between prompt to last token) by up to 3.6 times when compared to Nvidia’s GB300 —a chip the company currently relies on—and do so while consuming less power. Whether these figures translate into real-world gains once Jalapeño enters widespread service in OpenAI’s inference fleet remains to be seen, but performance is only half the story. The other half is how the chip was designed—a process which, as you might expect, was accelerated by OpenAI’s large language models (LLMs). Jalapeño moved from first architecture concept to first silicon in under 20 months. Only nine months separated the first RTL—the register-transfer level code defining the chip’s logic—from tape-out, when the finished design goes to manufacturing. That’s a rapid timeline, yet experts believe it could soon look slow as LLMs improve and become more deeply integrated into chip design tools. OpenAI, unsurprisingly, is bullish about the opportunities. “The models are giving superpowers to our engineers,” says Richard Ho , vice president of hardware at OpenAI. “Our engineers are still driving the work. They’re still the final arbiter of what’s going on. But they can d…

3 ex-Apple researchers want to make AI less awkward. Lightspeed, Accel, and Nvidia are giving them $50 million to do it.

A startup bringing emotional intelligence and conversation to AI models has just raised $50 million.

What happens when you tell Jensen Huang you're quitting Nvidia

Nvidia CEO Jensen Huang gives blunt feedback to departing employees, influencing startups like Flexion Robotics and INT21 with direct insights.

Vodafone Egypt and Cassava Launch Egypt’s First AI Factory as Cairo Courts Multiple Infrastructure Partners

Vodafone Egypt and Cassava Technologies have launched Egypt’s first AI factory, offering government entities and businesses GPU-as-a-Service on NVIDIA hardware with data hosted and processed inside the country. The facility forms part of Vodafone Egypt’s plan to invest more than EGP 20 billion ($300 million) in the current fiscal year, building on more than EGP [...]

Nvidia wants to pour up to $10 billion into Anthropic's record-breaking IPO

Nvidia is in talks to invest up to $10 billion in Anthropic's planned IPO, Reuters reports. At a target valuation of $2 trillion, it would be the largest IPO in history. Most of that money will likely end up right back at Nvidia in chip orders. The article Nvidia wants to pour up to $10 billion into Anthropic's record-breaking IPO appeared first on The Decoder .

Nvidia's Groq acquihire is on the DOJ's radar, but it's already too late

Even if regulators did somehow unwind the $20B deal, there's a growing list of alternatives ready to take Groq's place, no merger required

What is AGI? How China’s AI firms are catching up as OpenAI Astra sparks debate

Nvidia CEO Jensen Huang’s declaration that artificial general intelligence (AGI) has arrived following the release of OpenAI’s latest model, Astra, has ignited debate over whether AI’s holy grail is now reality. As China races to close the gap with the US, leading Chinese AI companies are declaring their ambitions to pursue AGI, even as Beijing appears to maintain a cautious stance towards the concept. Here is a primer on what AGI means, where top Chinese AI developers stand, and how Chinese...

Nvidia will use Palantir to gain insight its supply chain

Nvidia will use Palantir’s Foundry software to analyze its global network of suppliers and partners for supply chain risks — and Palantir will incorporate Nvida’s Nemotron open AI model into its existing AI software stack. The deal will enhance both companies’ offerings, they said: Nvidia will use Palantir’s AI stack to optimize its complex supply chain ecosystem, helping teams identify potential constraints, evaluate alternatives more quickly and allocate materials based on end-to-end production impact. The companies are already close partners . At the same time, they said, Nemotron will bring more supply-chain visibility to the platform that Palantir sells to other companies, enabling its customers to build their own AI stacks by training Nemotron with their own data. They will be able to use the system to manage supply constraints and assess trade-offs. Nvidia CEO Jensen Huang highlighted the complexities of the supply chain involved in building modern AI data centers, saying, “Nvidia and Palantir are transforming this vast operational graph into sovereign intelligence — combining Nvidia Nemotron models with Palantir’s Ontology to reason, plan and orchestrate the journey from wafer to token.” The news release announcing the deal was riddled with references to sovereignty, a concern for enterprises as governments attempt to unwind decades of globalization and build to a new world order based on coercion rather than cooperation.

heise+ | Nvidia investiert in zahlreiche KI-Firmen: Besteht Monopolgefahr?

Nvidia liefert der Tech-Industrie nicht nur KI-Chips. Durch seine Milliardeninvestitionen macht sich der Konzern in der KI-Wertschöpfungskette unverzichtbar.

Chip competition heats up for Nvidia

A Chinese chip firm surged 180% in its stock-market debut, spotlighting the growing list of challengers to Nvidia’s dominance.

NVIDIA's SoL-Pi Slashes Coding Agent Token Use by 49%

NVIDIA Labs released SoL-Pi, a coding agent extension that cuts token cost by roughly one-third using four mechanisms discovered by auto-research loops.

Enflame shares soar 179% in Shanghai debut as Nvidia challenger taps investor fever for AI

Enflame Technology, one of the major challengers to Nvidia in China, saw its share price surge 179 per cent in its Shanghai trading debut on Friday, giving the Tencent Holdings-backed artificial intelligence chipmaker a market capitalisation of 170.9 billion yuan (US$25.5 billion). The Shanghai-based company opened at 410 yuan, up from its issue price of 142.18 yuan. It surged as much as 234 per cent to 475 yuan during the day, before closing at 397 yuan. The performance reflects continued...

Jensen Huang explains why Nvidia will grow an astounding 70% next year

Nvidia has its finger in every pie, and sees another year of plenty in its future, Jensen Huang says. But, he insists, its deals are not circular.

NVIDIA's HorizonRelight Fixes Flickering Lights in Long AI Videos

NVIDIA and USC present HorizonRelight, a diffusion transformer method that keeps lighting stable across long videos by propagating context between chunks.

Nvidia CEO Jensen Huang says cybersecurity is AI's next blockbuster app

Nvidia's Jensen Huang says AI will transform cybersecurity. The chip giant recently made strategic partnerships with CrowdStrike, Cisco, and Palantir.

Together AI's ThunderKittens Hits 22.4 PFLOPS on NVIDIA's Rubin

Together AI ported its ThunderKittens kernel framework to NVIDIA's Vera Rubin NVL72, hitting 22.4 PFLOPS on NVFP4 GEMMs and rivaling cuBLAS.

Skild AI Taps NVIDIA Physical AI to Teach Robots New Tasks From a Single Video

Manufacturing floors, warehouses and production lines rarely stay fixed — tasks change, layouts shift and new products arrive, and most robots can’t keep up without significant reprogramming. Skild AI’s new S1 robot foundation model helps address this, designed to learn previously unseen, long-horizon tasks from a single video demonstration. The model, launched last week, uses […]

Physical AI Takes the Wheel: How the World’s Robotaxi Leaders Are Building With NVIDIA Technologies

The global robotaxi market — physical AI’s first commercial breakthrough — is projected to reach $400 billion by 2035, with over 6 million commercial vehicles in operation as driverless fleets are already moving people through some of the world’s busiest and most complex streets. Deploying a driverless vehicle is one challenge. Scaling a fleet is […]

ARM-Kerngeneration C2: Lumex ist schon wieder Geschichte

ARM aktualisiert seinen Prozessor-Baukasten mit neuen CPU-Kernen und KI-Funktionen in der GPU. Letztere erinnern an AMD, Nvidia und Intel.

d-Matrix Adopts NVIDIA NVLink Fusion for Rack-Scale XPU Deployment

AI inference chipmaker d-Matrix today announced it will use NVLink Fusion to connect its next-generation Raptor XPUs to NVIDIA’s AI infrastructure platform — joining a growing roster of ecosystem partners. By connecting Raptor to NVIDIA NVLink scale-up and Spectrum-X scale-out networking, the NVIDIA MGX rack architecture and the broader NVIDIA AI platform, NVLink Fusion gives […]

d-Matrix drinks the Nvidia Kool-Aid with NVLink Fusion and MGX rack designs

AI infrastructure startup joins Qualcomm, Arm, Marvell, Amazon, Fujitsu, and MediaTek as NVLink true believers

Nvidia and Palantir team up to run supply chains with AI, starting with Nvidia's own million-part operation

Nvidia and Palantir want to run supply chains with AI. The article Nvidia and Palantir team up to run supply chains with AI, starting with Nvidia's own million-part operation appeared first on The Decoder .

NVIDIA Brings Real-Time AI to Broadcast, Sports and Global Streaming at IBC

At the IBC conference, running Sept. 11-14 in Amsterdam, the creative, technology and business communities are coming together to turn ideas into action and discuss innovations across the media and entertainment industries. More than 44,000 attendees from 170+ countries are gathering to explore 1,300+ exhibitions in 14+ halls and outdoor spaces, with over 600 speakers […]

엔비디아, GPU 커널까지 러스트로 개발하는 ‘CUDA 러스트’ 공개...안전한 AI 인프라 구축

엔비디아가 AI 시스템의 핵심 영역인 GPU 커널 개발에 프로그래밍 언어 러스트(Rust)를 본격 도입한다. 기존에는 러스트로 CUDA 커널을 호출하는 수준에 머물렀으나, 앞으로는 GPU 커널 자체를 러스트로 직접 작성해 네이티브 PTX 코드로 컴파일하는 ‘CUDA 러스트’를 추진하며 소프트웨어 생태계 전환에 나섰다.엔비디아는 8일(현지시간) CUDA 러스트를 공개하고 2027년 이후까지 관련 기술을 지속 발전시킬 계획이라고 밝혔다. CUDA C++와 CUDA 파이썬이 구축해 온 엔터프라이즈급 개발 환경에 러스트를 추가해 선택지를

Vodafone, Cassava launch Egypt’s first national AI factory

Partnership targets sovereign AI infrastructure; brings NVIDIA GPUs

Comment on Jensen Huang Serves Up the A100: NVIDIA’s Hot New Ampere Data Centre GPU by Sarah William

Jensen really knows how to put on a show! Pulling a freshly baked DGX A100 motherboard out of his kitchen oven is definitely one of the most memorable keynote moments we have had in years. Beyond the entertaining presentation, the actual Ampere architecture specs are staggering. Packing over 54 billion transistors onto a 7-nanometer processor is a massive hardware milestone, and that up to 20x performance leap over the previous Volta generation is going to completely reshape AI training and data analytics. I am especially impressed by the new Multi-instance GPU capability. Being able to partition a single A100 into seven isolated GPU instances provides exactly the kind of workload flexibility that modern cloud infrastructure needs to maximize scale and efficiency. If anyone here is planning an enterprise server upgrade or needs to source heavy duty data center components, I highly recommend checking out https://orangehardwares.com/ , you can also check out NEWEGG, Toms Hardware for reliable inventory. It is truly exciting to see what Nvidia has been cooking up!

Open-source AI developer Mistral closes €3B funding round

French artificial intelligence lab Mistral AI SAS today announced that it has raised €3 billion, or about $3.49 billion, in funding. Samsung Electronics Co. Ltd. led the investment. It was joined by more than two dozen other backers including Salesforce Ventures, Nvidia Corp. and ASML Holdings NV, which led Mistral’s last round. The startup is […] The post Open-source AI developer Mistral closes €3B funding round appeared first on SiliconANGLE .

NVIDIA's CUDA Python 1.0 Makes Python a First-Class GPU Citizen

NVIDIA ships CUDA Python 1.0 with semantic versioning, a shared cuda.core foundation, and PyTorch and CuPy already building on it.

Cohere's Open-Source Megakernel Beats vLLM by 1.58x on H100

Cohere open-sourced a serving engine that runs the entire LLM decode step as one persistent CUDA kernel, hitting 1.58x vLLM throughput on H100.

Inception's Mercury 2.5 Hits 1,107 Tokens per Second, Beating Autoregressive Models

Inception's new diffusion-based LLM hits 1,107 tokens per second on NVIDIA GPUs while boosting quality 40% over Mercury 2.

Benchmarking small LLM inference on SageMaker AI: G7 vs G5 and G6

Benchmark two 30B Mixture-of-Experts models, Qwen3-Coder-30B and NVIDIA Nemotron-3-Nano-30B, across G5, G6, G6e, and G7 GPU instances on Amazon SageMaker AI. Compare throughput, latency, and cost-per-token, and see how G7's NVIDIA Blackwell GPUs deliver measurable price-performance gains for real-time LLM inference.

Comment on Moody Moving Faces: NVIDIA’s SPACEx Delivers High-Quality Portrait Animation with Controllable Expression by Jack Taylor

As technology continues to create more interactive and expressive experiences, the appeal of hands-on sensory play remains just as powerful. NeeDoh offers a simple, tactile way to relax, fidget, and engage the senses, giving kids and adults an enjoyable break from the increasingly digital world around them.

AI won’t kill SaaS

Nvidia CEO Jensen Huang argues it’s the “most illogical thing in the world” to believe AI will kill SaaS, and says the markets “got it wrong” in sending SaaS stocks tumbling. Why “illogical”? Because, as analyst Benedict Evans stresses, the fact that everyone can now easily spin up code actually doesn’t solve any SaaS problems, because creating code and tools is the easy part: “The hard part is knowing that you need a tool for this in the first place and then knowing what the tool should do.” If that’s true, then what Shopify is doing with Sidekick is potentially revolutionary by embracing and extending the traditional SaaS model. In December, Shopify introduced custom app generation through Sidekick . A merchant (Shopify customer) describes a tool, and Sidekick writes the code, using Shopify’s interface components and connecting to its Admin API. It’s a cool option and has been very popular. Shopify says merchants created almost 4,000 custom apps in the first three weeks following the release. This isn’t surprising: Shopify is delivering the customization customers have long wanted from enterprise SaaS while ensuring they still enjoy the comfort of ongoing support and platform stability. I suspect we’ll see more enterprise SaaS like this, despite silly predictions that AI would kill SaaS. Cheaper code gives customers a way to fix the things they dislike about an application without replacing everything they do like. For a vendor willing to accommodate that, AI could make it…

Chinas KI-Entkopplung: DeepSeek setzt mit neuer Großbestellung auf Huawei

DeepSeek will mindestens 160.000 Huawei-Chips statt der bisherigen Nvidia-Chips in einem Rechenzentrum verbauen. Trainiert werden soll damit aber vorerst nicht.

Nvidia's Jensen Huang says 'AGI has arrived' and congratulates OpenAI

Nvidia CEO Jensen Huang made the comment on Sunday, days after OpenAI released Astra, its newest and most powerful AI model.

Jensen's purchase of a new toy could reshape the entire AI industry

This week on The Kettle we weigh in on Nvidia's Hugging Face acquisition and why it could spell a new, more fragmented and siloed era of AI development

Could NVIDIA's purchase of Hugging Face boost the EU's AI sovereignty?

The deal, marking NVIDIA's increased focus on open-AI models, is likely to draw significant regulatory concern from the EU due to its size and implications for the bloc's digital and AI sovereignty.

py/cuTAGI: An Open-Source Library for Tractable Approximate Gaussian Inference in Bayesian Neural Networks

This paper introduces pyTAGI, a Python wrapper, and cuTAGI, its high-performance C++/CUDA backend, implementing Tractable Approximate Gaussian Inference (TAGI) for neural networks. TAGI treats all network quantities as Gaussian random variables and derives closed-form expressions for prior/posterior expected values, variances, and covariances, enabling analytic Bayesian learning without relying on gradient descent or backpropagation. The libraries mimic PyTorch's sequential interface, allowing users to define models by stacking layers in order and performing uncertainty-aware Bayesian inference. Beyond epistemic uncertainty, it also allows quantifying heteroscedastic aleatoric uncertainty. cuTAGI's custom CPU/GPU kernels and distributed-data-parallel support via NCCL/MPI deliver competitive runtimes, while pyTAGI's pip-installable frontend and MIT-licensed GitHub repo facilitate community adoption and extension. Version 0.2.1 already supports a comprehensive suite of layers and activations; future work will add eager execution, further kernel optimizations, attention mechanisms, and advanced covariance factorization. Together, py/cuTAGI offer an efficient, open-source foundation for the analytic treatment of Bayesian deep learning.

Comment on Revolutionising Graphics: Nvidia Unveils Turing Architecture With Real-Time Ray Tracing by John Mitchell

Nvidia’s Turing launch really marked an important shift because it showed how dedicated hardware could make real-time ray tracing practical rather than just an ambitious concept. What stands out most is the combination of RT cores and Tensor cores, since AI-assisted rendering has become just as important as raw graphical power. It is interesting to see how specialized technology solves different problems across industries; even something seemingly unrelated, like diagnosing the source of a leak during roof repair new jersey , benefits from using the right tools instead of relying on guesswork. Turing helped push graphics toward a future where realism and intelligent computing work together.

Meta's AIRA₃ Beats 4,000 Human Teams to Win Kaggle Gold

Meta's next-generation autonomous research agent AIRA₃ placed 8th of roughly 4,000 human teams in an NVIDIA-run Kaggle contest to fine-tune Nemotron.

NVIDIA's Nemotron Beats the Best Human at the Coding Olympics

NVIDIA's fine-tuned Nemotron system scored 535.4 out of 600 at IOI 2026, topping the best human contestant under identical contest conditions.

AGI is whatever you want it to be

OpenAI announced its next big model, GPT-6 Astra, and also, by the way, that "the AGI era" is here now. Today on The Vergecast, we've got an all-star panel to break down the news of the week. First, senior AI reporter Hayden Field joins us to talk about our supposed AGI era and Nvidia's acquisition […]

Build a Physical AI model factory with NVIDIA Cosmos 3 on SageMaker HyperPod

Building a Physical AI system takes a continuous pipeline, not a single training job. This post shows how to run that model factory (synthetic data generation, post-training, and closed-loop evaluation with NVIDIA Cosmos 3) on a persistent, resilient Amazon SageMaker HyperPod cluster on Amazon EKS, with GPU goodput as the metric that matters.

Alienware’s refurbished 16 Aurora is almost $200 off at Woot

Gaming laptop deals aren’t what they used to be (stares daggers at RAMageddon), which is why I consider Woot’s deal on a refurbished Alienware 16 Aurora gaming laptop with Nvidia’s RTX 5050 a pretty good deal at $927 for new Woot customers (with code WOOTALIEN used at checkout). It costs $1,029 for returning Woot shoppers, […]

Nvidia PAIR: KI-Inferenz auf Heimgeräten verteilen

Nvidia hat eine Open Source Software veröffentlicht, die Privatgeräte zu einem Computing-Netzwerk für lokale KI-Inferenz verbindet.

Nvidia has built a $99 billion equity portfolio from almost scratch in 2 years

Nvidia's equity portfolio ballooned from around $2 billion to nearly $100 billion in two years as the AI chipmaker backed several tech peers.

Nvidia bags Hugging Face, AI models play leapfrog and CrowdStrike doubles down on AI

Perhaps it’s no surprise that Nvidia ended up embracing open artificial intelligence model archive Hugging Face this week following more than a week of rumors. Even at almost $13 billion, it may end up being a steal — especially for a company that had $24 billion in cash flow last quarter alone. The reason: Hugging […] The post Nvidia bags Hugging Face, AI models play leapfrog and CrowdStrike doubles down on AI appeared first on SiliconANGLE .

Nvidia lets you build your own AI clusters locally with PAIR software

Nvidia has released a free tool that will enable users to build an AI inferencing cluster from disparate PCs on the same network, accessible from a single interface. Released as a beta, Nvidia Personal AI router (PAIR) connects devices running Windows, macOS or Linux to process AI inferencing workloads privately. While the system is aimed primarily at home users, it could find favour with enterprises looking to put idle desktop compute capacity to use. PAIR works with DGX Spark desktop supercomputer s, PCs containing RTX GPUs, and some MacOS devices. The systems in the cluster run tasks in parallel, but PAIR does not turn them into a virtual GPU, Nvidia said. The beta version of Nvidia PAIR is available for download now. This article first appeared on Network World.

Switchyard: NVIDIA’s Open Source Routing Library

Stop sending every AI request to your most expensive model. See how intelligent routing can cut cost and latency without sacrificing much quality.

Nvidia weitet DLSS 5 auf RTX-40-Grafikkarten aus

Nvidia will DLSS 5 offiziell auch auf RTX-40-Karten bringen – wo eine inoffizielle Mod-Version schon läuft. Die Rechenkosten des KI-Modells bleiben enorm.

NVIDIA confirms it will acquire Hugging Face for $12.9 billion

NVIDIA will acquire Hugging Face for $12.93 billion, gaining a strategic foothold in the open AI ecosystem while keeping the platform open to multiple models, clouds and hardware providers. The post NVIDIA confirms it will acquire Hugging Face for $12.9 billion appeared first on MEDIANAMA .

Nvidia wants your home network to work like a mini data center for local AI

Nvidia's PAIR (Personal AI Router) automatically spreads local AI requests across all available devices on a home network, cutting wait times for parallel agent tasks. The article Nvidia wants your home network to work like a mini data center for local AI appeared first on The Decoder .

Nvidia will officially bring DLSS 5 to older GPUs — but won’t give gamers full control

Officially, Nvidia's controversial DLSS 5 AI rendering was supposed to launch this evening with only a single game, only on Nvidia's latest RTX 50 GPUs, and with developers in full control of their artistic vision. But unofficially, modders have already ported a leaked version of DLSS 5 to run on just about anything while cranking […]

Nvidia PAIR makes it easy to create a household data center for running agentic AI tasks

Nvidia Corp. is targeting artificial intelligence agent enthusiasts with a new local distributed clustering tool called the Personal AI Router. It enables them to use any idle Mac computers or PCs lying around the house to run small language models on demand and accelerate agentic workloads with the assistance of sub-agents. It was announced at IFA […] The post Nvidia PAIR makes it easy to create a household data center for running agentic AI tasks appeared first on SiliconANGLE .

Nvidia’s Hugging Face deal is a bet on open models — and proof it’s no longer just a chip company

As Nvidia Corp. announced this morning that it has agreed to acquire Hugging Face Inc. for $12.93 billion — one of the largest acquisitions in the company’s history — Chief Executive Jensen Huang promised that the platform will retain its brand, its leadership and, according to both companies, its neutrality. “Hugging Face will remain an […] The post Nvidia’s Hugging Face deal is a bet on open models — and proof it’s no longer just a chip company appeared first on SiliconANGLE .

Hugging Face is too important to fall into Nvidia's hands

$12.9 billion deal will inevitably cement Nvidia's market dominance and harm competition in the process. Regulators should take note

Looking forward to this ecosystem with open models continuing to flourish and grow with NVIDIA and Hugging Face, and the continued partnership!

The post Looking forward to this ecosystem with open models continuing to flourish and grow with NVIDIA and Hugging Face, and the continued partnership! appeared first on Source .

What Nvidia’s $13B acquisition of Hugging Face means for AI model choice

When Nvidia said Thursday that it plans to pay $13 billion to acquire Hugging Face, the question arose of whether the open AI platform would remain open when it becomes a unit of Nvidia. And the current lack of a single viable open alternative that does everything Hugging Face does for enterprises adds further complications for CIOs. Rumors of the pending deal have been circulating for at least a week. In its announcement, Nvidia said , “Hugging Face will remain an open platform for the entire AI ecosystem. Developers will choose the models they want, the frameworks they want, the clouds and inference service providers they want and the computing platforms they want. Nvidia compute will not be required to build on or deploy through Hugging Face.” It added that Hugging Face will continue to support open source and open weight models from every model builder, and “continue to support multi-cloud and multi-accelerator development and deployment, so builders can use the hardware and infrastructure that best fit their work.” Hugging Face CEO Clément Delangue took to his X account to also reassure customers, noting, “open-source AI is at an inflection point” and pointing out that, for the business to scale, it needs “more compute, more support, more collaboration and more visibility. That’s why we went to talk to [Nvidia CEO] Jensen [Huang], who offered to do exactly that with us.” Preserving the Hugging Face team Nvidia is also attempting to retain some of the Hugging Face workfo…

What Nvidia’s $13B acquisition of Hugging Face means for AI model choice

When Nvidia said Thursday that it plans to pay $13 billion to acquire Hugging Face, the question arose of whether the open AI platform would remain open when it becomes a unit of Nvidia. And the current lack of a single viable open alternative that does everything Hugging Face does for enterprises adds further complications for CIOs. Rumors of the pending deal have been circulating for at least a week. In its announcement, Nvidia said , “Hugging Face will remain an open platform for the entire AI ecosystem. Developers will choose the models they want, the frameworks they want, the clouds and inference service providers they want and the computing platforms they want. Nvidia compute will not be required to build on or deploy through Hugging Face.” It added that Hugging Face will continue to support open source and open weight models from every model builder, and “continue to support multi-cloud and multi-accelerator development and deployment, so builders can use the hardware and infrastructure that best fit their work.” Hugging Face CEO Clément Delangue took to his X account to also reassure customers, noting, “open-source AI is at an inflection point” and pointing out that, for the business to scale, it needs “more compute, more support, more collaboration and more visibility. That’s why we went to talk to [Nvidia CEO] Jensen [Huang], who offered to do exactly that with us.” Preserving the Hugging Face team Nvidia is also attempting to retain some of the Hugging Face workfo…

Nvidia confirms $12.9B acquisition of AI hosting platform Hugging Face

Nvidia Corp. today confirmed that it has agreed to buy Hugging Face Inc. for just over $12.93 billion. CNBC reported that the acquisition talks began a few weeks ago. Rumors that a deal was in the works surfaced last Monday, when sources tipped off Business Insider about the discussions. Two days later, The Information reported […] The post Nvidia confirms $12.9B acquisition of AI hosting platform Hugging Face appeared first on SiliconANGLE .

Hugging Face CEO says 'planets aligned' for Nvidia deal, aims to reach 100M users

When the moon is in the seventh house...

Nvidia to buy developer platform Hugging Face in $12.9bn deal

Semi-conductor giant bets that support for open AI models could offset potential slowdown in demand for chips Nvidia will buy the popular developer platform Hugging Face for nearly $13bn, betting that support for ⁠open AI models could offset a potential slowdown in demand for the semiconductor giant’s chips. Shares ⁠in Nvidia were ⁠slightly lower ​after the $12.93bn (£9.57bn) deal – which ranks among its biggest ever – was announced for the database of AI models on Thursday. Continue reading...

Sparks Fly: NVIDIA Accelerates Local AI at IFA 2026

Frontier intelligence is going local. At IFA 2026, NVIDIA, Microsoft and its partners are teaming up to provide faster inference and new tools that make agents easier to set up and run locally on NVIDIA hardware. New compact NVIDIA RTX Spark Windows PCs are also coming in October to give AI enthusiasts, developers and creators […]

Nvidia launches free tool that links idle computers into a personal AI data center

Nvidia is announcing its new Personal AI Router (PAIR), a free tool that syncs up your home computers for tackling local AI inference tasks with tools like Ollama and LM Studio. Let's get the obvious thing out of the way, despite what its name might imply: PAIR is not a hardware router. It's open-source software […]

Lenovo’s 4 most innovative laptops from IFA 2026 – including its most practical rollable yet

Lenovo showed off its new Yoga Pro 9n with the Nvidia RTX Spark and a range of colorful new Neo competitors for $699.

There's an Easter egg hiding inside the $12.9303 billion price tag of the Nvidia-Hugging Face deal

"Special congrats if you find the Hugging Face and Nvidia references hidden in our $12,930,300,000 acquisition price," cofounder Thomas Wolf wrote.

Nvidia confirms $12.93BN purchase of Hugging Face

Nvidia has today confirmed its acquisition of open-source AI model repository Hugging Face for $12.93bn, as it makes a big bet on open-source AI models and continues to plough billions into the broade...

Why Nvidia wants Hugging Face — and a bigger say in the future of AI

Nvidia bought Hugging Face for $12.9 billion. The deal boosts Nvidia's open-source strategy, challenging OpenAI and Anthropic.

Nvidia buys the front door to open AI as closed labs increasingly design their own silicon

Nvidia plans to acquire Hugging Face for about $12.9 billion, securing the central platform for open AI models. More than 18 million developers and 200,000 companies use the hub. CEO Jensen Huang promises to keep the platform open and hardware-neutral, but the deal also hands him a powerful distribution channel for compute. The article Nvidia buys the front door to open AI as closed labs increasingly design their own silicon appeared first on The Decoder .

Nvidia übernimmt Hugging Face für 12,93 Milliarden US-Dollar

Nvidia kauft Hugging Face für 12,93 Milliarden US-Dollar. Die Plattform für offene KI-Modelle soll offen bleiben, verspricht das Unternehmen.

Nvidia to buy Hugging Face for nearly $13 billion

Hugging Face has exploded in popularity, providing an open-source hub for collaborative machine learning.

Figure Bets $6B on NVIDIA Vera Rubin GPUs to Scale Humanoid Robots

Figure locks in a $3.5B compute commitment scaling past $6B, targeting up to 100,000 Vera Rubin GPUs to train its Helix humanoid AI.

Nvidia buys Hugging Face for $12.9B, promises not to squeeze too hard

GPU giant pledges to keep the model hub open to the entire AI ecosystem

‘NBA 2K27’ With NVIDIA DLSS 5 Leads 28 New Games Coming to GeForce NOW

September is here with 28 more games streaming on GeForce NOW this month, led by a slam dunk: NBA 2K27 with the NVIDIA DLSS 5 3D-Guided Neural Rendering feature. Through NVIDIA’s close collaboration with Visual Concepts and 2K, DLSS 5 brings a new level of lifelike lighting and material detail to the court — tuned […]

Nvidia to buy open-source AI hub Hugging Face for $12.9bn

Nvidia is buying Hugging Face, the platform millions of developers use to build AI, for $12.9bn (€11.1bn) — its second-biggest deal ever.

Nvidia RTX Spark ‘Superchip’: The First AI PCs Are Here

At IFA 2026, Nvidia and its partners showed off the first RTX Spark-powered laptops and mini PCs, designed to run AI models right on your computer.

Nvidia’s Hugging Face Acquisition Is a $12.9 Billion Bet on Open-Source AI

The long-rumored deal will give the chip giant access to—and help it promote—a huge repository of open-source AI models and data sets.