Topic: #nvidia

In a blog post, NVIDIA describes how French companies deploy agentic computing across space, financial services, the public sector and research. The Altair-1 satellite carries Jetson modules running Mistral models for Earth observation and belongs to a planned constellation of 50 satellites. ai from LINAGORA and Docaposte becomes available to more than 2,500 public organizations through a framework agreement.

Geeky Gadgets looks at how Apple's M5 Ultra in the Mac Studio stacks up against Nvidia GPUs such as the RTX 5090 for local AI and pro workloads. The focus is the 96GB unified memory architecture, which lets CPU and GPU share the same memory pool without the usual transfer bottlenecks. According to the article, the chip leads in rendering workflows and suits AI development, 3D and video production.

Anti-AI campaign groups report a surge in membership following a series of AI safety alerts and apocalyptic warnings. The Guardian followed a London cell of Pull The Plug, one of the fastest-growing groups, as four members planned to disrupt a tech industry dinner featuring a senior Nvidia executive. For some, like a 28-year-old bartender, it is their first direct action.

Nvidia is introducing a 64GB version of its DGX Spark local AI workstation that's tailored for a new generation of highly intelligent yet compact local models. Starting at $4999, the more affordable configuration is otherwise identical to the original 128GB Spark and its GB10 siblings.

Federal prosecutors arrested a California man on Thursday on charges of smuggling computer servers containing about $300 million worth of Nvidia AI chips to China in violation of US export controls. The case shows how strong demand for high-end AI hardware remains in China despite Washington's restrictions.

OpenAI introduced GPT-6.1 Sol during its 2026 Dev Day, drawing attention for its ability to match the performance of Astra, a prominent AI system, at just one-fifth of the cost. According to Universe of AI, the model is priced at $2 per input and $10 per output, making it a more accessible option for users […] The post OpenAI’s GPT-6.1 Sol Matches Astra Capabilities at Dev Day 2026 appeared first on Geeky Gadgets.

NVIDIA’s introduction of the NVFP4 format for its Blackwell GPUs offers a compact four-bit floating-point representation designed to optimize AI workloads. As highlighted by The Stack, this format aims to improve both computational performance and memory efficiency, potentially doubling processing speeds in certain scenarios.

The heads of the biggest AI labs — Google, Anthropic, Meta, OpenAI, SpaceXAI, and Nvidia — went to Washington and signed the 'Joint Commitment on Frontier Responsibilities,' promising to develop their own models safely. Trump says that it's the best way to move forward with AI as it balances progress with safety.

Donald Trump will hold a luncheon on Tuesday with the chief executives of Nvidia, Anthropic and Palantir to discuss artificial intelligence risks. OpenAI President Greg Brockman is also expected to attend. Trump is hosting the event together with House Speaker Mike Johnson, and Bloomberg reports on the meeting.

More AI is the surest fix for an emerging AI security crisis, according to industry executives and researchers. Axios reported that researchers are investigating tens of thousands of problematic AI security incidents rather than the dozens made public, raising doubts about whether AI leaders control their technology.

Nvidia on Monday unveiled a new security platform that the chipmaker says can stop AI agents from going rogue, following a series of incidents involving AI agents at top companies. The Open Agent Safety Platform is designed to monitor agents and quarantine them within milliseconds if they try to escape their boundaries.

Nvidia is launching a new safety platform designed to contain and monitor AI agents, responding to a wave of rogue hacking incidents first reported by Reuters. According to Nvidia's Monday announcement, the Open Agent Safety Platform can quarantine agents that try to escape their boundaries within milliseconds. It is built on Nvidia's open-source OpenShell software, which runs on the company's Vera AI CPU.

Jensen Huang dismisses warnings from former Anthropic researcher and others as ‘doomsday narratives’ Business live – latest updates 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…

Nvidia CEO Jensen Huang told CBS Sunday Morning there is a "0% chance" that AI ends the world, and called it "unnecessary" and "irresponsible" to scare people about its dangers. He dismissed slowdown calls from Anthropic's Dario Amodei and OpenAI's Sam Altman as "not grounded in science" and argued that no new rules, laws or guidelines are needed.

The US nonprofit C4ADS, a monitoring group funded mostly by the US government, has published a report on how export-restricted Nvidia AI accelerators still reach China. According to the investigation, chips worth billions of dollars flow to Chinese buyers through a range of workarounds. The findings show how Chinese firms get around the export rules of the Trump administration.

Nvidia CEO Jensen Huang dismissed the need for new artificial intelligence security regulations on Tuesday, arguing that market forces will help companies innovate safely. The comments land in a heated debate after Anthropic CEO Dario Amodei called for slowing the pace of AI capability gains. A day earlier, Huang told President Trump onstage that the industry would not let an AI slowdown happen.

The CEOs of OpenAI and Anthropic, as well as other industry leaders, are calling for a general slowdown in AI development over safety fears. On the flip side, Chinese authorities, the U. President, and CEO of Nvidia have dismissed their concerns as fearmongering.

President Trump called Nvidia CEO Jensen Huang while Huang was onstage in Los Angeles and used the moment to criticize calls to slow down and regulate AI. The call came during a week in which several AI lab leaders publicly argued for a slower pace of development.

Nvidia CEO Jensen Huang took a call from President Trump on Monday while onstage at the All-In Podcast's All-In Summit and put him on speakerphone in front of a large crowd. Trump used the moment to dismiss recent fears about AI development as a "hoax" and told the audience that the robots will not be taking over.

Perplexity has brought Portable Computer to Windows. It is a local version of the Perplexity Computer agent that plans and carries out multistep tasks on the PC. It requires a GeForce RTX GPU with at least 24 GB of VRAM or an RTX PRO workstation and ships with Qwen 3.8 27B, post-trained for Perplexity Computer.

OpenAI has unveiled Jalapeño, its first in-house AI accelerator. OpenAI says it cuts end-to-end latency by up to 3.6x compared with Nvidia's GB300 while using less power, and it pairs 13.4 petaflops of 4-bit compute with 232 GB of HBM4 memory.

Buying your own AI hardware can look like a simple answer to demanding workloads, but the maths is more complicated. Depreciation, scalability and hidden costs such as idle power, cooling and maintenance tip the balance against local machines for many users.

Anthropic CEO Dario Amodei published an essay over the weekend calling for a slower pace of AI capability development, and Sam Altman and Elon Musk said they agree. Markets reacted on Monday: SoftBank fell as much as 13 percent in Tokyo, Nasdaq futures dropped 1.3 percent, and Nvidia, AMD, Intel and Qualcomm slid in premarket trading. Companies seen as threatened by AI moved the other way.

In a social media post, Dario Amodei proposed a plan including third-party evaluations of AI systems The CEO of the artificial intelligence company Anthropic issued a new appeal on Saturday for the AI industry to “slow down” and offered a three-part plan for doing so, saying that his company would “unilaterally” commit to the first of the steps. In a post on social media, Dario Amodei shared a link to an essay titled We Must Pace the Frontier in which h…

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.

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.

DeepSeek plans to deploy at least 160,000 of Huawei Technologies Co. ’s top accelerators at a massive data center it’s building in Inner Mongolia, which could create one of the largest known clusters of Huawei AI chips and advance China’s efforts to replace Nvidia Corp.

Nvidia is officially launching DLSS 5 this week, following a divisive announcement in March where the AI upscaling tech was likened to a real-time generative AI filter for video games, or motion smoothing for games but worse. DLSS 5 will be available on RTX 50-series desktop and laptop GPUs and through GeForce Now cloud gaming, though the only game supporting it so far is NBA 2K27, launching September 3rd on PC.

Futurism reports that Russia is deploying drones in Ukraine that select and attack targets fully autonomously, including strikes that hit civilians. The compute behind them reportedly runs on Nvidia chips that reach the systems despite export controls. One expert quoted in the piece warns that machines are already making strike decisions.

Robinhood Markets CIO Stephanie Guild says Nvidia's results reinforce the AI investment theme, but warns that heavy corporate borrowing, persistent inflation and elevated interest rates could increasingly shape market returns. She favors gold, commodities and select healthcare exposure as diversification, while remaining cautious on long-duration assets and questioning whether Bitcoin is ready to serve as a reliable store of value.

Commerce Secretary Howard Lutnick will hold fireside chats with OpenAI CEO Sam Altman and Nvidia CEO Jensen Huang next week during the U. -led G20 Innovation Ministerial in Chapel Hill, North Carolina. 1-2 summit, co-hosted by the Commerce Department and the White House Office of Science and Technology Policy, is aimed at fostering global innovation in AI and other technologies.

Nvidia has projected 70% revenue growth for its next fiscal year, pushing the stock up in after-hours trading. Revenue for the most recent quarter came in at $96.2bn, ahead of expectations. CFO Colette Kress said the company remains supply constrained and could otherwise double revenue next year.

Gary Marcus, NYU Emeritus Professor of Psychology and Neural Science, discusses the rumored total addressable market figures presented by AI companies like Anthropic, which suggest a market size comparable to the entire U. He is skeptical that such valuations are realistic, noting that while AI touches many areas, not everyone is using it or satisfied with it.

The next wave of AI is placing new demands on infrastructure. As AI agents and trillion-parameter workloads become mainstream, performance depends not only on compute but on how compute, memory, storage, networking and software are designed together as one system.

In Piketon, southern Ohio, OpenAI, Nvidia and Japanese investors plan to spend around $500bn on one of the largest AI datacentres on the planet, targeting 8GW of computing power. The region hopes for thousands of jobs in an economically strained corner of Appalachia. Environmental groups warn about water and power consumption and the impact on residents.

Deploying a 405-billion-parameter AI model on a desktop is no small feat, but advancements in hardware like the NVIDIA DGX Spark and software such as OPNsense have made it achievable for those with the right resources and expertise. The Stack explores this ambitious undertaking, detailing how configurations like connecting two DGX Spark units via a […] The post Dual NVIDIA DGX Sparks Run 405B AI But Trails Cloud Processing appeared first on Geeky Gadgets.

Among those charged are two Super Micro employees and one from Nvidia, marking another flashpoint in US-China AI rivalry Taiwanese prosecutors charged nine people Monday, including one from Nvidia and two from Super Micro, for illegally exporting “high-end AI servers” to mainland China, adding another wave of turbulence in the AI ​​rivalry between China and the United States. Prosecutors said the servers involved were graphics processing units known as…

Ilya Sutskever’s Safe Super Intelligence (SSI) initiative represents a pivotal step in the development of advanced AI systems, emphasizing both safety and scalability. Backed by NVIDIA’s significant investment, SSI aims to address the challenges of creating superintelligent systems while minimizing risks associated with their deployment.

Ilya Sutskever, co-founder of Safe Super Intelligence Inc. (SSI), is spearheading efforts to develop artificial intelligence systems that prioritize safety and alignment with human values. Backed by a $5 billion investment from NVIDIA, SSI’s upcoming AI model, scheduled for release in August 2026, incorporates features like continual learning and internal feedback mechanisms.

On Hacker News, the community is debating whether the circular cash flows between Nvidia, Anthropic, OpenAI, Google and Meta pose a systemic risk to the global economy. The thread asks for concrete evidence of a stock market bubble in AI and whether such financial entanglements should be regulated or banned. Engagement so far is low, with only a handful of points and comments.

Anthropic has announced a bold shift in strategy by developing custom silicon chips for its Claude AI models, moving away from reliance on external providers like Google and NVIDIA. This decision aligns with a broader industry trend where proprietary hardware is seen as essential for optimizing performance and reducing costs.

Nvidia has agreed to put up as much as 105 billion dollars to support the first phase of a large data centre campus in Ohio that OpenAI is set to lease. The deal is the latest link between the two companies driving the current AI buildout. Bloomberg is so far the only source for the figure, and the structure of the agreement remains unconfirmed.

Indonesia is building its own AI capacity. The Ministry of Communication and Digital Affairs (Komdigi), Indosat Ooredoo Hutchison, NVIDIA and Universitas Gadjah Mada opened the UGM Indosat NVIDIA AI Technology Center in Yogyakarta, the country's first university-based AI technology center. Set up under Indonesia's AI Center of Excellence, it is meant to combine research, training and local talent development.

The NVIDIA DGX Spark has been widely discussed among AI developers since its release. It is marketed as a personal AI supercomputer meant to bring high performance computing to individual developers and small teams. The catch is the price: global memory shortages have pushed it to $4,699. That moves the device out of reach for much of the audience it was designed for.

NVIDIA has released Switchboard, an open source library for dynamic routing of AI tasks. The framework routes requests to suitable models based on complexity and resource constraints, working around the limits of a static model choice. Geeky Gadgets AI reports up to 50 percent faster response times and a 25 percent reduction in resource use.

Hon Hai Precision Industry, one of Nvidia's most important manufacturing partners, reported a larger quarterly profit than expected. The result points to robust global demand for AI hardware, from data center servers to components for accelerated workloads. For the market it is another signal that AI infrastructure spending is holding up.

After months of talks with tech industry leaders, the Trump administration has finalized a framework for testing new AI models for safety and cybersecurity risks. Staff from OpenAI, Anthropic, Meta, Google, Nvidia and Microsoft reviewed it in a private meeting at the White House.

A key US agency is reviewing how Chinese AI firms acquire and access Nvidia Corp. chips overseas, following a spate of technological breakthroughs that highlighted their ability to use the cutting-edge hardware despite Washington’s restrictions on shipments to the Asian country.

In July, NVIDIA joined more than 200 companies and organizations in signing „Open Weights and American AI Leadership“, an open letter arguing that AI leadership will be measured not by any single frontier model but by whether an open ecosystem reaches every sector. NVIDIA ties that argument to open world models that push the frontier of physical AI in Omniverse.

Anthropic spent the winter and spring as a darling of the US AI boom while casting itself as the industry's moral conscience. By summer, the Claude maker found itself increasingly isolated. It is the only frontier lab that declined to sign an open letter led by Nvidia CEO Jensen Huang urging Washington not to restrict open-weight models, a category currently dominated by Chinese providers.

Nvidia is preparing a fresh round of AI deals worth more than $750 billion, according to Bloomberg. Skeptics see the pattern they have been warning about: capital circulating between the chipmaker and its customers, making demand and valuations look larger than they are. Whether the investments reflect real demand or manufacture it remains an open question.

is in discussions to provide a financing guarantee to help OpenAI lease computing from a US data center project planned for 2028, underscoring how the world’s most valuable company is funneling capital into the infrastructure that drives its business.

AMD announced a raft of new data-center products it says will outperform rival Nvidia's, aiming to make gains in a booming market for AI computing. The move underscores how fierce the competition for AI infrastructure has become and how large the market at stake now is.

Nvidia CEO Jensen Huang is warning the Trump administration and other policymakers not to let "science fiction" fears about AI drive policy, arguing that overreaction could slow adoption and weaken America's competitive edge. Speaking to Axios, he railed against AI doomerism and implicitly challenged fellow tech CEOs who emphasize catastrophic risk.

Akamai CEO Tom Leighton lays out a contrarian vision for AI infrastructure: instead of ever-larger centralized data centers, he argues that distributed compute sitting closer to users delivers inference faster and more cheaply than central megaclusters. Nvidia is backing the approach.

Nvidia CEO Jensen Huang says China's open-source models are excellent and that American companies should be allowed to use them. In an interview with Axios he positioned himself against Trump officials and US labs pushing for a ban. Among those critics are Nvidia's own customers OpenAI and Anthropic, which accuse Chinese rivals of siphoning capabilities from their models.

Apple’s new Mac Studio, equipped with 1.5TB of unified memory, introduces a significant leap in localized AI and data processing capabilities. According to Kiraa, its unified memory architecture connects the CPU, GPU and neural engine, allowing advanced AI workloads to run efficiently without relying on cloud infrastructure.

- NVIDIA frames Vera as a new CPU category for agentic AI: maximum single-thread speed at data-center scale, not just high core counts. - Vera uses the Olympus core, which NVIDIA says delivers 50% higher instructions per cycle than Grace, with 88 cores, up to 1.2 TB/s LPDDR5X bandwidth and 3.4 TB/s core-to-core bandwidth.

- NVIDIA and Hugging Face are bringing Isaac GR00T 1.7 and Isaac Teleop into LeRobot, Hugging Face's open source robotics library. Cosmos 3 is planned to follow later. - The integrations aim to standardize data collection, training, fine-tuning, evaluation and deployment for robotics models.

- NVIDIA says it had 74 papers accepted at ICML 2026. Around 2,000 accepted papers cite NVIDIA GPUs, and 145 cite NVIDIA Nemotron as a foundation for new research. - The post frames Nemotron as more than one model release: an open research stack with weights, datasets, and recipes for reasoning, tool use, safety, data curation, and efficient inference.

- NVIDIA is introducing a new partner model for AI clouds: providers can build large-scale, multi-tenant AI factories with NVIDIA infrastructure and sell capacity to startups, model builders, enterprises, research organizations and regional AI players. - The model combines standard product revenue with cloud revenue sharing and credit support.

- Amazon Bedrock now offers OpenAI GPT OSS and NVIDIA Nemotron in AWS GovCloud (US): gpt-oss-120b, gpt-oss-20b, plus Nemotron Nano 9B v2, Nano 12B v2, Nano 30B, and Super 120B. - The models run inside the GovCloud boundary. In-Region inference is available in us-gov-west-1, while Geo Cross-Region routing spans us-gov-west-1 and us-gov-east-1 without using commercial AWS Regions.

- MIT Technology Review frames Zurich as a dense R&D hub where Apple, Anthropic, Disney Research, Google, Meta, Microsoft, NVIDIA and OpenAI all maintain research teams or labs. - The point is concentration, not scale: just over 400,000 residents, proximity to ETH Zurich, and deep talent in AI, computer vision, graphics, robotics and systems engineering.

- OpenAI is working with Broadcom on Jalapeño, a custom inference chip, joining Google, Apple, and SpaceX in the push to reduce reliance on Nvidia. - The point is not a clean break from Nvidia. It is a hedge against single-supplier risk around pricing, supply, priority access, and product roadmaps.

- AWS explains how to tune Amazon SageMaker AI training jobs for NVIDIA Blackwell: batch size, sequence length, precision format and activation checkpointing are the main levers. - The examples use P6-B200 instances with 8 Blackwell GPUs and PyTorch FSDP, focused on transformer models from 1B to 64B parameters.

- NVIDIA and AWS are packaging several production AI infrastructure pieces: Amazon EC2 G7 with NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs, OpenSearch Serverless with NVIDIA cuVS, and validated GB300 training performance. - EC2 G7 is positioned as a step up from G6, with up to 4.6x AI inference performance, up to 2.1x graphics performance, and faster GPU analytics via cuDF on Amazon EMR.

- At DTW Ignite 2026, NVIDIA is presenting a telecom autonomy stack built from synthetic data, domain models, secure runtimes and simulation, aimed at moving operators beyond task automation into 24/7 agentic operations. - SoftBank is using NeMo Safe Synthesizer and NeMo Anonymizer to create privacy-preserving synthetic telecom datasets for fine-tuning large telecom models and specialized network agents.

- Groq confirmed a new $650 million funding round led by Disruptive and Infinitum. The company did not disclose a new valuation. - The raise follows Nvidia’s deal about six months ago, in which Nvidia licensed Groq technology and hired founder Jonathan Ross, president Sunny Madra, and other staff.

- The NSF NAIRR pilot has run for two years and, according to NVIDIA, now supports more than 700 U. research projects, from protein prediction to infectious-disease outbreak management. - NVIDIA contributes cloud-based DGX capacity: researchers get access to at least four DGX nodes for at least one month, plus technical support for onboarding and project work.

- NVIDIA is using Cannes Lions to frame advertising and marketing as a GPU infrastructure market. The partner list includes Alembic, AWS, Criteo, Higgsfield, KERV. - Alembic plans to use DGX Vera Rubin SuperPODs for Causal AI, aiming to separate true marketing impact from correlation across channels, markets and audiences.

- NVIDIA frames France as a growing European AI hub: one year after GTC Paris, AI factories, national compute capacity and industrial AI platforms are moving from announcements into deployment. - Mistral is already running 18,000 GB200 systems, according to NVIDIA, and is building a 44 MW data center in Bruyères-le-Châtel as part of a roadmap toward 200 MW of European compute by 2027.

Accelerated computing has transformed industrial engineering, cutting simulation times from weeks to hours. The remaining bottlenecks now sit around the simulation itself: CAD design, meshing, simulation setup and debugging, plus post-processing and report generation.

At NVIDIA GTC Taipei during COMPUTEX, developers, researchers, and industry leaders converge to cover the latest in AI factories, scaling infrastructure, agentic AI, and physical AI. NVIDIA traditionally uses this stage for major announcements — anyone building or buying into the AI stack should watch the livestream. It's not just hardware news; it's the roadmap for the next 12 months.

After open-source hardware accelerated robotics development, the software running robot brains is increasingly going open too. Hugging Face, Nvidia, and Alibaba have all made significant open-source robotics bets in the past two years, releasing foundation models for robot control. This lowers the cost of building capable robots for research labs and startups, with the industry hoping for an LLM-style breakthrough.

The first NVIDIA Vera CPUs arrived at three of the world's leading AI labs — Anthropic in San Francisco, OpenAI in Mission Bay, and SpaceXAI in Palo Alto — followed by a delivery to Oracle Cloud Infrastructure in Santa Clara. NVIDIA VP of Hyperscale and HPC Ian Buck hand-delivered them.

NVIDIA’s latest AI model Nemotron 3 Nano Omnia, featuring an impressive 30 billion parameters, is designed to excel in multimodal processing, handling images, video and audio with remarkable efficiency. Highlighted by Two Minute Papers, this system achieves exceptional throughput, processing nearly 10 hours of video per hour, a speed 10 times faster than real-time playback.

The rise of electricity-guzzling data centers has forced the AI industry to get creative about finding power. Nvidia is teaming up with InfraPartners, Prologis, and nonprofit EPRI to build about 25 micro data centers (5–20 MW each) next to utility substations at five US utilities.

Nvidia founder and CEO Jensen Huang told graduates at Carnegie Mellon University in Pittsburgh yesterday that demand for AI infrastructure is creating a once-in-a-generation opportunity to reindustrialize America and restore the nation's capacity to build. With many college grads fearing AI could obliterate their career dreams, Huang pointed to boundless opportunity as a new industry is being born and a new era of science and discovery begins.

The SpaceX–Anthropic deal marks a pivotal moment in the AI market and underscores the industry's brutal compute hunger. SpaceX is leasing Anthropic the Colossus 1 supercomputer — over 220,000 Nvidia GPUs and 300 MW of power — so the lab can keep scaling its models. Notable twist: Elon Musk's SpaceX is supplying compute to a direct rival of his own xAI.

The Pentagon has struck deals with OpenAI, Google, Microsoft, Amazon, Nvidia, Elon Musk's xAI, and the startup Reflection, allowing the agency to use their AI tools in classified settings. The Defense Department has left out Anthropic — which it previously used for classified information — after declaring it a supply-chain risk.

Samsung Electronics reported record quarterly profit driven by a 49-fold jump in chip income, warning that the global memory shortage will deepen into 2027. The AI datacenter buildout is pushing Samsung and rivals to allocate capacity to high-end chips used in Nvidia's AI accelerators. The squeeze hits conventional chips hard — pricing pressure is mounting across SSDs and DRAM.

Altman trial, exhibits are surfacing piece by piece — emails, photos, and corporate documents from OpenAI's earliest days, some predating even the lab's name. Highlights so far: Nvidia CEO Jensen Huang gifted OpenAI an in-demand supercomputer, Musk largely drafted OpenAI's mission and shaped its early structure, Sam Altman apparently wanted to lean heavily on Y Combinator for early support, and Greg Brockman and Ilya Sutskever were already worried about…

NVIDIA is launching a 12 GB version of the RTX 5070 GPU for laptops, alongside the existing 8 GB model. The new SKU uses 24 Gb G7 modules to ease pressure on the constrained 16 Gb G7 supply currently shipping with most GPUs. First laptops with the variant arrive in June from ASUS, Lenovo and MSI.

IT budgets are blowing up as some companies spend more on AI than on employee salaries. Nvidia's Bryan Catanzaro says compute costs already exceed the people costs of his team, and Uber's CTO has already burned through his full 2026 AI budget. Gartner projects worldwide IT spending of $6.31 trillion in 2026, up 13.5% from 2025, driven by sustained momentum across AI infrastructure, software and cloud services.

Google Cloud has launched two new AI accelerator chips designed to compete with Nvidia's dominance in the AI infrastructure market. The new TPUs are faster and cheaper than previous generations, offering cloud customers a Google-native alternative for AI workloads. Despite the push, Google Cloud still supports Nvidia hardware—signaling a pragmatic dual-track strategy for the near term.

Nvidia CEO Jensen Huang suggested that AI will function as a constant, ever-present manager that monitors and nudges workers continuously. The vision positions AI less as a helpful assistant and more as an inescapable digital overseer. Huang's comments spark debate about how much AI-driven supervision is actually desirable in the workplace—and where the line between productivity tool and surveillance lies.

Amazon announced the availability of G7e instances powered by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs on Amazon SageMaker AI. You can provision nodes with 1, 2, 4, and 8 GPU instances, with each GPU providing 96 GB of GDDR7 memory. This enables cost-effective hosting of large foundation models like GPT-OSS-120B and Qwen3.5-35B-A3B on a single node.