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Nvidia powers world’s largest quantum research supercomputer

Nvidia announced the opening of the Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT), which hosts ABCI-Q — the world’s largest research supercomputer dedicated to quantum computing. Quantum processors promise to augment AI supercomputers in solving some of the world’s most complex challenges, spanning industries including healthcare, energy and finance. By enabling quantum-GPU computing at an unprecedented scale, ABCI-Q marks a profound leap toward realizing practical, accelerated quantum systems, Nvidia said. Delivered by Japan’s National Institute of Advanced Industrial Science and Technology (AIST), the ABCI-Q supercomputer features 2,020 Nvidia H100 graphics processing units (GPUs) interconnected by the Nvidia Quantum-2 InfiniBand networking platform. The system is integrated with Nvidia CUDA-Q, an open-source hybrid computing platform for orchestrating the hardware and software needed to run useful, massive-scale quantum computing applications. “Seamlessly coupling quantum hardware with AI supercomputing will accelerate realizing the promise of quantum computing for all,” said Tim Costa, senior director of computer-aided engineering, quantum and CUDA-X™ at Nvidia, in a statement. “Nvidia’s collaboration with AIST will catalyze progress in areas like quantum error correction and applications development — crucial for building useful, accelerated quantum supercomputers.” ABCI-Q’s AI supercomputing is integrated with a superconducting qubit processor by Fujitsu, a neutral atom quantum processor by QuEra and a photonic processor by OptQC — enabling hybrid quantum-GPU workloads across multiple qubit modalities. “ABCI-Q will enable researchers in Japan to explore the core challenges quantum computing technologies face and speed the path to practical use cases,” said Masahiro Horibe, deputy director of G-QuAT and AIST. “The Nvidia accelerated computing platform in ABCI-Q will empower scientists to experiment with the stepping-stone systems needed to advance quantum computing.”

Nvidia announced the opening of the Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT), which hosts ABCI-Q — the world’s largest research supercomputer dedicated to quantum computing.

Quantum processors promise to augment AI supercomputers in solving some of the world’s most complex challenges, spanning industries including healthcare, energy and finance. By enabling quantum-GPU computing at an unprecedented scale, ABCI-Q marks a profound leap toward realizing practical, accelerated quantum systems, Nvidia said.

Delivered by Japan’s National Institute of Advanced Industrial Science and Technology (AIST), the ABCI-Q supercomputer features 2,020 Nvidia H100 graphics processing units (GPUs) interconnected by the Nvidia Quantum-2 InfiniBand networking platform.

The system is integrated with Nvidia CUDA-Q, an open-source hybrid computing platform for orchestrating the hardware and software needed to run useful, massive-scale quantum computing applications.

“Seamlessly coupling quantum hardware with AI supercomputing will accelerate realizing the promise of quantum computing for all,” said Tim Costa, senior director of computer-aided engineering, quantum and CUDA-X™ at Nvidia, in a statement. “Nvidia’s collaboration with AIST will catalyze progress in areas like quantum error correction and applications development — crucial for building useful, accelerated quantum supercomputers.”

ABCI-Q’s AI supercomputing is integrated with a superconducting qubit processor by Fujitsu, a neutral atom quantum processor by QuEra and a photonic processor by OptQC — enabling hybrid quantum-GPU workloads across multiple qubit modalities.

“ABCI-Q will enable researchers in Japan to explore the core challenges quantum computing technologies face and speed the path to practical use cases,” said Masahiro Horibe, deputy director of G-QuAT and AIST. “The Nvidia accelerated computing platform in ABCI-Q will empower scientists to experiment with the stepping-stone systems needed to advance quantum computing.”

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6 trends that will shape the future of the cloud: Gartner

For this reason, Gartner recommends identifying specific use cases and planning the applications and data distributed across the organization that could benefit from a cross-cloud deployment model. This allows workloads to operate collaboratively across different cloud platforms, as well as different on-premises and co-location facilities. 4. Industry solutions According to

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New England Patriots kick off network upgrade

The longer-term roadmap with NWN includes a refresh of the stadium’s 1,800 Extreme Networks Wi-Fi 6 access points to either Wi-Fi 6E or 7, a refresh of the network’s 80 Cisco physical and virtual firewalls, followed by a network consolidation project. On top of all that, the Kraft Group is

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CompTIA cert targets operational cybersecurity skills

The SecOT+ certification will provide OT professionals with the skills to manage, mitigate, and remediate security risks in manufacturing and critical infrastructure environments, according to CompTIA. The certification program will provide OT positions, such as floor technicians and industrial engineers, as well as cybersecurity engineers and network architects on the

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North America Adds Rigs for First Time in Months

North America added five rigs week on week, according to Baker Hughes’ latest North America rotary rig count, which was released on May 16. Although the U.S. dropped a total of two rigs week on week, Canada added a total of seven rigs during the same period, taking the total North America rig count up to 697, comprising 576 rigs from the U.S. and 121 from Canada, the count outlined. Of the total U.S. rig count of 576, 563 rigs are categorized as land rigs, 11 are categorized as offshore rigs, and two are categorized as inland water rigs. The total U.S. rig count is made up of 473 oil rigs, 100 gas rigs, and three miscellaneous rigs, according to Baker Hughes’ count, which revealed that the U.S. total comprises 520 horizontal rigs, 41 directional rigs, and 15 vertical rigs. Week on week, the U.S. land and inland water rig counts each dropped by one, and the country’s offshore rig count remained unchanged, the count highlighted. The U.S. oil and gas rig counts each decreased by one week on week, and its miscellaneous rig count remained unchanged, the count showed. Baker Hughes revealed that the U.S. horizontal rig count dropped by two week on week, while its directional and vertical rig counts remained unchanged during the period. A major state variances subcategory included in the rig count showed that, week on week, New Mexico and Texas each dropped two rigs, and Wyoming and Ohio each added one rig. A major basin variances subcategory included in Baker Hughes’ rig count showed that, week on week, the Permian basin dropped three rigs and the Utica basin added one rig. Canada’s total rig count of 121 is made up of 74 oil rigs and 47 gas rigs, Baker Hughes pointed out. The country’s

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Hopes rise for EU and UK cooperation on energy trading and carbon capture and storage

The UK and the European Union (EU) are set to forge closer ties on energy trading and emerging technologies such as carbon capture and storage (CCS) following a landmark summit in London. UK Prime Minister Sir Keir Starmer hosted EU leaders as the two sides reached a post-Brexit deal which also covered fishing rights and defence. According to a joint UK-EU statement, policymakers will explore UK participation in the EU’s internal electricity market, including participating in EU trading platforms. The statement also outlined continued regulatory cooperation on emerging energy transition sectors such as hydrogen, CCS and biomethane. The deal could have implications for the future of interconnector projects between the UK and EU countries, as well as offshore carbon storage projects in the North Sea. UK and EU cooperation on carbon capture and storage Many of the UK’s CCS developments, including the track-2 Acorn and Viking projects, are aiming to eventually import captured CO2 from mainland European nations such as Germany. © Supplied by Viking CCSA map showing major industrial emitters in the UK in relation to the proposed Viking CCS project from Harbour Energy. However, since the UK left the EU in 2016, the country has so far failed to secure any bilateral agreements with EU nations on cross-border CO2 transport and storage. Meanwhile, North Sea neighbour Norway has secured CO2 deals with EU members Denmark, Sweden, Belgium and the Netherlands, despite not being part of the EU. As a result, Norway’s Northern Lights CCS project is set to begin receiving international CO2 shipments later this year. © Supplied by Northern LightsThe Northern Lights carbon capture and storage project in Norway. Similarly, Denmark’s Greensand CCS project has already signed deals with a Swedish firm covering imported CO2 volumes. If the UK and the EU can align their regulatory schemes

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North Sea firms underestimating financial risks from net zero transition, study finds

Many UK oil and gas companies are underestimating the financial risks posed by the energy transition and are potentially exposing investors to significant losses, according to a study. Led by academics from the UK and France, the study explored how well transition risks were being accounted for by offshore firms. The study found the net zero shift was likely to reduce access to capital for fossil fuel companies, push up borrowing costs, and trigger large-scale write-downs – leading to some assets being stranded. Loughborough University lecturer Dr Freeman Owusu said these pressures “could have put the future viability of some companies in question”. “Our findings show that the transition to net zero presents significant risks for oil and gas companies in the UK,” Dr Owusu said. “These risks include rising operational costs, reduced access to finance, and increased financial pressure. “Together, these risks threaten the going concern of some oil and gas companies, lower market value, and have knock-on effects on the wider energy supply chain and government revenues.” Smaller firms ‘most exposed’ to net zero risks According to the study, smaller firms with higher emissions and fewer alternative business streams were seen as “most exposed” to these risks. The research identified issues surrounding the financial risks tied to the energy transition, as well as the need for clearer, more tailored company disclosures. The study found existing reporting frameworks do not fully capture the unique financial and accounting risks facing oil and gas firms during the energy transition. © Supplied by ShutterstockAn oil rig in the North Sea. Participants in the study called for greater transparency around environmental, social and governance (ESG) performance, alongside remaining reserves, plans for asset write-downs and evolving business models. Without these changes, oil and gas firms risked losing stakeholder trust and weakening their long-term prospects,

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Venture Global Exported Record LNG in Q1

Venture Global Inc. exported 233.6 trillion British thermal units (TBtu) of liquefied natural gas (LNG) in the first quarter (Q1), increasing 62 percent from the same three-month period last year and setting a new quarterly record for the company. Meanwhile LNG volumes sold totaled 228.3 TBtu, also up 62 percent from Q1 2024. Revenue grew 105 percent year-on-year to $2.89 billion. However, net profit fell 39 percent year-over-year to $396 million. “This decrease was largely driven by non-cash factors such as unfavorable changes in the fair value of our interest rate swaps”, the Arlington, Virginia-based LNG developer said in an online statement. Income from operations increased 75 percent year-on-year to $1.08 billion primarily due to higher sales volumes and prices. Consolidated adjusted earnings before interest, taxes, depreciation and amortization grew 94 percent year-on-year to $1.35 billion. The positive impact from higher sales volumes and prices were partially offset by an increase in operating costs “in support of the ramp-up of LNG production at the Plaquemines Project and operating our LNG tankers, as well as remediation and rectification costs associated with the preparation of the Calcasieu Project for COD”, Venture Global said. Plaquemines LNG shipped its first cargo, from phase 1, last December. Phase 2, which the company approved 2023, is expected to start operation this year. Phases 1 and 2 have a total permitted capacity of 27.2 million metric tons per annum, though phase 2 has yet to obtain a permit to export to countries with no free trade agreement (FTA) with the United States. The quarterly report said, “Eighteen of the Phase 1 liquefaction trains at the Plaquemines Project demonstrated production levels of approximately 140 percent of nameplate capacity”. Venture Global confirmed that in April, subsequent to the quarter, Calcasieu Pass LNG started “commercial operations”. The Cameron Parish facility

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Weatherford Enters into Collaboration with Amazon Web Services

Weatherford International plc said it has signed an agreement with Amazon Web Services (AWS) that aims to transform Weatherford’s digital capabilities and “help drive innovation in the energy sector”. As part of the collaboration, Weatherford will have AWS as its preferred cloud provider and will migrate its software and hardware suite to AWS. The migration includes Weatherford’s modern edge platform, which integrates advanced software-enabled hardware with its control system CygNet, the company said in a news release. AWS will support the development of next-generation technologies, further enhancing Weatherford’s unified data model, a solution that allows customers to integrate, harmonize, and analyze multi-asset data within a scalable, API-compatible model, according to the release. The collaboration will also enhance the WFRD Software Launchpad, a platform that provides customers with access to Weatherford-built and Weatherford-partnered applications. The Launchpad ensures that customers retain control over their data while seamlessly managing multiple software solutions without being locked into a single application, the company said. Weatherford President and CEO Girish Saligram said, “We are excited to work with AWS to deliver a comprehensive suite of innovative solutions that enable our customers to drive efficiency and innovation. This collaboration allows us to leverage AWS’s world-class cloud infrastructure to help our customers modernize their operations, reduce complexity, and achieve greater autonomy in their decision-making”. “AWS capabilities are accelerating Weatherford’s digital transformation and helping the company drive innovation in their digital solutions to meet customers’ needs,” Howard Gefen, GM for Energy and Utilities at AWS, said. “This collaboration will enhance Weatherford’s ability to deliver its operational and petrotechnical solutions by leveraging scalable, hardware and software solutions that empower energy companies to optimize their operations and achieve sustainable growth in an increasingly complex landscape”. New CFO Named Weatherford said in an earlier statement that Anuj Dhruv has been appointed as

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Africa Oil Corp Announces New Brand Identity

In a release posted on its website, Africa Oil Corp. announced a new brand identity with a change of name to Meren Energy Inc. The company noted in the release that its rebranding follows the recent completion of the “transformative Prime consolidation, doubling reserves and production in high quality offshore assets that benefit from low lifting costs, premium Brent pricing and a favorable fiscal regime”. The business said its common shares will trade under the new symbol ‘MER’ on the TSX and Nasdaq OMX Stockholm. It added in the release that there is no change in the capitalization of the company pursuant to the change of name and new trading symbols. In connection with its name change, the company also announced the launch of a new website, which has gone live today, “to coincide with the trading under the new symbols”. The name Meren is derived from an old nautical term representing the mooring of a vessel as it docks, the company stated in the release.  “Inspired by the maritime legends that set sail in pursuit of new worlds, the name mirrors the company’s stability anchored by a diverse portfolio, strong cash flow profile and proven ability to work side by side with industry leaders on world-class assets,” it added. In the release, the company noted that Meren’s “key strategic objectives will remain to – drive long-term value through its existing portfolio of world-class assets and deliver compelling shareholder returns; continue growing into a leading independent E&P company that is a trusted and prominent industry partner, recognized for the quality of its assets, balance sheet strength, and disciplined capital allocation; and judiciously consider strategic acquisition of production assets within target markets, with strict adherence to strategic, financial and operational criteria”. President and Chief Executive Officer Roger Tucker said in the release,

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Liquid cooling becoming essential as AI servers proliferate

“Facility water loops sometimes have good water quality, sometimes bad,” says My Troung, CTO at ZutaCore, a liquid cooling company. “Sometimes you have organics you don’t want to have inside the technical loop.” So there’s one set of pipes that goes around the data center, collecting the heat from the server racks, and another set of smaller pipes that lives inside individual racks or servers. “That inner loop is some sort of technical fluid, and the two loops exchange heat across a heat exchanger,” says Troung. The most common approach today, he says, is to use a single-phase liquid — one that stays in liquid form and never evaporates into a gas — such as water or propylene glycol. But it’s not the most efficient option. Evaporation is a great way to dissipate heat. That’s what our bodies do when we sweat. When water goes from a liquid to a gas it’s called a phase change, and it uses up energy and makes everything around it slightly cooler. Of course, few servers run hot enough to boil water — but they can boil other liquids. “Two phase is the most efficient cooling technology,” says Xianming (Simon) Dai, a professor at University of Texas at Dallas. And it might be here sooner than you think. In a keynote address in March at Nvidia GTC, Nvidia CEO Jensen Huang unveiled the Rubin Ultra NVL576, due in the second half of 2027 — with 600 kilowatts per rack. “With the 600 kilowatt racks that Nvidia is announcing, the industry will have to shift very soon from single-phase approaches to two-phase,” says ZutaCore’s Troung. Another highly-efficient cooling approach is immersion cooling. According to a Castrol survey released in March, 90% of 600 data center industry leaders say that they are considering switching to immersion

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Cisco taps OpenAI’s Codex for AI-driven network coding

“If you want to ask Codex a question about your codebase, click “Ask”. Each task is processed independently in a separate, isolated environment preloaded with your codebase. Codex can read and edit files, as well as run commands including test harnesses, linters, and type checkers. Task completion typically takes between 1 and 30 minutes, depending on complexity, and you can monitor Codex’s progress in real time,” according to OpenAI. “Once Codex completes a task, it commits its changes in its environment. Codex provides verifiable evidence of its actions through citations of terminal logs and test outputs, allowing you to trace each step taken during task completion,” OpenAI wrote. “You can then review the results, request further revisions, open a GitHub pull request, or directly integrate the changes into your local environment. In the product, you can configure the Codex environment to match your real development environment as closely as possible.” OpenAI is releasing Codex as a research preview: “We prioritized security and transparency when designing Codex so users can verify its outputs – a safeguard that grows increasingly more important as AI models handle more complex coding tasks independently and safety considerations evolve. Users can check Codex’s work through citations, terminal logs and test results,” OpenAI wrote.  Internally, technical teams at OpenAI have started using Codex. “It is most often used by OpenAI engineers to offload repetitive, well-scoped tasks, like refactoring, renaming, and writing tests, that would otherwise break focus. It’s equally useful for scaffolding new features, wiring components, fixing bugs, and drafting documentation,” OpenAI stated. Cisco’s view of agentic AI Patel stated that Codex is part of the developing AI agent world, where Cisco envisions billions of AI agents will work together to transform and redefine the architectural assumptions the industry has relied on. Agents will communicate within and

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US companies are helping Saudi Arabia to build an AI powerhouse

AMD announced a five-year, $10 billion collaboration with Humain to deploy up to 500 megawatts of AI compute in Saudi Arabia and the US, aiming to deploy “multi-exaflop capacity by early 2026.” AWS, too, is expanding its data centers in Saudi Arabia to bolster Humain’s cloud infrastructure. Saudi Arabia has abundant oil and gas to power those data centers, and is growing its renewable energy resources with the goal of supplying 50% of the country’s power by 2030. “Commercial electricity rates, nearly 50% lower than in the US, offer potential cost savings for AI model training, though high local hosting costs due to land, talent, and infrastructure limit total savings,” said Eric Samuel, Associate Director at IDC. Located near Middle Eastern population centers and fiber optic cables to Asia, these data centers will offer enterprises low-latency cloud computing for real-time AI applications. Late is great There’s an advantage to being a relative latecomer to the technology industry, said Eric Samuel, associate director, research at IDC. “Saudi Arabia’s greenfield tech landscape offers a unique opportunity for rapid, ground-up AI integration, unburdened by legacy systems,” he said.

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AMD, Nvidia partner with Saudi startup to build multi-billion dollar AI service centers

Humain will deploy the Nvidia Omniverse platform as a multi-tenant system to drive acceleration of the new era of physical AI and robotics through simulation, optimization and operation of physical environments by new human-AI-led solutions. The AMD deal did not discuss the number of chips involved in the deal, but it is valued at $10 billion. AMD and Humain plan to develop a comprehensive AI infrastructure through a network of AMD-based AI data centers that will extend from Saudi Arabia to the US and support a wide range of AI workloads across corporate, start-up, and government markets. Think of it as AWS but only offering AI as a service. AMD will provide its AI compute portfolio – Epyc, Instinct, and FPGA networking — and the AMD ROCm open software ecosystem, while Humain will manage the delivery of the hyperscale data center, sustainable power systems, and global fiber interconnects. The partners expect to activate a multi-exaflop network by early 2026, supported by next-generation AI silicon, modular data center zones, and a software platform stack focused on developer enablement, open standards, and interoperability. Amazon Web Services also got a piece of the action, announcing a more than $5 billion investment to build an “AI zone” in the Kingdom. The zone is the first of its kind and will bring together multiple capabilities, including dedicated AWS AI infrastructure and servers, UltraCluster networks for faster AI training and inference, AWS services like SageMaker and Bedrock, and AI application services such as Amazon Q. Like the AMD project, the zone will be available in 2026. Humain only emerged this month, so little is known about it. But given that it is backed by Crown Prince Salman and has the full weight of the Kingdom’s Public Investment Fund (PIF), which ranks among the world’s largest and

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Check Point CISO: Network segregation can prevent blackouts, disruptions

Fischbein agrees 100% with his colleague’s analysis and adds that education and training can help prevent such incidents from occurring. “Simulating such a blackout is impossible, it has never been done,” he acknowledges, but he is committed to strengthening personal and team training and risk awareness. Increased defense and cybersecurity budgets In 2025, industry watchers expect there will be an increase in the public budget allocated to defense. In Spain, one-third of the budget will be allocated to increasing cybersecurity. But for Fischbein, training teams is much more important than the budget. “The challenge is to distribute the budget in a way that can be managed,” he notes, and to leverage intuitive and easy-to-use platforms, so that organizations don’t have to invest all the money in training. “When you have information, management, users, devices, mobiles, data centers, clouds, cameras, printers… the security challenge is very complex. You have to look for a security platform that makes things easier, faster, and simpler,” he says. ” Today there are excellent tools that can stop all kinds of attacks.” “Since 2010, there have been cybersecurity systems, also from Check Point, that help prevent this type of incident from happening, but I’m not sure that [Spain’s electricity blackout] was a cyberattack.” Leading the way in email security According to Gartner’s Magic Quadrant, Check Point is the leader in email security platforms. Today email is still responsible for 88% of all malicious file distributions. Attacks that, as Fischbein explains, enter through phishing, spam, SMS, or QR codes. “There are two challenges: to stop the threats and not to disturb, because if the security tool is a nuisance it causes more harm than good. It is very important that the solution does not annoy [users],” he stresses. “As almost all attacks enter via e-mail, it is

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HPE ‘morphs’ private cloud portfolio with improved virtualization, storage and data protection

What do you get when combining Morpheus with Aruba? As part of the extensible platform message that HPE is promoting with Morpheus, it’s also working in some capabilities from the broader HPE portfolio. One integration is with HPE Aruba for networking microsegmentation. Bhardwaj noted that a lot of HPE Morpheus users are looking for microsegmentation in order to make sure that the traffic between two virtual machines on a server is secure. “The traditional approach of doing that is on the hypervisor, but that costs cycles on the hypervisor,” Bhardwaj said. “Frankly, the way that’s being delivered today, customers have to pay extra cost on the server.” With the HPE Aruba plugin that now works with HPE Morpheus, the microsegmentation capability can be enabled at the switch level. Bhardwaj said that by doing the microsegmentation in the switch and not the hypervisor, costs can be lowered and performance can be increased. The integration brings additional capabilities, including the ability to support VPN and network address translation (NAT) in an integrated way between the switch and the hypervisor. VMware isn’t the only hypervisor supported by HPE  The HPE Morpheus VM Essentials Hypervisor is another new element in the HPE cloud portfolio. The hypervisor is now being integrated into HPE’s private cloud offerings for both data center as well as edge deployments.

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Microsoft will invest $80B in AI data centers in fiscal 2025

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs).  In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

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John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

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2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

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OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

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