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Chevron, Engine No1 Announce Power Solution Partnership for US Data Centers

In a recent joint release, Chevron U.S.A Inc. and Engine No. 1 announced “the formation of a partnership to build a new company to develop scalable, reliable power solutions for U.S. based data centers running on U.S. natural gas”. The release highlighted that the joint development is “in conjunction with GE Vernova” and “aims to […]

In a recent joint release, Chevron U.S.A Inc. and Engine No. 1 announced “the formation of a partnership to build a new company to develop scalable, reliable power solutions for U.S. based data centers running on U.S. natural gas”.

The release highlighted that the joint development is “in conjunction with GE Vernova” and “aims to establish the first multi gigawatt-scale co-located power plant and data center during President Trump’s second term”.

The first projects are expected to leverage seven U.S. made GE Vernova 7HA natural gas turbines, secured under a slot reservation agreement, on an accelerated timeline, the release noted. The projects are expected to serve co-located data centers in the U.S. Southeast, Midwest, and West regions, the release added, stating that power generation is not designed to flow initially through the existing transmission grid, “reducing the risk of increasing electricity prices for consumers”.

According to the release, the joint development plans to deliver up to four gigawatts, “the equivalent of powering 3-3.5 million U.S. homes, with initial in-service targeted by the end of 2027 and potential for project expansion beyond this capacity”. The release noted that the projects are expected to be designed with the flexibility to integrate lower carbon solutions.

The release said the companies’ plans directly address the need for affordable, reliable energy to meet the significant demand for electricity to power U.S. data centers, enabling current and future generations of AI to be developed in the United States.

The joint release also stated that the joint development is expected to create thousands of jobs and help the reindustrialization of the United States.

Rigzone has asked Chevron, Engine No. 1, and GE Vernova what kind of jobs these are likely to be and roughly when recruitment will take place. At the time of writing, none of the companies have responded to Rigzone yet.

“We are proud to play our part in bringing to fruition President Trump’s vision for a new American golden age, powered by our enormous energy resources and unrivaled workforce,” Mike Wirth, chief executive officer and chairman, Chevron Corporation, said in the release.

“President Trump’s pro-American energy policies and commitment to energy and AI dominance give us the confidence to invest in projects that will create American jobs and strengthen our national security,” he added.

Chris James, founder and chief investment officer of Engine No. 1, said in the release, “energy is the key to America’s AI dominance”.

“By using abundant domestic natural gas to generate electricity directly connected to data centers, we can secure AI leadership, drive productivity gains across our economy, and restore America’s standing as an industrial superpower,” he added.

“This partnership with Chevron and GE Vernova addresses the biggest energy challenge we face,” he continued.

Scott Strazik, chief executive officer at GE Vernova, said in the release, “we are excited to enable the advancement of data center growth in the U.S. by supporting delivery of critical power needs to customers using innovative solutions”.

“GE Vernova is uniquely positioned to provide the energy systems and support required to make this large-scale endeavor possible, as the leading U.S. energy manufacturer,” he added.

In a separate release posted on its website on Wednesday, GE Vernova said it is planning to invest nearly $600 million in its U.S. factories and facilities over the next two years to help meet the surging electricity demands around the world.

The new investments are expected to create more than 1,500 new U.S. jobs, according to the release. GE Vernona noted in the release that the new investments are the first part of a larger $9 billion cumulative global capex and R&D investment plan through 2028 that was announced at the company’s investor update on December 10.

An executive order published on the White House website on January 23 states that it “revokes certain existing AI policies and directives that act as barriers to American AI innovation, clearing a path for the United States to act decisively to retain global leadership in artificial intelligence”.

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Three options for wireless power in the enterprise

Sensors such as these can be attached to pallets to track its location, says Srivastava. “People in Europe are very conscious about where their food is coming from and, to comply with regulations, companies need to have sensors on the pallets,” he says. “Or they might need to know that

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IBM unveils advanced quantum computer in Spain

IBM executives and officials from the Basque Government and regional councils in front of Europe’s first IBM Quantum System Two, located at the IBM-Euskadi Quantum Computational Center in San Sebastián, Spain. The Basque Government and IBM unveil the first IBM Quantum System Two in Europe at the IBM-Euskadi Quantum Computational

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Oil Drops as Potential Trump-Putin Meeting Eases Supply Fears

Oil fell to a fresh five-month low after US President Donald Trump said he’ll meet with Russian counterpart Vladimir Putin to discuss ending the war in Ukraine, raising expectations that Russian crude may soon flow freely. West Texas Intermediate fell 1.4% Thursday to settle near $57 a barrel, the lowest since May. Trump announced on social media that the US and Russia will hold high-level talks focused on ending the war next week, followed by a leaders’ summit in Budapest.  The prospect of a Russia-Ukraine truce comes amid mounting pressure on Moscow’s oil infrastructure. Russian exports of refined fuels have slumped to the lowest since the onset of the war, underscoring continued strain on the country’s refineries targeted by drone attacks. At the same time, Western nations are turning the screws on Russia’s energy sector in a bid to curb the flow of petrodollars to the Kremlin and limit Putin’s ability to finance the war. The UK recently slapped sanctions on Russia’s biggest oil producers, two Chinese energy firms and Indian refiner Nayara Energy Ltd. because of their handling of Russian fuel. The development took some air out of the earlier rally after India’s oil refiners said they expect to reduce — not stop — the purchase of Russian crude, a move that could squeeze global supply, following remarks by Trump that the South Asian nation would halt all buying. India, along with neighbor China, has made the most of discounted Russian supplies accessible under a Group of Seven price cap mechanism that was designed to keep oil flowing while limiting Moscow’s access to funds.  Crude has fallen this month as increased trade tensions between the US and China raised concerns about demand in the two biggest crude consumers, and as major trading houses said a long-anticipated oversupply is already starting to emerge.  “The softness in oil demand seen in early

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China Appetite for Canadian Oil Headed for All Time High

Canadian oil exports to China are on pace for a record month amid a surge of purchases as the Asian giant pivots away from US crude. Almost 5 million barrels have been shipped out of Vancouver so far in October, a record for the first 15 days of any month, according to Vortexa ship tracking data.  Chinese buyers were recently stockpiling more than half a million barrels a day of foreign crude to take advantage of steep price discounts for Russian and Iranian oil amid growing US pressure to economically hobble those nations. More than 70% of oil-laden vessels departing the British Columbia port have sailed for China, according to the data. The remainder headed for the US West Coast, an area off Los Angeles where cargoes typically are offloaded to larger tankers for shipment elsewhere, or had no listed destination.  Asian demand has driven Canadian heavy crude to the strongest prices since July even as prices are normally near their weakest in the fourth quarter. Western Canadian Select in Alberta was trading at $10.20 less than US benchmark West Texas Intermediate as of Thursday, according to Modern Commodities prices. Canadian oil shipments to China are surging as the country shuns US crude amid an intensifying trade dispute between the world’s two largest economies. China recently imposed retaliatory port fees on US-linked vessels, increasing freight rates to haul American crude to Asia.  The three ports that receiving the most Canadian crude this month include Ningbo, Zhoushan and Zhanjiang, Vortexa data show. Zhoushan is where the 800,000 barrel a day Zhejiang Petroleum & Chemical refinery, majority owned by Rongsheng Petrochemical, receives its crude. The plant has been the biggest Chinese buyer of Canadian oil since the expanded Trans Mountain pipeline to Vancouver went into operation last year. Earlier this year, the company hired

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Energy Department Closes Loan Guarantee to Strengthen U.S. Grid Reliability

WASHINGTON—U.S. Secretary of Energy Chris Wright today announced the Department of Energy’s (DOE) Loan Programs Office (LPO) closed a loan guarantee to strengthen grid reliability and ensure lower electricity costs across the midwestern region of the United States. In accordance with President Trump’s Executive Order, Strengthening the Reliability and Security of the United States Electric Grid, the $1.6 billion loan guarantee to a subsidiary of American Electric Power (AEP) will reconductor and rebuild around 5,000 miles of transmission lines across Indiana, Michigan, Ohio, Oklahoma, and West Virginia. The project will create over 1,000 construction jobs and enhance grid reliability and capacity in rapidly growing areas. “Thanks to President Trump and the Working Families Tax Cut, the Energy Department is ensuring the American people will have access to affordable, reliable and secure energy for decades to come,” said U.S. Secretary Wright. “The President has been clear: America must reverse course from the energy subtraction agenda of past administrations and strengthen our electrical grid. This loan guarantee will not only help modernize the grid and expand transmission capacity but will help position the United States to win the AI race and grow our manufacturing base.”The loan guarantee, which was carefully evaluated under the new LPO guidance directed by Secretary Wright, delivers on the Trump administration’s promise to responsibly steward taxpayer dollars and unleash American energy dominance. The AEP financial close is also the first closed loan guarantee under the Energy Dominance Financing (EDF) Program created by the Working Families Tax Cut, also known as the One Big Beautiful Bill Act. President Trump signed the legislation into law earlier this year. All electric utilities receiving an EDF loan must provide assurance to DOE that financial benefits from the financing will be passed on to the customers of that utility. DOE remains committed to

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Torch Clean Energy taps Fluence for 640 MWh battery at Arizona solar plant

Torch Clean Energy is developing two 80 MW solar arrays in Cochise County, Arizona, and has selected Fluence Energy to deliver a 160 MW / 640 MWh battery system to support the renewables, the companies announced Wednesday. The project is an example of the clean energy buildout expected across the United States. The U.S. Energy Information Administration expects domestic utility-scale battery storage to more than double over the next two years, to close out 2026 at nearly 65 GW. Torch’s project, dubbed “Winchester,” is expected to be online in 2027 and will support grid balancing and the forecasted load growth for the region, as well as economic development and local infrastructure investment, the companies said. Torch is a renewables developer focused on the U.S. Mid-Atlantic and Southwest, and has developed and solar more than 1.2 GW of green power assets. “Torch is excited to partner with Fluence to manufacture the energy storage system for our Winchester project,” said Torch President Travis Haggard. The battery “will allow us to shift cost-effective solar generation to be dispatched when the grid needs it most.” Fluence’s Gridstack Pro 5000 battery will include domestically manufactured enclosures, inverters and thermal management systems “to enable the full solar-plus-storage facility to qualify for domestic content tax credits,” the companies said. Fluence says it has more than 22 GWh of battery energy storage capacity deployed or contracted across projects in the U.S. “This facility is a great step toward ensuring affordable, reliable, and secure power for the local community and will support regional economic activity and expected load growth for many years to come,” Fluence Americas President John Zahurancik said in a statement.

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DOE closes $1.6B loan commitment for AEP transmission rebuild

Listen to the article 3 min This audio is auto-generated. Please let us know if you have feedback. Dive Brief: The U.S. Department of Energy’s Loan Programs Office said Thursday it has closed a $1.6 billion loan guarantee to a subsidiary of American Electric Power to reconductor and rebuild around 5,000 miles of transmission lines across Indiana, Michigan, Ohio, Oklahoma, and West Virginia. The conditional loan commitment was announced in January as part of $23 billion in assistance DOE offered to eight utilities for investments in transmission, energy storage, grid modernization and gas pipelines. The Trump administration has been reviewing loan commitments and grants finalized in the waning days of the Biden administration, charging that many were rushed through with inadequate review. Energy Secretary Chris Wright said the AEP loan will bolster reliability and “ensure lower electricity costs across the Midwestern region of the United States.” Dive Insight: DOE did not immediately respond to questions about the status of other loan guarantees announced in January. AEP is the first company to close a loan guarantee under the Energy Dominance Financing Program created by the One Big Beautiful Bill Act. President Trump signed the legislation into law earlier this year. The guarantee “was carefully evaluated” under new LPO guidance and “delivers on the Trump administration’s promise to responsibly steward taxpayer dollars and unleash American energy dominance,” DOE said in a statement. AEP is “experiencing growth in energy demand that has not been seen in a generation,” President, CEO and Chairman Bill Fehrman said in a statement. Customers have committed to 24 GW of electricity demand by the end of the decade, AEP said, and necessary upgrades have been identified to support data center, artificial intelligence and manufacturing development. Approximately 100 miles of transmission line across Ohio and Oklahoma are the first projects supported by

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HSBC Dubs BP 3Q Trading Statement ‘Mixed to Negative’

In a research note sent to Rigzone by the HSBC team late Tuesday, HSBC Senior Global Oil and Gas Analyst Kim Fustier said BP’s third quarter trading statement was “mixed to negative”. “Gas trading was ‘average’ (same as 2Q), while oil trading was ‘weak’ as oil price volatility subsided (implying a big delta vs ‘strong’ in 2Q),” Fustier said in the note. “On the positive side, 3Q oil and gas production is expected to be higher vs 2Q vs ‘slightly lower’ previously, thanks to U.S. onshore (BPX) growth. This is the second consecutive quarter when production will exceed initial guidance, which suggests good operational regularity, though the financial impact may be muted given low U.S. gas prices,” Fustier added. “In Downstream, stronger refining indicator margins ($15.8/b vs $11.9/b in 2Q) and ‘significantly lower’ turnarounds (as expected) are partly offset by environmental costs and the unplanned Whiting outage in August caused by severe weather,” Fustier continued. “Net debt is expected to be stable q-o-q at $26 billion including a working capital release, better than our forecast of a modest increase,” Fustier stated. In the research note, Fustier revealed that HSBC was raising its BP third quarter earnings forecast by four percent to $1.9 billion “as higher production and a positive refining mark-to-market are offset by weaker oil trading”. “Our updated forecast is slightly below consensus. We believe that 2Q marked the start of a recovery at BP. But as the mixed 3Q update shows, it will take several quarters of consistent delivery for BP to establish a track record,” Fustier said in the note. Rigzone has contacted BP for comment on the HSBC research note. At the time of writing, BP has not responded to Rigzone. In a release posted on its website on October 14, BP announced “updated third quarter

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BlackRock’s $40B data center deal opens a new infrastructure battle for CIOs

Everest Group partner Yugal Joshi said, “CIOs are under significant pressure to clearly define their data center strategy beyond traditional one-off leases. Given most of the capacity is built and delivered by fewer players, CIOs need to prepare for a higher-price market with limited negotiation power.” The numbers bear this out. Global data center costs rose to $217.30 per kilowatt per month in the first quarter of 2025, with major markets seeing increases of 17-18% year-over-year, according to CBRE. Those prices are at levels last seen in 2011-2012, and analysts expect them to remain elevated. Gogia said, “The combination of AI demand, energy scarcity, and environmental regulation has permanently rewritten the economics of running workloads. Prices that once looked extraordinary have now become baseline.” Hyperscalers get first dibs The consolidation problem is compounded by the way capacity is being allocated. North America’s data center vacancy rate fell to 1.6% in the first half of 2025, with Northern Virginia posting just 0.76%, according to CBRE Research. More troubling for enterprises: 74.3% of capacity currently under construction is already preleased, primarily to cloud and AI providers. “The global compute market is no longer governed by open supply and demand,” Gogia said. “It is increasingly shaped by pre-emptive control. Hyperscalers and AI majors are reserving capacity years in advance, often before the first trench for power is dug. This has quietly created a two-tier world: one in which large players guarantee their future and everyone else competes for what remains.” That dynamic forces enterprises into longer planning cycles. “CIOs must forecast their infrastructure requirements with the same precision they apply to financial budgets and talent pipelines,” Gogia said. “The planning horizon must stretch to three or even five years.”

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Nvidia, Infineon partner for AI data center power overhaul

The solution is to convert power right at the GPU on the server board and to upgrade the backbone to 800 volts. That should squeeze more reliability and efficiency out of the system while dealing with the heat, Infineon stated.   Nvidia announced the 800 Volt direct current (VDC) power architecture at Computex 2025 as a much-needed replacement for the 54 Volt backbone currently in use, which is overwhelmed by the demand of AI processors and increasingly prone to failure. “This makes sense with the power needs of AI and how it is growing,” said Alvin Nguyen, senior analyst with Forrester Research. “This helps mitigate power losses seen from lower voltage and AC systems, reduces the need for materials like copper for wiring/bus bars, better reliability, and better serviceability.” Infineon says a shift to a centralized 800 VDC architecture allows for reduced power losses, higher efficiency and reliability. However, the new architecture requires new power conversion solutions and safety mechanisms to prevent potential hazards and costly server downtimes such as service and maintenance.

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Meta details cutting-edge networking technologies for AI infrastructure

ESUN initiative As part of its standardization efforts, Meta said it would be a key player in the new Ethernet for Scale-Up Networking (ESUN) initiative that brings together AMD, Arista, ARM, Broadcom, Cisco, HPE Networking, Marvell, Microsoft, NVIDIA, OpenAI and Oracle to advance the networking technology to handle the growing scale-up domain for AI systems. ESUN will focus solely on open, standards-based Ethernet switching and framing for scale-up networking—excluding host-side stacks, non-Ethernet protocols, application-layer solutions, and proprietary technologies. The group will focus on the development and interoperability of XPU network interfaces and Ethernet switch ASICs for scale-up networks, the OCP wrote in a blog. ESUN will actively engage with other organizations such as Ultra-Ethernet Consortium (UEC) and long-standing IEEE 802.3 Ethernet to align open standards, incorporate best practices, and accelerate innovation, the OCP stated. Data center networking milestones The launch of ESUN is just one of the AI networking developments Meta shared at the event. Meta engineers also announced three data center networking innovations aimed at making its infrastructure more flexible, scalable, and efficient: The evolution of Meta’s Disaggregated Scheduled Fabric (DSF) to support scale-out interconnect for large AI clusters that span entire data center buildings. A new Non-Scheduled Fabric (NSF) architecture based entirely on shallow-buffer, disaggregated Ethernet switches that will support our largest AI clusters like Prometheus. The addition of Minipack3N, based on Nvidia’s Ethernet Spectrum-4 ASIC, to Meta’s portfolio of 51Tbps OCP switches that use OCP’s Switch Abstraction Interface and Meta’s Facebook Open Switching System (FBOSS) software stack. DSF is Meta’s open networking fabric that completely separates switch hardware, NICs, endpoints, and other networking components from the underlying network and uses OCP-SAI and FBOSS to achieve that, according to Meta. It supports Ethernet-based RoCE RDMA over Converged Ethernet (RoCE/RDMA)) to endpoints, accelerators and NICs from multiple vendors, such as Nvidia,

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Arm joins Open Compute Project to build next-generation AI data center silicon

Keeping up with the demand comes down to performance, and more specifically, performance per watt. With power limited, OEMs have become much more involved in all aspects of the system design, rather than pulling silicon off the shelf or pulling servers or racks off the shelf. “They’re getting much more specific about what that silicon looks like, which is a big departure from where the data center was ten or 15 years ago. The point here being is that they look to create a more optimized system design to bring the acceleration closer to the compute, and get much better performance per watt,” said Awad. The Open Compute Project is a global industry organization dedicated to designing and sharing open-source hardware configurations for data center technologies and infrastructure. It covers everything from silicon products to rack and tray design.  It is hosting its 2025 OCP Global Summit this week in San Jose, Calif. Arm also was part of the Ethernet for Scale-Up Networking (ESUN) initiative announced this week at the Summit that included AMD, Arista, Broadcom, Cisco, HPE Networking, Marvell, Meta, Microsoft, and Nvidia. ESUN promises to advance Ethernet networking technology to handle scale-up connectivity across accelerated AI infrastructures. Arm’s goal by joining OCP is to encourage knowledge sharing and collaboration between companies and users to share ideas, specifications and intellectual property. It is known for focusing on modular rather than monolithic designs, which is where chiplets come in. For example, customers might have multiple different companies building a 64-core CPU and then choose IO to pair it with, whether like PCIe or an NVLink. They then choose their own memory subsystem, deciding whether to go HBM, LPDDR, or DDR. It’s all mix and match like Legos, Awad said.

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BlackRock-Led Consortium to Acquire Aligned Data Centers in $40 Billion AI Infrastructure Deal

Capital Strategy and Infrastructure Readiness The AIP consortium has outlined an initial $30 billion in equity, with potential to scale toward $100 billion including debt over time as part of a broader AI infrastructure buildout. The Aligned acquisition represents a cornerstone investment within that capital roadmap. Aligned’s “ready-to-scale” platform – encompassing land, permits, interconnects, and power roadmaps – is far more valuable today than a patchwork of single-site developments. The consortium framed the transaction as a direct response to the global AI buildout crunch, targeting critical land, energy, and equipment bottlenecks that continue to constrain hyperscale expansion. Platform Overview: Aligned’s Evolution and Strategic Fit Aligned Data Centers has rapidly emerged as a scale developer and operator purpose-built for high-density, quick-turn capacity demanded by hyperscalers and AI platforms. Beyond the U.S., Aligned extended its reach across the Americas through its acquisition of ODATA in Latin America, creating a Pan-American presence that now spans more than 50 campuses and over 5 GW of capacity. The company has repeatedly accessed both public and private capital markets, most recently securing more than $12 billion in new equity and debt financing to accelerate expansion. Aligned’s U.S.–LATAM footprint provides geographic diversification and proximity to fast-growing AI regions. The buyer consortium’s global relationships – spanning utilities, OEMs, and sovereign-fund partners – help address power, interconnect, and supply-chain constraints, all of which are critical to sustaining growth in the AI data-center ecosystem. Macquarie Asset Management built Aligned from a niche U.S. operator into a 5 GW-plus, multi-market platform, the kind of asset infrastructure investors covet as AI demand outpaces grid and supply-chain capacity. Its sale at this stage reflects a broader wave of industry consolidation among large-scale digital-infrastructure owners. Since its own acquisition by BlackRock in early 2024, GIP has strengthened its position as one of the world’s top owners

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Oracle’s big bet for AI: Zettascale10

“OCI Zettascale10 was designed with the goal of integrating large-scale generative AI use cases, including training and running large language models,” said Info-Tech’s Palanichamy. Oracle also introduced new capabilities in Oracle Acceleron, its OCI networking stack, that it said helps customers run workloads more quickly and cost-effectively. They include dedicated network fabrics, converged NICs, and host-level zero-trust packet routing that Oracle says can double network and storage throughput while cutting latency and cost. Oracle’s zettascale supercomputer is built on the Acceleron RoCE (RDMA over Converged Ethernet) architecture and Nvidia AI infrastructure. This allows it to deliver what Oracle calls “breakthrough” scale, “extremely low” GPU-to-GPU latency, and improved price/performance, cluster use, and overall reliability. The new architecture has a “wide, shallow, resilient” fabric, according to Oracle, and takes advantage of switching capabilities built into modern GPU network interface cards (NICs). This means it can connect to multiple switches at the same time, but each switch stays on its own isolated network plane. Customers can thus deploy larger clusters, faster, while running into fewer stalls and checkpoint restarts, because traffic can be shifted to different network planes and re-routed when the system encounters unstable or contested paths. The architecture also features power-efficient optics and is “hyper-optimized” for density, as its clusters are located in large data center campuses within a two-kilometer radius, Oracle said.

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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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