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Phillips 66 Seals Acquisition of EPIC Midstream Assets

Phillips 66 has completed the acquisition of EPIC Y-Grade GP LLC and EPIC Y-Grade LP for about $2.2 billion, boosting its midstream footprint in the Permian Basin. The units, bought from EPIC Midstream Holdings LP, own natural gas liquids (NGL) pipelines, fractionation facilities and distribution systems. “This transaction strengthens our position as a leading integrated […]

Phillips 66 has completed the acquisition of EPIC Y-Grade GP LLC and EPIC Y-Grade LP for about $2.2 billion, boosting its midstream footprint in the Permian Basin.

The units, bought from EPIC Midstream Holdings LP, own natural gas liquids (NGL) pipelines, fractionation facilities and distribution systems.

“This transaction strengthens our position as a leading integrated downstream energy provider”, Don Baldridge, Phillips 66 executive vice president for midstream and chemicals, said in a company statement. “We are evolving our portfolio and enhancing our ability to provide seamless and efficient delivery of energy products.

“Phillips 66 will offer producers unparalleled flow assurance, while advancing a strategy that is expected to deliver attractive returns and create long-term value for our shareholders”.

The acquired operations comprise two fractionators with a capacity of170,000 barrels per day (bpd) near Corpus Christi, Texas; purity distribution pipelines stretching about 350 miles; and an NGL pipeline around 885 miles long and with a capacity of 175,000 bpd. The NGL pipeline links the Delaware, Midland and Eagle Ford basins to the fractionation complexes and Phillips 66’s Sweeny Hub, which has facilities for crude distilling, naphtha reforming, fluid catalytic cracking, alkylation and hydrodesulfurization, as well as aromatics units, a vacuum distillation unit and a delayed coking unit.

The pipeline capacity is being raised to 225,000 bpd, in a project expected to be completed in the second quarter. A further expansion has also been sanctioned to grow the capacity to 350,000 bpd; completion is expected 2026. EPIC has also put in place plans to raise the fractionation capacity to 280,000 bpd.

“The acquired assets connect Permian production to Gulf Coast refiners, petrochemical companies and export markets, and are highly integrated with the Phillips 66 asset base”, Phillips 66 said.

Announcing the agreement January 6, the company said, “Phillips 66 does not expect to increase its recently announced 2025 capital program in connection with that expansion”.

On December 16, 2024, the Houston, Texas-based downstream oil and gas company announced $2.1 billion in capital for 2025, comprising $1.1 billion for growth and $998 million for sustaining capital.

Phillips 66 expects the acquisition to be “immediately accretive to earnings per share”.

Before the EPIC agreement, Phillips 66 exceeded a $3 billion divestment plan meant to support its shareholder return target and other long-term priorities.

“We intend to continue to optimize the portfolio and rationalize non-core assets going forward”, chair and chief executive Mark Lashier said in a statement December 16, 2024, announcing an agreement to divest DCP GCX Pipeline LLC, which owns a 25 percent non-operating stake in the Gulf Coast Express Pipeline, to ArcLight Capital Partners LLC. “The evolution of our portfolio underscores our position as a leading integrated downstream energy provider, enhancing shareholder value and positioning the company for the future”.

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Cisco, Google Cloud offer enterprises new way to connect SD-WANs

Looking back, the rapid adoption of SaaS and cloud applications led to a WAN transformation and the emergence of SD-WAN via direct internet access, Sambi asserted. “Then, to enhance application performance, enterprises built colocation-based cloud on-ramps, which, while improving latency, introduced complexity and costs. This evolution led to a proliferation

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Fortinet embeds AI capabilities across Security Fabric platform

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Tailscale secures $160 million for its WireGuard-based VPN development

Building on WireGuard’s foundation At the heart of Tailscale’s technology is WireGuard, a modern VPN protocol that offers significant security and performance advantages over legacy solutions.  WireGuard is an open-source technology built in a way that minimizes the attack surface while providing greater performance than older VPN approaches. While WireGuard

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UALink releases inaugural GPU interconnect specification

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Malaysian Firm to Deliver Diesel, Jet Fuel to Swiss One

AGAPE ATP Corporation (ATPC) said it has entered into two sales and purchase agreements collectively worth $24 billion with Swiss One Oil & Gas AG for diesel and jet fuel. Under the terms of the agreements, its subsidiary ATPC Green Energy will supply EN590 10PPM diesel and Jet Fuel A1 to Swiss One over a 12-month period plus rolls and extensions, with an initial trial order comprising 200,000 metric tons of EN590 10PPM diesel and 2 million barrels of Jet Fuel A1, ATPC said in a news release. The trial shipment started in March, the Kuala Lumpur, Malaysia-based company said. Upon successful completion of the trial, the contract will transition into full-scale supply, with weekly deliveries of 500,000 metric tons of EN590 10PPM diesel and 2 million barrels of Jet Fuel A1 to meet growing global demand, according to the release. All deliveries will be executed through free-on-board procedures at major international ports. The agreement complies with global quality standards, with SGS or equivalent inspection authorities conducting independent quality assessments to ensure that the fuel meets ASTM/IP international standards, the company stated. The agreements build upon an earlier initial corporate purchase order signed in February, which laid the foundation for the procurement and supply of refined fuels, including Jet Fuel A1 and EN590 10PPM diesel, the company said. The initial order covered a trial shipment of 100,000 metric tons of EN590 10PPM diesel and one million barrels of Jet Fuel A1, and its successful completion led to long-term structured agreements between the parties. Dato’ Sri How Kok Choong, founder and global group CEO of ATPC, said, “Our initial [corporate purchase order] with Swiss One Oil & Gas AG was a crucial step in trust and operational efficiency in the oil and gas sector. The transition to a full-scale [sales and

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RE, Nuclear Generation Breached 40 Percent Last Year: Think Tank

For the first time since the 1940s, global annual electricity production from renewable sources and nuclear energy surpassed 40 percent, reaching 40.9 percent in 2024, according to Ember Energy. Renewable power saw a 49 percent growth against 2023, adding a record 858 terawatt hours (tWh), the London-based think tank said in a report. Solar remained the biggest growth contributor for the third consecutive year, with solar generation rising by 29 percent or 474 tWh, enough to meet 40 percent of the global increase in demand, according to the report. Solar was the fastest-growing source for the 20th year running. “Solar is now so cheap that large markets can emerge in the space of a single year”, the report said, highlighting the case of Pakistan. “Amid high electricity prices linked to expensive contracts with privately-owned thermal power stations, rooftop solar installations in Pakistan’s homes and businesses soared as a means of accessing lower-cost power”, the report said. The South Asian country imported 17 GW of solar last year to meet this demand, double the amount it imported 2023, according to Ember. “Within just a year, Pakistan became one of the world’s largest markets for new solar installations in 2024. Pakistan’s case shows that the low-cost, fast-to-build nature of solar power can transform electricity systems at an unprecedented rate. “Updated system planning and regulatory frameworks are needed alongside this deployment to ensure a sustainable and managed transition”. Wind generation grew to 8.1 percent of global power production in 2024, while hydropower’s share remained steady at 14 percent. Hydro was the single biggest renewable source accounting for 1,356 tWh or 13.5 percent of last year’s clean power production. The European Union had the biggest share of wind and solar generation in 2024 at 29 percent, followed by Brazil at 25 percent and China

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Japan’s Terra Drone Partners with Aramco Eyeing Tech for Energy

Japan’s Terra Drone Corporation said it signed a memorandum of understanding (MoU) with Saudi Arabian Oil Co. (Aramco) for a strategic partnership exploring innovation in drones, robotics, and AI-driven solutions tailored to the oil and gas sector. The MoU aims to strengthen collaboration between Terra Drone and Aramco with the aim of advancing drone technologies that contribute to enhancing safety and operational efficiency in the energy sector. It serves as a platform for fostering innovation in critical areas such as research and development, technology piloting, training and localization, Terra Drone said in a news release. Terra Drone founder and CEO Toru Tokushige said, “This MoU reflects our commitment to driving innovation and supporting localization in line with the vision of Aramco. Through our group company, Terra Drone Arabia, we aim to introduce cutting-edge drone technologies that not only enhance safety and efficiency but also empower the local workforce. By fostering collaboration and investing in R&D [research and development], we are building a foundation for sustainable growth and technological advancement in the Kingdom.” Terra Drone said it received funding from Aramco’s venture arm, Wa’ed Ventures, in 2023, targeting to contribute to the localization of advanced drone technologies from global leaders. Terra Drone then established a branch in Saudi Arabia, Terra Drone Arabia, to localize its services in the short term and to establish local research and development and production facilities in the long term. Terra Drone Arabia is a provider of drone and geospatial solutions across the Middle East and Africa. The unit offers services in land surveying, bathymetry, and data processing, among others. Tokyo-based Terra Drone said it has a portfolio of over 3,000 completed projects worldwide, and specializes in surveying, inspections, agriculture, and UAS Traffic Management (UTM), with a focus on industries such as oil and gas, construction, chemicals,

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Starmer appoints ex-Office of Fair Trading chief to lead nuclear taskforce

The UK government’s nuclear taskforce will be led by John Fingleton, formerly the boss of the Office of Fair Trading, following his appointment to spearhead the unit. The Nuclear Regulatory Taskforce, which was set up to accelerate the development of new nuclear power stations across the country, is poised to embark on an overhaul of UK planning regulation. In February, Keir Starmer moved to slash “red tape” in the industry to enable more nuclear power plants to be approved across England and Wales. Those reforms are designed to enable small modular reactors to be built for the first time. That is the intended result of the government abolishing a set list of approved sites for nuclear development so that nuclear power stations can be built anywhere in the country. The energy department said that contract negotiations to progress a competition for these small reactors, held by Great British Nuclear, are “currently underway”, and that a panel of nuclear experts will be appointed to the taskforce in due course. In a controversial move, the government is also getting rid of expiry dates on nuclear planning rules, in an effort to avoid projects timing out. These changes to nuclear planning rules were proposed after the pre-development stage Sizewell C nuclear plant in Suffolk was taken to court by local activists. The Department for Net Zero and Energy Security said that the government committed a further £2.7 billion in public funding to Sizewell C last month. Prime minister Starmer’s cabinet is seeking to deliver a “nuclear renaissance” as part of his Plan for Change. Energy secretary Ed Miliband said: “Our Plan for Change and clean energy mission means it is time to build, build, build – it is time for a nuclear renaissance in this country, and that can only happen if we move further and

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Britain Utility Regulator Opens Applications for New LDES Investment Scheme

Britian’s Office of Gas and Electricity Markets (Ofgem) has opened applications under a new “cap and floor” scheme for so-called long-duration electricity storage (LDES) projects. The scheme seeks to produce the first LDES facilities in Britain in 40 years by easing hurdles such as high costs. Currently Britain has 2.8 gigawatts (GW) of LDES capacity, from four pumped storage hydro facilities in Scotland and Wales, according to Ofgem. The government sees LDES as key to achieving the United Kingdom’s goal of clean power by 2030 and net-zero emissions by 2050. “Long Duration Electricity Storage facilities provide vital back-up for the renewable power system – working like giant batteries that store electricity created by wind and solar farms, then release it to the grid when needed”, Ofgem said in an online statement. The inaugural application window is offering 2.7-7.7 GW, an indicative range that the National Energy Systems Operator (NESO) recommended to be installed by 2035. The official target for 2050 is to reach 20 GW of LDES capacity. “Producing one gigawatt constantly for a year is enough to power 2.65 million homes”, Ofgem said. Developers applying in window 1 have two tracks. One is for projects that can go onstream 2030 and the other is for projects that will be delivered 2033. “Ofgem will prioritize decisions on projects that can deliver by 2030 if necessary”, the statement said. The cap-and-floor scheme boosts “investor confidence with the security of providing minimum revenue for LDES operators to manage high start-up costs and long build times”, Ofgem said. “The scheme will ensure value for money by driving down costs, only allowing efficient projects with a storage capacity of more than eight hours. “At the same time, the regime protects consumers with a cap on profits, meaning any excess revenues flow directly back to customers

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Uncertainty is the Only Certainty, Commodities Analyst Warns

Uncertainty is the only certainty. That’s what Ole R. Hvalbye, Commodities Analyst at Skandinaviska Enskilda Banken AB (SEB), said in an oil report sent to Rigzone by the SEB team on Thursday, adding that Brent “spike[d]… $8 before sliding this morning”. “Brent crude prices have sharply rebounded since yesterday evening, reversing much of the steep losses seen during Tuesday afternoon and early Wednesday trading,” Hvalbye said in the report. “From a low of $58.4 per barrel, Brent surged overnight to $66.1, marking an immediate and notable $7.7 per barrel recovery. The brent price has declined to the current $63.8 per barrel during the morning,” he added. In the report, Hvalbye noted that market fundamentals remain sidelined as tariff rhetoric continues to dominate headlines. “The latest rally is largely driven by geopolitical developments, as the U.S. president announced a pause on scheduled additional tariffs for most countries, while simultaneously escalating measures against China,” he said. “In response to China’s retaliatory tariffs, the U.S. raised its tariff rate on Chinese goods to a high 125 percent,” he added. “Meanwhile, the president signaled a 90-day pause on ‘reciprocal’ tariffs targeting other trade partners, including the EU, as a ‘reward’ for not retaliating. This establishes a temporary tariff floor of 10 percent for all countries excluding China,” he continued. Hvalbye highlighted in the report that the market responded swiftly, noting that global equity and commodity markets surged, rebounding from recent lows. “Asian markets rallied this morning, while in the U.S., the S&P 500 closed up 9.5 percent, its strongest day since 2008. The Nasdaq Composite climbed more than 12 percent, its largest single-day gain since 2001,” Hvalbye said. “Crude prices are trading slightly down this morning, consolidating after the sharp rebound. Still, concerns over global oil demand persist, particularly in light of the growing

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Google reaffirms $75B AI infra investment as cloud providers pursue divergent strategies

“We are witnessing a divergence in hyperscaler strategy,” noted Abhivyakti Sengar, practice director at Everest Group. “Google is doubling down on global, AI-first scale; Microsoft is signaling regional optimization and selective restraint. For enterprises, this changes the calculus.” Meanwhile, OpenAI is reportedly exploring building its own data center infrastructure to reduce reliance on cloud providers and increase its computing capabilities. Shifting enterprise priorities For CIOs and enterprise architects, these divergent infrastructure approaches present new considerations when planning AI deployments. Organizations must now evaluate not just immediate availability, but long-term infrastructure alignment with their AI roadmaps. “Enterprise cloud strategies for AI are no longer just about picking a hyperscaler — they’re increasingly about workload sovereignty, GPU availability, latency economics, and AI model hosting rights,” said Sanchit Gogia, CEO and chief analyst at Greyhound Research. According to Greyhound’s research, 61% of large enterprises now prioritize “AI-specific procurement criteria” when evaluating cloud providers — up from just 24% in 2023. These criteria include model interoperability, fine-tuning costs, and support for open-weight alternatives. The rise of multicloud strategies As hyperscalers pursue different approaches to AI infrastructure, enterprise IT leaders are increasingly adopting multicloud strategies as a risk mitigation measure.

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China’s rare earth export controls threaten enterprise IT hardware supply chains

“AI-first infrastructure rollouts — particularly those involving GPUs, edge accelerators, and high-efficiency cooling — are directly in the crosshairs,” Gogia noted. “So are quantum computing R&D efforts and high-reliability storage systems where thermal and magnetic materials matter.” China, responsible for 70% of global rare earth mining output and 87% of refined supply, poses a serious threat to enterprise IT hardware supply chains with these restrictions — especially for companies with AI-optimized server lines. AI chip production under threat The impact on semiconductor manufacturing comes at a critical time when enterprise demand for AI chips is soaring. Companies including Nvidia, AMD, Intel, and TSMC rely on rare earth elements during the manufacturing of advanced chips. “We see the greatest exposure in private data center expansion projects, AI inferencing at the edge, and next-gen device manufacturing, including specialized industrial IoT and robotics,” noted Gogia. Major cloud providers have been aggressively expanding their AI compute capacity, with substantial hardware refreshes planned for late 2025. These plans may now face delays or cost increases as chip manufacturers grapple with supply constraints. Pricing pressures to be felt in 3-6 months The immediate impact is expected to be limited as manufacturers work through existing inventory, but pricing pressure could emerge within 3-6 months, experts feel.

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DARPA backs multiple quantum paths in benchmarking initiative

Nord Quantique plans to use the money to expand its team, says Julien Camirand Lemyre, the company’s president, CTO and co-founder. That’s an opportunity to accelerate the development of the technology, he says. “By extension, what this will mean for enterprise users is that quantum solutions to real-world business problems will be available sooner, due to that acceleration,” he says. “And so enterprise customers need to also accelerate how they are thinking about adoption because the advantages quantum will provide will be tangible.” Lemyre predicts that useful quantum computers will be available for enterprises before the end of the decade. “In fact, there has been tremendous progress across the entire quantum sector in recent years,” he says. “This means industry needs to begin thinking seriously about how they will integrate quantum computing into their operations over the medium term.” “We’re seeing, with the deployment of programs like the QBI in the US and investments of billions of dollars from  public and private investors globally, an increasing maturity of quantum technologies,” said Paul Terry, CEO at Photonic, which is betting on optically-linked silicon spin qubits.  “Our architecture has been designed from day one to build modular, scalable, fault-tolerant quantum systems able to be deployed in data centers,” he said. He’s not the only one to mention fault-tolerance. DARPA stressed fault-tolerance in its announcement, and its selections point to the importance of error correction for the future of quantum computing. The biggest problem with today’s quantum computers is that the number of errors increases faster than the number of qubits, making them impossible to scale up. Quantum companies are working on a variety of approaches to reduce the error rates low enough that quantum computers can get big enough to actually to real work.

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Zayo’s Fiber Bet: Scaling Long-Haul and Metro Networks for AI Data Centers

Zayo Group Holdings Inc. has emerged as one of the most aggressive fiber infrastructure players in North America, particularly in the context of AI-driven growth. With a $4 billion investment in AI-related long-haul fiber expansion, Zayo is positioning itself as a critical enabler of the AI and cloud computing boom. The company is aggressively expanding its long-haul fiber network, adding over 5,000 route miles to accommodate the anticipated 2-6X increase in AI-driven data center capacity by 2030. This initiative comes as AI workloads continue to push the limits of existing network infrastructure, particularly in long-haul connectivity. New Fiber Routes The new routes include critical connections between key AI data center hubs, such as Chicago-Columbus, Las Vegas-Reno, Atlanta-Ashburn, and Columbus-Indianapolis, among others. Additionally, Zayo is overbuilding seven existing routes to further enhance network performance, resiliency, and low-latency connectivity. This new development is a follow-on to 15 new long haul routes representing over 5300 route miles of new and expanded capacity deployed over the last five years. These route locations were selected based on expected data center growth, power availability, existing capacity constraints, and specific regional considerations. The AI Data Center Sector: A Significant Driver of Fiber Infrastructure The exponential growth of AI-driven data center demand means that the U.S. faces a potential bandwidth shortage. Zayo’s investments look to ensure that long-haul fiber capacity keeps pace with this growth, allowing AI data centers to efficiently transmit data between key markets. This is especially important as data center development locations are being driven more by land and power availability rather than proximity to market. Emerging AI data center markets get the high speed fiber they need, especially as they are moving away from expensive power regions (e.g., California, Virginia) to lower-cost locations (e.g., Ohio, Nevada, Midwest). Without the high-speed networking capabilities offered by

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Crusoe Adds 4.5 GW Natural Gas to Fuel AI, Expands Abilene Data Center to 1.2 GW

Crusoe and the Lancium Clean Campus: A New Model for Power-Optimized Compute Crusoe Energy’s 300-megawatt deployment at the Lancium Clean Campus in Abilene is a significant marker of how data center strategies are evolving to integrate more deeply with energy markets. By leveraging demand flexibility, stranded power, and renewable energy, Crusoe is following a path similar to some of the most forward-thinking projects in the data center industry. But it’s also pushing the model further—fusing AI and high-performance computing (HPC) with the next generation of power-responsive infrastructure. Here’s how Crusoe’s strategy compares to some of the industry’s most notable power-driven data center deployments: Google’s Oklahoma Data Center: Proximity to Renewable Growth A close parallel to Crusoe’s energy-centric site selection strategy is Google’s Mayes County data center in Oklahoma. Google sited its facility there to take advantage of abundant wind energy, aligning with the local power grid’s renewable capacity. Similarly, Crusoe is tapping into Texas’s deregulated energy market, optimizing for low-cost renewable power and the ability to flexibly scale compute operations in response to grid conditions. Google has also been an industry leader in time-matching workloads to renewable energy availability, something that Crusoe is enabling in real time through grid-responsive compute orchestration. Sabey Data Centers in Quincy: Low-Cost Power as a Foundation Another instructive comparison is Sabey Data Centers’ Quincy, Washington, campus, which was built around one of the most cost-effective power sources in the U.S.—abundant hydroelectric energy. Sabey’s long-term strategy has been to co-locate power-intensive compute infrastructure near predictable, low-cost energy sources. Crusoe’s project applies a similar logic but adapts it for a variable grid environment. Instead of relying on a fixed low-cost power source like hydro, Crusoe dynamically adjusts to real-time energy availability, a strategy that could become a model for future power-aware, AI-driven workloads. Compass and Aligned: Modular, Energy-Adaptive

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Executive Roundtable: Data Center Site Selection and Market Evolution in a Constrained Environment

For the third installment of our Executive Roundtable for the First Quarter of 2025, we asked our panel of seasoned industry experts about how the dynamics of data center site selection have never been more complex—or more critical to long-term success. In an industry where speed to market is paramount, operators must now navigate an increasingly constrained landscape in the age of AI, ultra cloud and hyperscale expansion, marked by fierce competition for land, tightening power availability, and evolving local regulations.  Traditional core markets such as Northern Virginia, Dallas, and Phoenix remain essential, but supply constraints and permitting challenges are prompting developers to rethink their approach. As hyperscalers and colocation providers push the boundaries of site selection strategy, secondary and edge markets are emerging as viable alternatives, driven by favorable energy economics, infrastructure investment, and shifting customer demand.  At the same time, power procurement is now reshaping the equation. With grid limitations and interconnection delays creating uncertainty in major hubs, operators are exploring new solutions, from direct utility partnerships to on-site generation with renewables, natural gas, and burgeoning modular nuclear concepts. The question now is not just where to build but how to ensure long-term operational resilience. As data center demand accelerates, operators face mounting challenges in securing suitable land, reliable power, and regulatory approvals in both established and emerging markets.  And so we asked our distinguished executive panel for the First Quarter of 2025, with grid capacity constraints, zoning complexities, and heightened competition shaping development decisions, how are companies refining their site selection strategies in Q1 2025 to balance speed to market, scalability, and sustainability? And, which North American regions are showing the greatest potential as the next wave of data center expansion takes shape?

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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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