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Trican to Acquire Tubing Services Firm Iron Horse

Calgary, Alberta-based Trican Well Service Ltd. said it has entered into an agreement to acquire privately owned fracturing and coiled tubing services provider Iron Horse Energy Services, which operates primarily in the Cardium, Charlie Lake, Mannville Stack, Viking, Montney and Shaunavon plays in the Western Canadian Sedimentary Basin (WCSB). Trican aims to acquire all of […]

Calgary, Alberta-based Trican Well Service Ltd. said it has entered into an agreement to acquire privately owned fracturing and coiled tubing services provider Iron Horse Energy Services, which operates primarily in the Cardium, Charlie Lake, Mannville Stack, Viking, Montney and Shaunavon plays in the Western Canadian Sedimentary Basin (WCSB).

Trican aims to acquire all of the issued and outstanding shares of Iron Horse for approximately $56.6 million (CAD 77.35 million) in cash and approximately 33.76 million common shares of Trican, the company said in a news release.

Iron Horse “extends Trican’s fracturing footprint and adds industry-leading coiled tubing integrated fracturing expertise,” according to the release.

The acquisition will add over four fracturing spreads and 10 coiled tubing units, which will augment Trican’s services offering throughout the WCSB across the drilling, completion, and production lifecycles, the company said.

Following the acquisition, Iron Horse will operate as a wholly owned division of Trican, continuing to serve its existing customers while increasing its footprint with the support of Trican’s resources. Trican said it expects to retain all of the existing management and employees of Iron Horse.

The acquisition is expected to close in the second half. Iron Horse Chairman and CEO Tom Coolen will be appointed to the board of directors of Trican after closing, according to the release.

Other than Competition Act Approval, and TSX listing approval of the common shares of Trican to be issued pursuant to the Acquisition, no approval, order, consent of or filing with any government agency is required on the part of Iron Horse or Trican, in connection with the completion of the acquisition, Trican said.

“Iron Horse is one of [the] few North American fracturing companies that has consistently demonstrated operational and financial performance that aligns with Trican. The acquisition will provide significant EBITDA, free cash flow and earnings accretion to Trican shareholders. It will also expand Trican’s customer base into both conventional and unconventional plays in Alberta and Saskatchewan,” Trican President and CEO Brad Fedora said.

“Mr. Coolen and his partners have built their company into a trusted and innovative services provider, and we look forward to welcoming him to the Board and benefitting from his 20-plus years of industry experience to create incremental value for Trican shareholders,” Fedora added.

“Trican is widely considered among the top completions services providers in North America and has developed this reputation through a focus on the same core values that Iron Horse has demonstrated for two decades. Together, we will continue to deliver exceptional service to existing and prospective clients and create new career opportunities for both Iron Horse and Trican employees,” Coolen said.

Trican said it expects to use the additional free cash flow provided by the acquisition to execute strategic growth, repay the credit facility, and/or return to shareholders through share repurchases and future dividend growth.

Trican’s board also approved a 10 percent increase to Trican’s dividend following the closing of the acquisition. The dividend will be boosted to $0.055 per share from $0.050 per share, which equates to $0.220 per share on an annual basis.

The first distribution of the increased dividend will be made on September 30 to shareholders of record as of September 12. The increase in Trican’s base dividend will be funded by a portion of the free cash flow from the acquisition, the company said.

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Trican to Acquire Tubing Services Firm Iron Horse

Calgary, Alberta-based Trican Well Service Ltd. said it has entered into an agreement to acquire privately owned fracturing and coiled tubing services provider Iron Horse Energy Services, which operates primarily in the Cardium, Charlie Lake, Mannville Stack, Viking, Montney and Shaunavon plays in the Western Canadian Sedimentary Basin (WCSB). Trican aims to acquire all of the issued and outstanding shares of Iron Horse for approximately $56.6 million (CAD 77.35 million) in cash and approximately 33.76 million common shares of Trican, the company said in a news release. Iron Horse “extends Trican’s fracturing footprint and adds industry-leading coiled tubing integrated fracturing expertise,” according to the release. The acquisition will add over four fracturing spreads and 10 coiled tubing units, which will augment Trican’s services offering throughout the WCSB across the drilling, completion, and production lifecycles, the company said. Following the acquisition, Iron Horse will operate as a wholly owned division of Trican, continuing to serve its existing customers while increasing its footprint with the support of Trican’s resources. Trican said it expects to retain all of the existing management and employees of Iron Horse. The acquisition is expected to close in the second half. Iron Horse Chairman and CEO Tom Coolen will be appointed to the board of directors of Trican after closing, according to the release. Other than Competition Act Approval, and TSX listing approval of the common shares of Trican to be issued pursuant to the Acquisition, no approval, order, consent of or filing with any government agency is required on the part of Iron Horse or Trican, in connection with the completion of the acquisition, Trican said. “Iron Horse is one of [the] few North American fracturing companies that has consistently demonstrated operational and financial performance that aligns with Trican. The acquisition will provide significant EBITDA, free cash

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CoreWeave acquires Core Scientific for $9B to power AI infrastructure push

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CoreWeave achieves a first with Nvidia GB300 NVL72 deployment

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Oracle to power OpenAI’s AGI ambitions with 4.5GW expansion

“For CIOs, this shift means more competition for AI infrastructure. Over the next 12–24 months, securing capacity for AI workloads will likely get harder, not easier. Though cost is coming down but demand is increasing as well, due to which CIOs must plan earlier and build stronger partnerships to ensure availability,” said Pareekh Jain, CEO at EIIRTrend & Pareekh Consulting. He added that CIOs should expect longer wait times for AI infrastructure. To mitigate this, they should lock in capacity through reserved instances, diversify across regions and cloud providers, and work with vendors to align on long-term demand forecasts.  “Enterprises stand to benefit from more efficient and cost-effective AI infrastructure tailored to specialized AI workloads, significantly lower their overall future AI-related investments and expenses. Consequently, CIOs face a critical task: to analyze and predict the diverse AI workloads that will prevail across their organizations, business units, functions, and employee personas in the future. This foresight will be crucial in prioritizing and optimizing AI workloads for either in-house deployment or outsourced infrastructure, ensuring strategic and efficient resource allocation,” said Neil Shah, vice president at Counterpoint Research. Strategic pivot toward AI data centers The OpenAI-Oracle deal comes in stark contrast to developments earlier this year. In April, AWS was reported to be scaling back its plans for leasing new colocation capacity — a move that AWS Vice President for global data centers Kevin Miller described as routine capacity management, not a shift in long-term expansion plans. Still, these announcements raised questions around whether the hyperscale data center boom was beginning to plateau. “This isn’t a slowdown, it’s a strategic pivot. The era of building generic data center capacity is over. The new global imperative is a race for specialized, high-density, AI-ready compute. Hyperscalers are not slowing down; they are reallocating their capital to

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Arista Buys VeloCloud to reboot SD-WANs amid AI infrastructure shift

What this doesn’t answer is how Arista Networks plans to add newer, security-oriented Secure Access Service Edge (SASE) capabilities to VeloCloud’s older SD-WAN technology. Post-acquisition, it still has only some of the building blocks necessary to achieve this. Mapping AI However, in 2025 there is always more going on with networking acquisitions than simply adding another brick to the wall, and in this case it’s the way AI is changing data flows across networks. “In the new AI era, the concepts of what comprises a user and a site in a WAN have changed fundamentally. The introduction of agentic AI even changes what might be considered a user,” wrote Arista Networks CEO, Jayshree Ullal, in a blog highlighting AI’s effect on WAN architectures. “In addition to people accessing data on demand, new AI agents will be deployed to access data independently, adapting over time to solve problems and enhance user productivity,” she said. Specifically, WANs needed modernization to cope with the effect AI traffic flows are having on data center traffic. Sanjay Uppal, now VP and general manager of the new VeloCloud Division at Arista Networks, elaborated. “The next step in SD-WAN is to identify, secure and optimize agentic AI traffic across that distributed enterprise, this time from all end points across to branches, campus sites, and the different data center locations, both public and private,” he wrote. “The best way to grab this opportunity was in partnership with a networking systems leader, as customers were increasingly looking for a comprehensive solution from LAN/Campus across the WAN to the data center.”

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Data center capacity continues to shift to hyperscalers

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Oracle inks $30 billion cloud deal, continuing its strong push into AI infrastructure.

He pointed out that, in addition to its continued growth, OCI has a remaining performance obligation (RPO) — total future revenue expected from contracts not yet reported as revenue — of $138 billion, a 41% increase, year over year. The company is benefiting from the immense demand for cloud computing largely driven by AI models. While traditionally an enterprise resource planning (ERP) company, Oracle launched OCI in 2016 and has been strategically investing in AI and data center infrastructure that can support gigawatts of capacity. Notably, it is a partner in the $500 billion SoftBank-backed Stargate project, along with OpenAI, Arm, Microsoft, and Nvidia, that will build out data center infrastructure in the US. Along with that, the company is reportedly spending about $40 billion on Nvidia chips for a massive new data center in Abilene, Texas, that will serve as Stargate’s first location in the country. Further, the company has signaled its plans to significantly increase its investment in Abu Dhabi to grow out its cloud and AI offerings in the UAE; has partnered with IBM to advance agentic AI; has launched more than 50 genAI use cases with Cohere; and is a key provider for ByteDance, which has said it plans to invest $20 billion in global cloud infrastructure this year, notably in Johor, Malaysia. Ellison’s plan: dominate the cloud world CTO and co-founder Larry Ellison announced in a recent earnings call Oracle’s intent to become No. 1 in cloud databases, cloud applications, and the construction and operation of cloud data centers. He said Oracle is uniquely positioned because it has so much enterprise data stored in its databases. He also highlighted the company’s flexible multi-cloud strategy and said that the latest version of its database, Oracle 23ai, is specifically tailored to the needs of AI workloads. Oracle

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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

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2025 playbook for enterprise AI success, from agents to evals

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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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