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Beyond compliance: A collaborative approach to wildfire and extreme weather resilience

As climate-related perils intensify, the relationship between electric utilities and the communities they serve is under immense pressure. The twin threats of wildfires and extreme weather events, fueled by shifting weather patterns, are both urgent and tangible realities. Electric utilities face the difficult task of balancing system reliability, public safety, and cost. To truly build […]

As climate-related perils intensify, the relationship between electric utilities and the communities they serve is under immense pressure. The twin threats of wildfires and extreme weather events, fueled by shifting weather patterns, are both urgent and tangible realities. Electric utilities face the difficult task of balancing system reliability, public safety, and cost. To truly build a resilient and safe system at a reasonable cost, a more proactive and collaborative partnership is needed between electric utilities and their state PUCs. This partnership must move beyond typical regulatory frameworks and embrace a shared commitment to risk reduction that leverages advanced data technology and weather intelligence to inform decisions and planning under constantly changing conditions.

Quantifying Investment in Community Safety

Asset hardening is one part of a typical electric utility Wildfire Mitigation Plan submitted by utilities for their regulators’ approval. A data-driven strategy empowers electric utilities to move beyond simply “asset improvements by geography” and instead, move to more dynamic risk-based asset investment efforts with surgical precision. By identifying the highest-risk areas on a continuous basis, electric utilities can ensure that their budget is spent most efficiently, maximizing the risk reduction per dollar invested. This concept of “risk-spend-efficiency,” or similar metrics like “cost benefit ratios,” are crucial for an electric utility to track and powerful tools for demonstrating to a PUC how investments are directly and optimally translating into enhanced and quantifiable community safety.

The benefits of a collaborative, data-driven model are also apparent during a necessary, last-resort, Public Safety Power Shutoff (PSPS) event. With advanced AI-based risk modeling, an electric utility can move from a reactive and broad-brush approach, to a targeted and surgical one. Several electric utilities in the western United States leverage advanced data to get much more precise in their actions. Instead of shutting off power across a wide area under a Red Flag Warning – which can impact hundreds of thousands of customers – they instead identify and de-energize only the few circuits that are actually at risk of igniting a fire and greatly reduce any impact. This level of precision minimizes customer impact, improves restoration times, and maximizes community safety.

Leveraging Dynamic Risk Intelligence

At the heart of examples like these lies a profound shift in how risk is understood and managed. Instead of relying on static, historical data, electric utilities can now employ dynamic, high-resolution validated wildfire and weather models. These models – tailored specifically for fire weather and other extreme weather conditions – can forecast potential risks across multiple time horizons using real-time changing weather and fuel conditions, something that static data cannot do. Feeding this data into sophisticated wildfire spread models, electric utilities can pinpoint areas where a potential ignition could have catastrophic consequences, like impacting homes or critical infrastructure. This insight allows for a granular, asset-level understanding of an electric utility’s risk, moving beyond broad warnings like a “Red Flag Warning” to a targeted view of where risk-reduction action is most needed.

A New Standard for Transparency and Trust

In the collaboration between electric utilities and PUC, this kind of intelligence provides the basis for critical reporting and trust. It allows electric utilities to clearly document their decision-making process and demonstrate how their actions were informed by high-resolution dynamic data under a variety of scenarios. Further, it enables PUC’s and electric utilities to measure progress over time and make adjustments as conditions change. For PSPS events, they can even simulate the potential consequences of a wildfire had the power not been shut off, quantifying the acres, structures, and lives that were saved. This ability builds transparency, allowing the PUC to see a clear justification for the electric utility’s actions, which in turn helps balance the necessary risk mitigation with the costs to consumers.

This same data-driven approach, used to identify wildfire risk, can equally inform strategies for extreme weather events. By analyzing decades of high-resolution historical weather data, electric utilities can establish a new climatology for their service territory, understanding what constitutes a “99th percentile” wind event or an unusually heavy snowstorm. This not only allows them to update their asset-hardening standards to build for greater resilience but also provides a quantifiable metric for assessing the effectiveness of their mitigation efforts.

In the face of unprecedented environmental challenges, the partnership between electric utilities and their state PUCs can and will evolve. By embracing a shared commitment to data-driven risk management, electric utilities can exceed regulatory requirements, build a more resilient system, and protect the communities they serve. This is no longer just about compliance; it is about proactive, collaborative, and intelligent risk reduction. It is about working together to build a safer and more reliable grid for the future.

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F5 to acquire CalypsoAI for advanced AI security capabilities

CalypsoAI’s platform creates what the company calls an Inference Perimeter that protects across models, vendors, and environments. The offers several products including Inference Red Team, Inference Defend, and Inference Observe, which deliver adversarial testing, threat detection and prevention, and enterprise oversight, respectively, among other capabilities. CalypsoAI says its platform proactively

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HomeLM: A foundation model for ambient AI

Capabilities of a HomeLM What makes a foundation model like HomeLM powerful is its ability to learn generalizable representations of sensor streams, allowing them to be reused, recombined and adapted across diverse tasks. This fundamentally differs from traditional signal processing and machine learning pipelines in RF sensing, which are typically

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Cisco’s Splunk embeds agentic AI into security and observability products

AI-powered observability enhancements Cisco also announced it has updated Splunk Observability to use Cisco AgenticOps, which deploys AI agents to automate telemetry collection, detect issues, identify root causes, and apply fixes. The agentic AI updates help enterprise customers automate incident detection, root-cause analysis, and routine fixes. “We are making sure

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MOL Discovers New Oil Field

In a statement posted on its website recently, MOL announced that it and O&GD have discovered a new oil field at a depth of approximately 2,400 meters (7,874 feet) near Galgahévíz, Hungary. “The Galgahévíz-4 well is capable of producing approximately 1,000 barrels of crude oil per day, which will be processed at the Danube Refinery in Százhalombatta,” MOL said in the statement, which highlighted that “O&GD and MOL share the extracted volume in a 51 percent-49 percent ratio”. The Galgahévíz-4 well contributes approximately 0.5 percent to MOL Group’s hydrocarbon production, according to the statement. “The new deposit contributes significantly to Hungary’s security of supply, as domestic production reduces import dependency,” György Bacsa, Managing Director of MOL Hungary, said in the statement. “Uncertainties surrounding supply routes also confirm that the more pipelines there are in the region, the more certain it is that there will always be enough energy,” Bacsa added. “However, the best source is always domestic, which is why MOL treats hydrocarbon exploration in Hungary as a priority,” Bacsa went on to state. Rigzone has contacted O&GD for comment on the discovery of the oil field. At the time of writing, the company has not responded to Rigzone. The Danube Refinery started its operation in 1965, MOL’s website states, adding that the refinery belongs to MOL Plc. It is one of the largest refineries in the Central and Eastern European region with a refining capacity of 165,000 barrels per day, MOL’s site notes. In a release posted on its website back in March, MOL said it had discovered a new oil field near Somogysámson in Western Hungary. “During the exploration drilling carried out in December last year, oil was found at a depth of 1,250 meters (4,101 feet),” the company said in that release. “According to the results, the

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Beyond compliance: A collaborative approach to wildfire and extreme weather resilience

As climate-related perils intensify, the relationship between electric utilities and the communities they serve is under immense pressure. The twin threats of wildfires and extreme weather events, fueled by shifting weather patterns, are both urgent and tangible realities. Electric utilities face the difficult task of balancing system reliability, public safety, and cost. To truly build a resilient and safe system at a reasonable cost, a more proactive and collaborative partnership is needed between electric utilities and their state PUCs. This partnership must move beyond typical regulatory frameworks and embrace a shared commitment to risk reduction that leverages advanced data technology and weather intelligence to inform decisions and planning under constantly changing conditions. Quantifying Investment in Community Safety Asset hardening is one part of a typical electric utility Wildfire Mitigation Plan submitted by utilities for their regulators’ approval. A data-driven strategy empowers electric utilities to move beyond simply “asset improvements by geography” and instead, move to more dynamic risk-based asset investment efforts with surgical precision. By identifying the highest-risk areas on a continuous basis, electric utilities can ensure that their budget is spent most efficiently, maximizing the risk reduction per dollar invested. This concept of “risk-spend-efficiency,” or similar metrics like “cost benefit ratios,” are crucial for an electric utility to track and powerful tools for demonstrating to a PUC how investments are directly and optimally translating into enhanced and quantifiable community safety. The benefits of a collaborative, data-driven model are also apparent during a necessary, last-resort, Public Safety Power Shutoff (PSPS) event. With advanced AI-based risk modeling, an electric utility can move from a reactive and broad-brush approach, to a targeted and surgical one. Several electric utilities in the western United States leverage advanced data to get much more precise in their actions. Instead of shutting off power across a wide

Read More »

Choosing the right electrical conduit for underground transmission and distribution utility projects

For underground transmission and distribution utility projects, conduit systems must be resilient, cost-effective, and support efficient cable pulling through various terrain. However, traditional materials often introduce challenges, including elbow burn-through, complex installations, heavy conduits, long pulls, and high costs. Let’s break down each of these issues and explore solutions. Utility project challenges Cost: Traditional conduit materials like steel and PVC-coated steel are significantly heavier than other options. Heavier conduit increases labor, material costs, and handling challenges. Complex Buried Installation: Utility projects frequently involve complex, underground installation. Heavy conduit materials require not only extensive equipment but also manpower, adding risk and time to the installation. Elbow Burn-Through: Traditional elbows used in underground systems, such as PVC, can experience burn-through, particularly with high friction from dense, extended cable pulls. Burn-through compromises system integrity and requires costly conduit repairs or replacements. Long Cable Pulls: Long pulls with traditional conduit can produce excessive friction, increasing installation time and the likelihood of conduit or cable damage, particularly at bends. Fault concerns: Cable faults that meld or weld to the inside of the conduit cause expensive repairs. Fiberglass conduit elbows: Practical solutions for utilities Fiberglass conduit elbows address each of these challenges, providing essential benefits that lead to better project outcomes. Lower material and installation costs: Fiberglass elbows are significantly lighter than alternatives such as GRC, PVC-coated steel and most sizes of PVC, lowering material and installation costs. Labor is reduced because the lightweight material allows installers to position and connect elbows faster without specialized equipment. Made in America fiberglass conduit offers substantial savings in both material costs, labor efficiency, and also shipping costs. Seamless installation: Fiberglass elbows are lighter and easier to handle than traditional options, simplifying buried installations. Fiberglass installs faster than many sizes of electrical conduit types per the NECA Manual of Labor

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Battery safety starts before the first spark

Engineers once designed our cars to brace for impact. Progress was measured in crash survival, so they built sturdier frames, added seatbelts, and improved airbags. These safety improvements were vital, but they were designed to minimise damage rather than prevent crashes from happening in the first place. Technology today has come a long way, allowing the automotive industry to expand its approach. New features like lane-departure warnings, intelligent speed assistance, and blind spot sensors have moved safety features upstream. This advanced safety strategy has saved countless lives and reshaped how the entire car industry designs, tests, and markets its products. It is time for energy storage to adopt a similar approach. In the past year alone, battery storage incidents have disrupted energy operations across multiple states. As the industry scales, so do the risks—and the need for a new safety paradigm. The sector has invested heavily in refining what happens if a battery system safety incident occurs. Sensors detect abnormal heat or off-gas. Containment limits the spread. These measures are critical, but they are designed to activate once damage is already underway. Even the fastest detection and mitigation systems may not intervene before serious damage to the battery storage system occurs. This is akin to relying on airbags without the benefits of a car’s collision avoidance technology: valuable, but purely reactive rather than preventive and proactive. From reaction to prevention: A new safety paradigm To make battery energy storage safer at scale, systems must be designed to intervene earlier—before conditions can become explosive. This means addressing the incidents at the source. Battery storage safety incidents can be caused by an accumulation of flammable gases released during thermal runaway, where heat builds inside a battery cell faster than it can be dissipated. Inside a battery enclosure, these gases can mix with

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Kuwait Said to Mull Pipeline Deal to Raise Billions

Kuwait Petroleum Corp. is considering leasing part of its pipeline network to help fund a $65 billion investment plan that covers everything from upstream to petrochemicals, according to people familiar with the matter. Centerview Partners LLC is advising the state-backed firm on the deal, one of the people said, asking not to be identified discussing non-public information. The transaction would likely be similar to those done by neighboring Gulf states like Saudi Arabia and the United Arab Emirates that have sought to monetize government assets to attract foreign investment.  KPC is aiming to raise $5 billion to $7 billion through the deal, two of the people said. As part of the transaction, the firm is weighing leasing 13 pipelines over 25 years, the people said. Deliberations are ongoing and no final decisions have been made, the people said. The plan would also still require the final approval of the government of Kuwait, which is OPEC’s fifth-biggest producer.  Representatives for KPC and Centerview declined to comment. Foreign Investment KPC’s investment program, which began in April 2024, includes plans to spend about $33 billion on boosting oil production capacity toward a 4 million barrel-a-day target by 2035. Chief Executive Officer Sheikh Nawaf Al-Sabah told Bloomberg News in November that the firm is considering multiple funding sources for future projects, including possible pipeline deals. “I’m looking at where the cheapest money is going to come from,” Sheikh Nawaf said in an interview. “If it comes from a pipeline monetization deal, which would be open to domestic and foreign investors, like what Adnoc and Aramco did recently, I’ll pursue that.”  Any such agreement would likely be done through “lease and leasebacks,” he said at the time. The latest deliberations come just weeks after BlackRock Inc.’s Global Infrastructure Partners signed a $11 billion deal to lease the

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New Balder FPSO Reaches Production Capacity

The Jotun floating production, storage and offloading platform (FPSO) of the Balder field on Norway’s side of the North Sea reached peak production of over 80,000 barrels of oil equivalent a day (boed) gross, operator Var Energi ASA said. Jotun ramped up to capacity earlier than expected, after starting production June, the Stavanger-headquartered Norwegian continental shelf (NCS) producer said in a statement on its website. “All 14 subsea production wells are now online and are on average producing in line with expectations, and work is ongoing to further optimize the production from Jotun FSPO”, Var Energi said. “The Balder Phase V and VI projects are underway and will add additional capacity, maintaining high production from the Balder area going forward”. The new capacity adds to “current production of around 30,000 boed gross combined from the Balder floating production unit and Ringhorne facilities”, the statement said. The wider Balder hub, which includes the Breidablikk and Grane fields, accounted for 20 percent of Var Energi’s 2024 output and 276 million boe of proven and probable reserves at the end of the year, the company says on its website. “The rapid ramp-up to peak production at the Jotun FPSO, alongside strong performance across our portfolio, puts us on track to meet our production target of around 430,000 boed in the fourth quarter of this year”, chief executive Nick Walker said in the statement. “With the new facilities in the Balder area designed to extend production beyond 2045 we are on track to create more value from the area”. Var Energi, 63.04 percent-owned by Italy’s state-controlled Eni SpA, has a 90 percent stake in the Balder field. Kistos Energy Norway AS owns 10 percent. Last month Var Energi said it had approved four of more than 10 projects for which it expects to make

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There are 121 AI processor companies. How many will succeed?

The US currently leads in AI hardware and software, but China’s DeepSeek and Huawei continue to push advanced chips, India has announced an indigenous GPU program targeting production by 2029, and policy shifts in Washington are reshaping the playing field. In Q2, the rollback of export restrictions allowed US companies like Nvidia and AMD to strike multibillion-dollar deals in Saudi Arabia.  JPR categorizes vendors into five segments: IoT (ultra-low-power inference in microcontrollers or small SoCs); Edge (on-device or near-device inference in 1–100W range, used outside data centers); Automotive (distinct enough to break out from Edge); data center training; and data center inference. There is some overlap between segments as many vendors play in multiple segments. Of the five categories, inference has the most startups with 90. Peddie says the inference application list is “humongous,” with everything from wearable health monitors to smart vehicle sensor arrays, to personal items in the home, and every imaginable machine in every imaginable manufacturing and production line, plus robotic box movers and surgeons.  Inference also offers the most versatility. “Smart devices” in the past, like washing machines or coffee makers, could do basically one thing and couldn’t adapt to any changes. “Inference-based systems will be able to duck and weave, adjust in real time, and find alternative solutions, quickly,” said Peddie. Peddie said despite his apparent cynicism, this is an exciting time. “There are really novel ideas being tried like analog neuron processors, and in-memory processors,” he said.

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Data Center Jobs: Engineering, Construction, Commissioning, Sales, Field Service and Facility Tech Jobs Available in Major Data Center Hotspots

Each month Data Center Frontier, in partnership with Pkaza, posts some of the hottest data center career opportunities in the market. Here’s a look at some of the latest data center jobs posted on the Data Center Frontier jobs board, powered by Pkaza Critical Facilities Recruiting. Looking for Data Center Candidates? Check out Pkaza’s Active Candidate / Featured Candidate Hotlist (and coming soon free Data Center Intern listing). Data Center Critical Facility Manager Impact, TX There position is also available in: Cheyenne, WY; Ashburn, VA or Manassas, VA. This opportunity is working directly with a leading mission-critical data center developer / wholesaler / colo provider. This firm provides data center solutions custom-fit to the requirements of their client’s mission-critical operational facilities. They provide reliability of mission-critical facilities for many of the world’s largest organizations (enterprise and hyperscale customers). This career-growth minded opportunity offers exciting projects with leading-edge technology and innovation as well as competitive salaries and benefits. Electrical Commissioning Engineer New Albany, OH This traveling position is also available in: Richmond, VA; Ashburn, VA; Charlotte, NC; Atlanta, GA; Hampton, GA; Fayetteville, GA; Cedar Rapids, IA; Phoenix, AZ; Dallas, TX or Chicago, IL. *** ALSO looking for a LEAD EE and ME CxA Agents and CxA PMs. *** Our client is an engineering design and commissioning company that has a national footprint and specializes in MEP critical facilities design. They provide design, commissioning, consulting and management expertise in the critical facilities space. They have a mindset to provide reliability, energy efficiency, sustainable design and LEED expertise when providing these consulting services for enterprise, colocation and hyperscale companies. This career-growth minded opportunity offers exciting projects with leading-edge technology and innovation as well as competitive salaries and benefits.  Data Center Engineering Design ManagerAshburn, VA This opportunity is working directly with a leading mission-critical data center developer /

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Modernizing Legacy Data Centers for the AI Revolution with Schneider Electric’s Steven Carlini

As artificial intelligence workloads drive unprecedented compute density, the U.S. data center industry faces a formidable challenge: modernizing aging facilities that were never designed to support today’s high-density AI servers. In a recent Data Center Frontier podcast, Steven Carlini, Vice President of Innovation and Data Centers at Schneider Electric, shared his insights on how operators are confronting these transformative pressures. “Many of these data centers were built with the expectation they would go through three, four, five IT refresh cycles,” Carlini explains. “Back then, growth in rack density was moderate. Facilities were designed for 10, 12 kilowatts per rack. Now with systems like Nvidia’s Blackwell, we’re seeing 132 kilowatts per rack, and each rack can weigh 5,000 pounds.” The implications are seismic. Legacy racks, floor layouts, power distribution systems, and cooling infrastructure were simply not engineered for such extreme densities. “With densification, a lot of the power distribution, cooling systems, even the rack systems — the new servers don’t fit in those racks. You need more room behind the racks for power and cooling. Almost everything needs to be changed,” Carlini notes. For operators, the first questions are inevitably about power availability. At 132 kilowatts per rack, even a single cluster can challenge the limits of older infrastructure. Many facilities are conducting rigorous evaluations to decide whether retrofitting is feasible or whether building new sites is the more practical solution. Carlini adds, “You may have transformers spaced every hundred yards, twenty of them. Now, one larger transformer can replace that footprint, and power distribution units feed busways that supply each accelerated compute rack. The scale and complexity are unlike anything we’ve seen before.” Safety considerations also intensify with these densifications. “At 132 kilowatts, maintenance is still feasible,” Carlini says, “but as voltages rise, data centers are moving toward environments where

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Google Backs Advanced Nuclear at TVA’s Clinch River as ORNL Pushes Quantum Frontiers

Inside the Hermes Reactor Design Kairos Power’s Hermes reactor is based on its KP-FHR architecture — short for fluoride salt–cooled, high-temperature reactor. Unlike conventional water-cooled reactors, Hermes uses a molten salt mixture called FLiBe (lithium fluoride and beryllium fluoride) as a coolant. Because FLiBe operates at atmospheric pressure, the design eliminates the risk of high-pressure ruptures and allows for inherently safer operation. Fuel for Hermes comes in the form of TRISO particles rather than traditional enriched uranium fuel rods. Each TRISO particle is encapsulated within ceramic layers that function like miniature containment vessels. These particles can withstand temperatures above 1,600 °C — far beyond the reactor’s normal operating range of about 700 °C. In combination with the salt coolant, Hermes achieves outlet temperatures between 650–750 °C, enabling efficient power generation and potential industrial applications such as hydrogen production. Because the salt coolant is chemically stable and requires no pressurization, the reactor can shut down and dissipate heat passively, without external power or operator intervention. This passive safety profile differentiates Hermes from traditional light-water reactors and reflects the Generation IV industry focus on safer, modular designs. From Hermes-1 to Hermes-2: Iterative Nuclear Development The first step in Kairos’ roadmap is Hermes-1, a 35 MW thermal demonstration reactor now under construction at TVA’s Clinch River site under a 2023 NRC license. Hermes-1 is not designed to generate electricity but will validate reactor physics, fuel handling, licensing strategies, and construction techniques. Building on that experience, Hermes-2 will be a 50 MW electric reactor connected to TVA’s grid, with operations targeted for 2030. Under the agreement, TVA will purchase electricity from Hermes-2 and supply it to Google’s data centers in Tennessee and Alabama. Kairos describes its development philosophy as “iterative,” scaling incrementally rather than attempting to deploy large fleets of units at once. By

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NVIDIA Forecasts $3–$4 Trillion AI Market, Driving Next Wave of Infrastructure

Whenever behemoth chipmaker NVIDIA announces its quarterly earnings, those results can have a massive influence on the stock market and its position as a key indicator for the AI industry. After all, NVIDIA is the most valuable publicly traded company in the world, valued at $4.24 trillion—ahead of Microsoft ($3.74 trillion), Apple ($3.41 trillion), Alphabet, the parent company of Google ($2.57 trillion), and Amazon ($2.44 trillion). Due to its explosive growth in recent years, a single NVIDIA earnings report can move the entire market. So, when NVIDIA leaders announced during their August 27 earnings call that Q2 2026 sales surged 56% to $46.74 billion, it was a record-setting performance for the company—and investors took notice. Executive VP & CFO Colette M. Kress said the revenue exceeded leadership’s outlook as the company grew sequentially across all market platforms. She outlined a path toward substantial growth driven by AI infrastructure. Foreseeing significant long-term growth opportunities in agentic AI and considering the scale of opportunity, CEO Jensen Huang said, “Over the next 5 years, we’re going to scale into it with Blackwell [architecture for GenAI], with Rubin [successor to Blackwell], and follow-ons to scale into effectively a $3 trillion to $4 trillion AI infrastructure opportunity.” The chipmaker’s Q2 2026 earnings fell short of Wall Street’s lofty expectations, but they did demonstrate that its sales are still rising faster than those of most other tech companies. NVIDIA is expected to post revenue growth of at least 42% over the next four quarters, compared with an average of about 10% for firms in the technology-heavy Nasdaq 100 Index, according to data compiled by Bloomberg Intelligence. On August 29, two days after announcing their earnings, NVIDIA stocks slid 3% and other chip stocks also declined. This came amid a broader sell-off after server-maker Dell, a customer of those chipmakers,

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Cologix and Lambda Debut NVIDIA HGX B200 AI Clusters in Columbus, Ohio

In our latest episode of the Data Center Frontier Show, we explore how powerhouse AI infrastructure is moving inland—anchored by the first NVIDIA HGX B200 cluster deployment in Columbus, Ohio. Cologix, Lambda, and Supermicro have partnered on the project, which combines Lambda’s 1-Click Clusters™, Supermicro’s energy-efficient hardware, and Cologix’s carrier-dense Scalelogix℠ COL4 facility. It’s a milestone that speaks to the rapid decentralization of AI workloads and the emergence of the Midwest as a serious player in the AI economy. Joining me for the conversation were Bill Bentley, VP Hyperscale and Cloud Sales at Cologix, and Ken Patchett, VP Data Center Infrastructure at Lambda. Why Columbus, Why Now? Asked about the significance of launching in Columbus, Patchett framed the move in terms of the coming era of “superintelligence.” “The shift to superintelligence is happening now—systems that can reason, adapt, and accelerate human progress,” Patchett said. “That requires an entirely new type of infrastructure, which means capital, vision, and the right partners. Columbus with Cologix made sense because beyond being centrally located, they’re highly connected, cost-efficient, and built to scale. We’re not chasing trends. We’re laying the groundwork for a future where intelligence infrastructure is as ubiquitous as electricity.” Bentley pointed to the city’s underlying strengths in connectivity, incentives, and utility economics. “Columbus is uniquely situated at the intersection of long-haul fiber,” Bentley said. “You’ve got state tax incentives, low-cost utilities, and a growing concentration of hyperscalers and local enterprises. The ecosystem is ripe for growth. It’s a natural geography for AI workloads that need geographic diversity without sacrificing performance.” Shifting—or Expanding—the Map for AI The guests agreed that deployments like this don’t represent a wholesale shift away from coastal hyperscale markets, but rather the expansion of AI’s footprint across multiple geographies. “I like to think of Lambda as an AI hyperscaler,”

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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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