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Land and Expand: The Gigawatt Credibility Test

The midsummer wave of U.S. data center development is not defined by a single market, developer or technology company. It stretches from the Georgia coast to West Texas, from the industrial Midwest to the Mississippi River. What links the projects announced since early June is not just their scale, it is the realization that scale […]

The midsummer wave of U.S. data center development is not defined by a single market, developer or technology company. It stretches from the Georgia coast to West Texas, from the industrial Midwest to the Mississippi River. What links the projects announced since early June is not just their scale, it is the realization that scale alone is not enough.

Developers are still announcing multibillion-dollar campuses and gigawatt power requirements, but the language surrounding those announcements has changed. Companies are emphasizing who will pay for new generation and transmission, how cooling systems will limit water consumption, what communities will receive beyond temporary construction employment, and when contracted customers will begin occupying capacity. In several cases, the announcement is less about acquiring land than proving that a project has become commercially and electrically credible.  As we have seen progressing through the industry, the latest announcements point toward campuses that combine compute, power, financing and community agreements in one development package.

OpenAI Goes Direct in Georgia

OpenAI, on July 22 disclosed Project Camellia, a long-term data center development in Effingham County, Georgia. OpenAI said it is designing and developing the campus itself and has contracted with Georgia Power for 3.2 gigawatts of electricity, to be delivered in phases from 2028 through 2032. The project has been reported as a roughly $20 billion investment on approximately 1,400 acres, making it one of the largest individual data center proposals currently moving through the U.S. pipeline.

Project Camellia is notable not only for its size but for OpenAI’s more direct role. The company has traditionally secured capacity through cloud providers and infrastructure partners. By taking responsibility for designing and developing the Georgia campus, OpenAI is signaling that control over power, schedule and facility design has become strategically important as AI companies compete for increasingly scarce large-scale capacity. The project remains early in development, with infrastructure, phasing, financing and operating details still to be completed.

OpenAI paired the announcement with a detailed community compact framework. It pledged to pay the full cost of infrastructure and electric service, use a closed-loop cooling system, provide $80 million in community benefits, make as much as $71 million in Codex credits available to eligible Georgia students, and commission an annual independent audit of its commitments. It also said the campus would be designed to reduce power consumption during periods of high grid demand before residential customers are affected.

The package treats community engagement as part of the infrastructure stack rather than a public-relations exercise begun after zoning approval.

Microsoft Pairs 2 Gigawatts of Capacity With Dedicated West Texas Power

Microsoft delivered another defining announcement on June 22, unveiling a new data center campus in Pecos, Texas, that would add approximately 2 gigawatts to its global capacity. The company described the project as one of the largest single capacity additions in its history and said the multibillion-dollar investment would unfold over five to seven years, supporting more than 6,000 construction jobs at peak and hundreds of permanent operating positions.

The central feature of the Pecos plan is its power arrangement. Microsoft said the campus would initially operate with a co-located natural-gas generation facility behind the meter, allowing the site to receive dedicated electricity without drawing its opening load from the existing public grid. Chevron separately announced a 20-year power agreement with Microsoft for the West Texas facility. Microsoft said it would fund the new generation and supporting infrastructure, while the power plant and campus could eventually connect to the broader regional grid.

Microsoft also emphasized water conservation. The campus is planned around closed-loop cooling that requires an initial water charge but little additional water during steady-state operation, and the company said it would use non-potable water where possible. In an arid West Texas market, those design choices are not secondary sustainability features; they are fundamental to whether the development can maintain local support.

PowerPlay AI Adds 400 Megawatts to the Abilene Power-First Corridor

The concentration of behind-the-meter development in West Texas expanded again on July 20, when PowerPlay AI announced plans for an initial 400-megawatt AI data center development in the greater Abilene area. The project is being advanced through a joint venture with an unidentified Nasdaq-listed neocloud company and is targeting delivery of its first 400 megawatts of power in 2028.

PowerPlay AI said the joint venture has completed site-feasibility work, infrastructure assessments, land assembly and property acquisition. The partners are now progressing natural-gas service agreements and completing a request-for-proposals process to select an independent power producer. The planned generation would operate behind the meter, supplying electricity directly to the data center rather than depending initially on a conventional utility interconnection.

The company has not disclosed the joint venture partner, the project’s anticipated capital cost, the precise location of the site or whether the initial 400 megawatts represents utility capacity or fully deliverable critical IT load. The announcement should therefore be viewed as an early development milestone rather than a final construction commitment. Nevertheless, PowerPlay AI said the site already benefits from installed natural-gas infrastructure, nearby fiber, assembled land and a location outside an incorporated municipality where conventional municipal zoning restrictions would not apply.

PowerPlay AI’s model also represents another variation of the emerging power-secured development platform. The company is not presenting itself solely as a data center operator. Instead, it aims to transform undeveloped land into energized, construction-ready campuses that can be leased, sold or jointly developed with hyperscalers, neocloud providers and other large computing customers.

The Abilene project joins Microsoft’s Pecos campus in demonstrating how West Texas is becoming a testing ground for gas-powered, behind-the-meter AI infrastructure. The approach may accelerate delivery, but it will also bring greater scrutiny of emissions, fuel-price exposure and the long-term relationship between privately supplied generation and the regional electric grid.

Hut 8 Turns a Texas Campus Into a Contracted Infrastructure Asset

Three days before OpenAI’s Georgia announcement, Hut 8 reported that it had fully commercialized its 1-gigawatt Beacon Point AI data center campus in Nueces County, Texas. The company signed a second 15-year lease covering 352 megawatts of IT capacity, doubling the unnamed investment-grade tenant’s commitment to 704 megawatts. Hut 8 valued the new lease at $9.8 billion over its base term and placed total base-term contract value for the campus at $19.6 billion.

Beacon Point demonstrates how AI campuses are increasingly being underwritten before delivery. Hut 8 said its contracted AI portfolio now totals 949 megawatts of IT capacity supported by 1,330 megawatts of utility capacity, with aggregate base-term contract value of $26.6 billion.

The company expects the first Phase 2 data hall at Beacon Point to be delivered in the second quarter of 2028. That timetable reinforces another pattern in the latest announcements: customers are reserving capacity years before delivery. AI infrastructure demand is being translated into long-duration leases that allow developers to finance construction, electrical equipment and site work well ahead of occupancy.

Kansas City Emerges as a Multi-Gigawatt Market

Digital Realty’s June 22 acquisition of roughly 1,440 acres at Astra Enterprise Park in De Soto, Kansas, marked another major expansion beyond the traditional primary markets. Digital Realty acquired the site for approximately $475 million in cash and common units in its operating partnership and entered into a utility agreement that could provide 600 megawatts by early 2028, rising to 2 gigawatts at full delivery.

The first phase, Astra North, is expected to cover about 280 acres and accommodate nine data center buildings totaling approximately 3 million square feet. Digital Realty estimates that the initial phase could employ more than 1,000 workers at peak construction, while the completed campus could support approximately 250 full-time jobs. The broader site includes the former Sunflower Army Ammunition Plant property, an industrial tract already undergoing redevelopment.

Amazon Builds a New Missouri Cluster and Spends Another $3 Billion in Mississippi

On June 15, Amazon announced a $10 billion data center campus in Montgomery City, Missouri. State officials said the project would create approximately 400 direct jobs, thousands of construction jobs and hundreds of millions of dollars in property-tax revenue over 25 years. Amazon also committed more than $7 million to community programs and infrastructure.

The power arrangement was again a central part of the announcement. Amazon and Ameren Missouri said the company would pay 100% of the cost of providing electric service to the campus, including the infrastructure required to connect it to the grid, without incentives or discounted electric rates. Missouri’s large-load tariff framework is designed to prevent data center costs from being shifted to residential and commercial customers.

Amazon also plans to build water infrastructure and transfer the completed system to the local water district. Its related water-efficiency program with Arable Labs is expected to help farmers reduce groundwater withdrawals by 100 million gallons annually. These commitments reflect the new competitive landscape among states: winning a hyperscale campus increasingly requires not only incentives and available land, but credible rules governing utility cost allocation and resource use.

The Missouri project follows Amazon’s Nov. 20, 2025 commitment to invest at least $3 billion in a new Warren County, Mississippi, data center campus serving AI and cloud workloads. Amazon estimated that the project would create at least 200 direct data center jobs, support more than 300 additional full-time-equivalent positions in the region and sustain thousands of construction and supply-chain jobs across the state.

The Warren County campus builds on Amazon’s previously announced $10 billion investment in two Madison County data center campuses. Together, the projects are creating a substantial Mississippi footprint supported by state development programs, regional power infrastructure and a growing construction and operations workforce. Amazon described the Warren County project as the largest private investment in the county’s history and launched a $150,000 community fund supporting STEM education and other local priorities.

The Development Boom Meets Its Limits?

The past 45 days also supplied a warning about projects that fail to maintain political and legal support. On July 2, Blackstone-owned QTS terminated its portion of the Prince William Digital Gateway project in Virginia and withdrew related filings after years of litigation and local opposition. Compass Datacenters had already exited its portion in April. The court fight centered on the county’s rezoning process and public-notice requirements.

The Digital Gateway collapse matters because it occurred in Northern Virginia, the country’s most established data center region. It demonstrates that market demand, capital and proximity to fiber cannot overcome every entitlement failure. Developers now have to treat community consent, procedural compliance and environmental review as schedule-critical inputs alongside substations, transformers and generators.

That reality explains a focus of these announcements. OpenAI’s community compact, Amazon’s ratepayer protections, Microsoft’s behind-the-meter power strategy and the long-term leases signed by Hut 8 are all responses to the same question: what makes a giant project believable?

The gigawatt era has arrived, but the projects most likely to survive it will be those that can prove, from the beginning, exactly who will power them, who will pay for them and who will benefit when they are built.

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Nvidia will use Palantir to gain insight its supply chain

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Energy Secretary Keeps Northwest Coal Generating Plant Online

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S&P Global: Middle East crude flows to stay below prewar levels through 2027

Crude markets are settling into a prolonged period in which supply disruption is a standing condition rather than a series of discrete shocks, according to a new analysis from S&P Global Energy. For the first time since the US-Iran war began, the firm no longer expects Middle Eastern crude production to recover to prewar levels by yearend 2027. The outlook assumes no definitive end to the conflict, no normalization of traffic through the Strait of Hormuz, and no removal of Red Sea disruption risk from Iran’s Houthi allies over that period. Middle Eastern crude and condensate exports are now forecast to average roughly 10-16 million b/d on a monthly basis through 2027, compared with about 20 million b/d in January-February 2026, immediately before the war. Regional crude and condensate production is expected to average 21 million b/d over the same period, 4.2 million b/d below S&P Global’s previous projection. Production capacity has not been permanently lost, but security and logistical constraints are limiting how much oil can reach the market, S&P Global said. Gulf producers have strong incentives to find ways to move more oil to market and can be expected to adapt around political and security constraints where possible, said Jim Burkhard, vice-president and global head of crude oil research at S&P Global Energy. The market, however, “is not returning to calm,” Burkhard said. Instead, it is adjusting to conditions defined by unresolved conflict and persistent maritime risk, with oil flows remaining below prewar levels and an uneven path toward recovery. Price outlook S&P Global now expects crude oil prices broadly in an $80-100/bbl range through 2027. Dated Brent is expected to average around $90/bbl or higher for the balance of 2026 and $86/bbl in 2027, $5/bbl above the firm’s previous forecast. Brent recently traded above $100/bbl for the

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Oil extends rally on further Middle East disruptions

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Barclays conference: EOG prepares for steel inflation while Murphy weighs long-term portfolio options

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IEA sees oil demand decline deepening as Middle East disruptions persist

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EIA forecasts continued growth in US crude oil production through 2026

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DCF Poll: How Should Utilities Vet Real vs. ‘Ghost’ Data Center Demand?

Matt Vincent is Editor in Chief of Data Center Frontier, where he leads editorial strategy and coverage focused on the infrastructure powering cloud computing, artificial intelligence, and the digital economy. A veteran B2B technology journalist with more than two decades of experience, Vincent specializes in the intersection of data centers, power, cooling, and emerging AI-era infrastructure. Since assuming the EIC role in 2023, he has helped guide Data Center Frontier’s coverage of the industry’s transition into the gigawatt-scale AI era, with a focus on hyperscale development, behind-the-meter power strategies, liquid cooling architectures, and the evolving energy demands of high-density compute, while working closely with the Digital Infrastructure Group at Endeavor Business Media to expand the brand’s analytical and multimedia footprint. Vincent also hosts The Data Center Frontier Show podcast, where he interviews industry leaders across hyperscale, colocation, utilities, and the data center supply chain to examine the technologies and business models reshaping digital infrastructure. Since its inception he serves as Head of Content for the Data Center Frontier Trends Summit. Before becoming Editor in Chief, he served in multiple senior editorial roles across Endeavor Business Media’s digital infrastructure portfolio, with coverage spanning data centers and hyperscale infrastructure, structured cabling and networking, telecom and datacom, IP physical security, and wireless and Pro AV markets. He began his career in 2005 within PennWell’s Advanced Technology Division and later held senior editorial positions supporting brands such as Cabling Installation & Maintenance, Lightwave Online, Broadband Technology Report, and Smart Buildings Technology. Vincent is a frequent moderator, interviewer, and keynote speaker at industry events including the HPC Forum, where he delivers forward-looking analysis on how AI and high-performance computing are reshaping digital infrastructure. He graduated with honors from Indiana University Bloomington with a B.A. in English Literature and Creative Writing and lives in southern New Hampshire with

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Nvidia invests $3.5B in MediaTek to extend its grip on AI

AI infrastructure: MediaTek will work with Nvidia’s NVLink Fusion ecosystem to enable customers to develop custom AI infrastructure designed to integrate with Nvidia rack-scale systems and AI factories. Local AI computing: The companies will continue to collaborate on multiple generations of Nvidia RTX Spark and DGX Spark PC chips, powering consumer PCs, AI developer supercomputers, and enterprise-class workstations, that integrate Nvidia GPUs with MediaTek SoCs. Automotive: MediaTek and Nvidia will continue developing platforms for AI-powered, software-defined vehicles in the era of physical AI.  “MediaTek is one of the world’s great semiconductor companies, with exceptional expertise in system-on-chip design, connectivity, leading performance and power efficiency,” said Jensen Huang, founder and CEO of Nvidia, in a statement. “Together, we’re building platforms that bring Nvidia accelerated computing to new markets and give customers the freedom to create differentiated AI systems at enormous scale.” NVLink is a high-performance interface, but this move also helps lock in customers to the Nvidia platform, since NVLink Fusion is not about to hook up to AMD processors. For MediaTek, the Nvidia investment provides a big pile of cash and access to Nvidia’s infrastructure as it attempts to establish itself as a major supplier of custom data center silicon.

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AI Puts Fiber on the Critical Path

Fiber Becomes Part of the Build A decade ago, DC Blox might have prioritized land near existing fiber from AT&T, Verizon, Zayo or another established network provider. That calculation is different today. As data center campuses have grown and hyperscalers have become a larger share of the customer base, Wabik said connectivity has increasingly become another construction package associated with the project itself. “If Zayo or Verizon or AT&T just happens to be there close by, that’s a good thing,” he said. “But fiber construction is inherently anymore just part of the construction component.” That changes the site-selection question from Is there fiber nearby? to Can fiber be built here at the scale and diversity the customer requires? For DC Blox, Wabik said that can mean assessing whether sufficient public right-of-way exists to establish three or sometimes four diverse fiber paths into a data center. That distinction is important, as AI workloads push infrastructure into markets where power, land and energy options may be more abundant than established carrier density. The hyperscalers themselves have also become major network builders. Wabik characterized them provocatively as today’s telecom providers, pointing to the scale of terrestrial fiber they commission as well as the growing role of companies such as Amazon, Google and Meta in subsea cable development. The point is less that traditional carriers have disappeared than that hyperscalers increasingly design, commission and control enormous portions of the connectivity required to support their own infrastructure. DC Blox now sees requests for 864-count fiber as routine and, in some cases, 1,728-count cable. That would have been difficult to imagine during an earlier era when a handful of fibers from an established carrier could satisfy a data center’s connectivity requirements. AI-Scale Fiber Gets Physical The scale becomes clearer when the discussion moves from abstract network

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Power First: AI Data Centers Become Energy Systems

For decades, data centers consumed electricity much like other large commercial customers: power arrived from the utility, while batteries and diesel generators stood behind it to protect the load. AI is starting to break that model. As data center campuses grow toward hundreds of megawatts and, in some cases, gigawatt scale, developers are increasingly taking responsibility for an energy system that once sat largely outside the data center boundary. Natural gas supply, onsite generation, fuel cells, batteries, controls and the behavior of the compute load itself are increasingly becoming parts of the same infrastructure system. That was the central thread running through “Power First: The New Playbook for Delivering AI Data Centers,” an Aug. 4 session at the Data Center Frontier Trends Summit 2026 in Reston, Virginia. Moderated by Fengrong Li, Senior Managing Director at FTI Consulting, the panel brought together Jim Summers, CEO of GPC Infrastructure; Shankar Achanta, EVP and Chief Product and Technology Officer at FuelCell Energy; Judith Judson, Executive Vice President at Calibrant Energy; and Yuval Bachar, Founder and CEO of EdgeCloudLink. The discussion began with the immediate constraint — the grid cannot deliver capacity on the timetable AI developers increasingly require — but quickly moved beyond the familiar concept of “bridge power.” The larger question was what happens when the data center itself becomes an energy system. From Backup Power to Prime Power Behind-the-meter generation is not new. What has changed is its role and scale. “Traditionally, behind-the-meter generation has been for backup and the sizes were smaller,” Achanta said. “But what they’re seeing is the demand for the power is growing rapidly due to the data center load.” Interconnection queues, transmission limitations and equipment supply constraints are pushing onsite generation into what Achanta called the “front seat,” supplying primary power rather than waiting behind the

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NVIDIA Pushes DSX Deeper Into Data Center Infrastructure

The joint reference design appears in Trane’s Continuum Rubin DSX and Eaton’s Beam Rubin DSX platforms. The goal is a pre-coordinated architecture stretching from grid power to the chip rather than requiring developers and engineering teams to independently assemble electrical and mechanical systems for each project. The systems are also intended to exchange operating data. Rather than cooling and electrical systems responding independently, the systems can instead exchange leading indicators and respond more dynamically to changing operating requirements. This is an approach that closely mirrors NVIDIA’s larger DSX philosophy. Trane and Eaton are also designing the architecture to accommodate future liquid-cooling and direct-current power-distribution technologies. That future-proofing matters as rack power densities continue to rise. An electrical and cooling plant optimized for one GPU generation may otherwise become a constraint several hardware generations later. The Broader DSX Buildout The Lancium, Cloverleaf and Trane/Eaton agreements are part of a considerably wider expansion of the DSX ecosystem. Earlier deals show NVIDIA moving into many of the same infrastructure layers through partnerships spanning powered land, electrical design, digital twins and even project financing. In May, NVIDIA and IREN announced plans to support as much as 5 GW of DSX-aligned AI infrastructure across IREN’s global development pipeline, with the companies identifying IREN’s 2 GW Sweetwater campus in Texas as an expected flagship DSX deployment. NVIDIA also received a five-year right to purchase up to 30 million IREN shares at $70 each, representing a potential investment of as much as $2.1 billion. The infrastructure ecosystem has widened as well. Siemens, NVIDIA and Fluence, incorporating nVent design considerations, have developed a DSX Vera Rubin-aligned electrical, power and controls architecture extending from the utility connection to the rack. ABB is integrating digital models of medium-voltage switchgear, power-distribution equipment and UPS systems into the Omniverse DSX Blueprint, while Vertiv

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ERCOT Puts Texas AI Megawatts to the Test

Texas has no shortage of proposed data center megawatts. The harder question is how many of them are real. That distinction is becoming central to the Electric Reliability Council of Texas (ERCOT) as the state works through an unprecedented wave of AI, hyperscale and other large-load requests. In June, ERCOT said it was tracking more than 438 GW of proposed large loads, nearly 89% associated with data centers. By Aug. 3, Gov. Greg Abbott said ERCOT was considering approximately 474 GW of connection requests, roughly 90% from data centers and more than five times the system’s record peak demand. Neither figure represents a forecast of what will actually get built. And that is increasingly the point. ERCOT’s new Batch Zero process is beginning to put harder boundaries around Texas’ enormous development pipeline, asking which projects have enough maturity, technical information and commitment to warrant space in the transmission plan. At the same time, new requirements surrounding voltage ride-through and dynamic modeling are forcing another realization on the AI infrastructure industry: at hundreds of megawatts, a data center is no longer simply a customer at the edge of the grid. Its behavior can affect the grid itself. For developers, utilities and investors, Texas is becoming a large-scale test of what separates an announced AI campus from executable infrastructure. The Queue Is Not the Grid The sheer scale of ERCOT’s large-load queue can obscure how early many projects remain. ERCOT’s April 2026 monthly report offered a revealing snapshot. Large-load applications totaled 445.8 GW through 2033, but 321 GW had no studies submitted to ERCOT. Another 93.7 GW was under ERCOT review, while 22 GW had met the applicable Section 9.5 requirements. Against that enormous development funnel, ERCOT reported just 5.9 GW of observed energized large loads, with another 3.2 GW approved to

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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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