BP Solar Farm in Texas Starts Delivery for ExxonMobil Petrochemical Plant

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BP Solar Farm in Texas Starts Delivery for ExxonMobil Petrochemical Plant

BP PLC has put online a 187-megawatt (MW) solar facility in San Patricio County, Texas, which has been contracted to help power a local petrochemical complex owned by Exxon Mobil Corp. and Saudi Basic Industries Corp. The Peacock solar project serves Gulf Coast Growth Ventures, operated by Texas-based ExxonMobil. The petrochemical complex has an ethane […]

The Peacock solar project serves Gulf Coast Growth Ventures, operated by Texas-based ExxonMobil. The petrochemical complex has an ethane steam cracker with an ethylene production capacity of 1.8 million metric tons per annum (MMtpa). The ethylene feeds three derivative units: one monoethylene glycol unit with a 1.1 MMtpa capacity and two polyethylene units that can produce up to 1.3 MMtpa together, according to online information from ExxonMobil.

With an annual expected generation of 360,000 MW hours, the solar farm can cut the petrochemical complex’s greenhouse gas emissions by over 256,000 MMtpa, the equivalent of taking about 55,000 gasoline-powered cars off the road, according to Lightsource BP, the solar arm of BP.

“The Peacock Solar project adds to Lightsource bp’s operational fleet in Texas, helping reduce carbon emissions while diversifying the state’s energy mix to enhance security and reliability,” Helen Brauner, interim chief operating officer of Lightsource BP, said in an online statement.

Peacock is expected to generate $25 million in tax revenue over 25 years, Lightsource BP said. During construction it supported over 300 onsite jobs, according to the company.

“The project also supports U.S. manufacturers, with ultra-low carbon solar panels from Arizona-based First Solar and intelligent trackers from Connecticut-based GameChange Solar”, Lightsource BP added.

The Peacock site will grow vegetation including native species to support pollinators and other wildlife, as well as allow sheep grazing, it said.

“By layering on biodiversity and agrivoltaics initiatives, projects like Peacock offer a win-win for both the environment and local communities”, Brauner said.

Besides Peacock, Lightsource BP has three other solar projects in Texas that are in operation: the 260-MW Impact Solar in Lamar County, the 163-MW Elm Branch Solar in Ellis County and the 153-MW Briar Creek Solar in Navarro County.

It is building two more: the 163-MW Starr Solar in Starr County and the 125-MW Second Division Solar in Brazoria County.

Last year Lightsource BP secured an offtake agreement with fashion brand H&M Group for the Brazoria project.

Second Division Solar was expected to start operation by the end of last year, Lightsource BP said October 31, 2024, announcing the power purchase agreement. “From then on, the Second Division solar farm will deliver enough electricity to power an estimated 20,500 U.S. homes each year, while lowering carbon emissions — the equivalent of taking 33,300 fuel-burning cars off the road”, it said.

BP, which has set a goal to approve projects for 50 GW of net installed renewables capacity globally by 2030, fully took over Lightsource BP last year after acquiring the 50.03 percent stake it did not already own, from founders, management and staff.

Before completing the takeover, Lightsource BP transferred 2.4 GW of its operational and under-construction capacity in the United States to a new joint venture between BP and Lightsource BP’s founders and certain management and staff, according to BP.

Lightsource BP retains “its standalone operating model and independent brand, delivering renewable and affordable energy to businesses and communities across the world”, BP said October 24, 2024, announcing the completion of the takeover.

The brand’s model involves “selling majority interests in assets it has developed to strategic partners”, BP said.

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Noble Quarterly Revenue Falls

Noble Corp on Monday reported $798 million in revenue for the third quarter, down from $849 million for the prior three-month period as lower rig utilization offset lower contract drilling services costs. “Utilization of the 35 marketed rigs was 65 percent in the third quarter of 2025 compared to 73

Google Cloud targets enterprise AI builders with upgraded Vertex AI Training

Enterprises can quickly set up managed Slurm environments with automated resiliency and cost optimization through the Dynamic Workload Scheduler. The platform also includes hyperparameter tuning, data optimization, and built-in recipes with frameworks like NVIDIA NeMo to streamline model development. Enterprises weigh AI training gains Building and scaling generative AI models

Quantum Circuits brings dual-rail qubits to Nvidia’s CUDA-Q development platform

Nvidia announced AWS Braket support at the end of 2024. CUDA-Q is also available on Nvidia’s own Quantum Cloud platform, which combines GPUs and quantum processors with AI. The other major quantum computing platform is IBM’s Qiskit, which Quantum Circuits was already supporting. Qiskit also works with IBM, IonQ, Rigetti,

Japan’s semiconductor industry battles back

Sekiguchi Waichi, CEO, MM Research Institute, Inc.

Why Is the USA Natural Gas Price Dropping?

Why is the U.S. natural gas price dropping today? That was the question Rigzone asked Art Hogan, Chief Market Strategist at B. Riley Wealth, in an exclusive interview on Tuesday. In response, Hogan told Rigzone that, “technically, natural gas found some resistance up at the $3.57 per million British thermal units (MMBtu) level and is now testing support at $3.27 per MMBtu”. Hogan added that, fundamentally, three things seem to be in play. “Steady production, comfortable storage levels, and normalized weather predictions through November,” he told Rigzone. “Output has stayed near a three-week high of around 108 billion cubic feet per day (bcfpd) over the past few days, while record production earlier this year allowed energy firms to build inventories well above seasonal levels,” he added. “Weather forecasts show mostly normal temperature forecasts across the U.S. through mid-November,” Hogan went on to state. When he was asked why the U.S. natural gas price is dropping today in a separate exclusive interview on Tuesday, Phil Flynn, a senior market analyst at the PRICE Futures Group, told Rigzone that “natural gas is struggling as cold weather forecasts are easing and [because of] record Canadian natural gas supplies”. “We also have a bit of commodity risk-off as metals and oil plunge,” he added. “Still, record-breaking LNG exports should keep us from falling too hard,” Flynn went on to state. In an EBW Analytics Group report sent to Rigzone by the EBW team on Tuesday, Eli Rubin, an energy analyst at the company, warned that the November natural gas contract is “volatile” entering options expiration. “While the November natural gas contract surged 13.8 cents in a volatile session yesterday, December added 0.2 cents and January slipped 0.2 cents as the front-month disconnected from the rest of the curve,” Rubin said in the report. “Although

PG&E avoids ‘big bets’ as data center demand softens

$73 billion Capital investment plan, unchanged from Q2. PG&E Corp., which owns Pacific Gas & Electric Co., has adopted a “no big bets” philosophy to avoid issuing equity while the company stock price is low. 9.6 GW Datacenter pipeline, down 400 MW from June. But the number of projects entering final engineering has increased slightly. $1.1 billion Core earnings, up 44% from Q3 2024, partly driven by reduced operations and maintenance expenses. 9% Annual core EPS growth guidance for 2027-2030. Steady course Figures on early-stage data center projects remain “very fluid” and the company has seen “modest attrition” since June, PG&E Corp. CEO Patti Poppe said during a third-quarter earnings call Thursday. But of the 9.6 GW in the company’s data center queue, 18 projects totaling 1.6 GW have entered final engineering — up from 1.5 GW at the end of the second quarter, according to PG&E. The company expects 95% of projects that reach final engineering to enter service by 2030; several may begin service as early as 2026. PG&E holds that it can cut customer bills by 1% to 2% per gigawatt of new load by using revenue from new large load customers to offset its five-year, $73 billion capital investment plan. But CFO Carolyn Burke said it was unlikely that PG&E would expand its capital plan to try to attract additional large load customers given the company’s low stock valuation. Instead, she said, the company would stick to a “no big bets plan” and focus on upgrading existing assets and investing in safety and reliability while working to improve PG&E’s credit rating. Burke said the company’s financial metrics meet the credit rating agencies’ criteria for investment-grade ratings, but that the agencies are watching regulatory developments in California for signs that it is time to upgrade the utility. Wildfire

North America Adds Rigs For 3 Straight Weeks

North America added three rigs week on week, according to Baker Hughes’ latest North America rotary rig count, which was published on October 24. The total U.S. rig count increased by two week on week and the total Canada rig count rose by one during the same period, taking the total North America rig count up to 749, comprising 550 rigs from the U.S. and 199 rigs from Canada, the count outlined. Of the total U.S. rig count of 550, 527 rigs are categorized as land rigs, 21 are categorized as offshore rigs, and two are categorized as inland water rigs. The total U.S. rig count is made up of 420 oil rigs, 121 gas rigs, and nine miscellaneous rigs, according to Baker Hughes’ count, which revealed that the U.S. total comprises 485 horizontal rigs, 53 directional rigs, and 12 vertical rigs. Week on week, the U.S. offshore rig count rose by four, and its land and inland water rig counts each dropped by one, Baker Hughes highlighted. The U.S. oil rig count rose by two week on week, and its gas and miscellaneous rig counts remained unchanged during the period, the count showed. The U.S. directional rig count rose by two week on week, while its vertical rig count increased by one and its horizontal rig count dropped by one, the count revealed. A major state variances subcategory included in the rig count showed that, week on week, Louisiana added three rigs, Wyoming added two rigs, and Colorado and Texas each dropped one rig. A major state variances subcategory included in the rig count showed that, week on week, the Eagle Ford and Permian basins each dropped one rig. Canada’s total rig count of 199 is made up of 138 oil rigs and 61 gas rigs, Baker Hughes pointed

Lukoil to Sell Foreign Assets amid Sanctions

(Update) October 28, 2025, 10:00 AM GMT+1: Article updated with details throughout. Lukoil PJSC, Russia’s second-largest oil producer, announced plans to sell international assets after being hit by US sanctions last week. The company is has started considering bids from potential buyers, according to a statement posted on its website late on Monday. The divestment process is being conducted under a wind-down license from the US Treasury’s Office of Foreign Assets Control, which Lukoil said it could ask to be extended “to ensure uninterrupted operations of its international assets.” Last week, President Donald Trump’s administration slapped sanctions on Russia’s two biggest oil producers – Lukoil and state-controlled Rosneft PJSC – to pressure the Kremlin to end the war in Ukraine. The oil and gas industry is a key source of tax revenues for the nation’s budget, and two producers account for just under a half of the country’s crude exports. The goal of the White House is to make Russia’s oil trade harder, costlier and riskier, rather than stopping the flows altogether in a way that could spike global crude prices. The UK also blacklisted the two companies earlier this month. Lukoil is the most internationally diverse of Russia’s oil giants, with upstream businesses in former Soviet countries such as Kazakstan, Uzbekistan and Azerbaijan, as well as in Egypt, the United Arab Emirates and West African nations of Ghana, Nigeria, Cameroon and Congo. In all these projects, the Russian producer holds minority stakes, and their share in Lukoil’s total crude production last year was only 5 percent, according to the company’s annual report. International assets jointly account for around a quarter of Lukoil’s current capitalization, according to estimates from Kirill Bakhtin, senior analyst at Moscow-based BCS. One notable exception is Iraq, where Lukoil holds 75 percent of the giant West Qurna 2 oil

QatarEnergy Joins North Rafah Exploration Block in Egypt

QatarEnergy said Monday it had completed the purchase of a 40 percent stake in the North Rafah exploration block offshore Egypt from Eni SpA. The Italian state-backed energy major retains 60 percent as operator, state-owned QatarEnergy said in a press release. North Rafah spans nearly 3,000 square kilometers (1,158.31 square miles) in the Mediterranean Sea off the northeastern coast of Egypt, QatarEnergy noted. The block has a water depth of up to 450 meters (1,476.38 feet), it said. The acquisition “strengthens our presence in Egypt and marks another important step in advancing our ambitious international exploration strategy”, said QatarEnergy president and chief executive Saad Sherida Al-Kaabi, who is also Qatar’s energy minister. Earlier this month QatarEnergy said it has entered into an agreement to buy a 27 percent ownership in the North Cleopatra exploration block on Egypt’s side of the Mediterranean Sea from operator Shell PLC. Shell will retain 36 percent. The other partners are Chevron Corp with a 27 percent interest and Egypt’s state-owned Tharwa Petroleum Co with 10 percent, according to a QatarEnergy statement October 5. North Cleopatra spans 3,400 square kilometers with waters up to 2,600 meters (8,530.18 feet) deep, QatarEnergy noted. The license area is in the frontier Herodotus basin and adjacent to the northern portion of the North El-Dabaa block, where QatarEnergy holds 23 percent, QatarEnergy said. QatarEnergy obtained its North El-Dabaa stake from United States oil and gas heavyweight Chevron, in an agreement announced November 11, 2024. North El-Dabaa lies about 10 kilometers off Egypt’s Mediterranean shore. The block has a water depth of 100-3,000 meters, according to QatarEnergy. On May 12, 2024, QatarEnergy announced a deal to acquire 40 percent each in the Cairo and Masry exploration blocks offshore Egypt from sole owner Exxon Mobil Corp. The blocks cover around 11,400 square kilometers

Baker Hughes Wins New Aramco Drilling Services Contract

Baker Hughes Co has signed an agreement with Saudi Arabian Oil Co (Aramco) expanding its integrated underbalanced coiled tubing drilling (UBCTD) operations across Saudi Arabia’s natural gas fields. “Under the multi-year agreement, Baker Hughes will expand its current UBCTD fleet from four to 10 units for re-entry and greenfield drilling projects across fields in the kingdom”, the Houston, Texas-based company said in a press release. “The company will provide integrated solutions to manage all aspects of the UBCTD operations, including coiled tubing drilling units, underbalanced drilling services, operational management, well construction and geosciences to scale and accelerate their access to gas from new and established fields”. Work under the expanded contract is scheduled to start next year. “Baker Hughes’ integrated approach to UBCTD includes the industry-leading CoilTrak™ bottomhole assembly system and enhanced reservoir analysis driven by GaffneyCline™ energy advisory”, Baker Hughes said. “This unique pairing of technology and insight allows operators to more effectively navigate the subsurface environment during horizontal drilling and re-entry operations. “By combining these solutions with holistic project management services, Baker Hughes will enhance production efficiency, speed and safety while mitigating reservoir damage when compared to traditional development methods”. Amerino Gatti, Baker Hughes executive vice president for oilfield services and equipment, said, “This project is the result of nearly two decades of successful collaboration between Baker Hughes and Aramco, which have set the standard for UBCTD. By combining advanced technologies with a holistic, integrated approach, we can support Aramco to more efficiently access bypassed and hard-to-reach hydrocarbons and produce the resources that help the kingdom thrive”. “This expansion sets the stage for further innovation in UBCTD, which has the potential to shape how oil and gas are produced around the world”, Gatti added. Baker Hughes entered the Saudi UBCTD market in 2008, according to the company. In a separate contract, Baker Hughes said Monday it has been tapped

Qualcomm goes all-in on inferencing with purpose-built cards and racks

From a strategy perspective, there is a longer term enterprise play here, noted Moor’s Kimball; Humain is Qualcomm’s first customer, and a cloud service provider (CSP) or hyperscaler will likely be customer number two. However, at some point, these rack-scale systems will find their way into the enterprise. “If I were the AI200 product marketing lead, I would be thinking about how I demonstrate this as a viable platform for those enterprise workloads that will be getting ‘agentified’ over the next several years,” said Kimball. It seems a natural step, as Qualcomm saw success with its AI100 accelerator, a strong inference chip, he noted. Right now, Nvidia and AMD dominate the training market, with CUDA and ROCm enjoying a “stickiness” with customers. “If I am a semiconductor giant like Qualcomm that is so good at understanding the performance-power balance, this inference market makes perfect sense to really lean in on,” said Kimball. He also pointed to the company’s plans to re-enter the datacenter CPU space with its Oryon CPU, which is featured in Snapdragon and loosely based on technology it acquired with its $1.4 billion Nuvia acquisition. Ultimately, Qualcomm’s move demonstrates how wide open the inference market is, said Kimball. The company, he noted, has been very good at choosing target markets and has seen success when entering those markets. “That the company would decide to go more ‘in’ on the inference market makes sense,” said Kimball. He added that, from an ROI perspective, inferencing will “dwarf” training in terms of volume and dollars.

AI data center building boom risks fueling future debt bust, bank warns

However, that’s only one part of the problem. Meeting the power demands of AI data centers will require the energy sector to make large investments. Then there’s data center demand for microprocessors, rare earth elements, and other valuable metals such as copper, which could, in a bust, make data centers the most expensively-assembled unwanted assets in history. “Financial stability consequences of an AI-related asset price fall could arise through multiple channels. If forecasted debt-financed AI infrastructure growth materializes, the potential financial stability consequences of such an event are likely to grow,” warned the BoE blog post. “For companies who depend on the continued demand for massive computational capacity to train and run inference on AI models, an algorithmic breakthrough or other event which challenges that paradigm could cause a significant re-evaluation of asset prices,” it continued. According to Matt Hasan, CEO of AI consultancy aiRESULTS, the underlying problem is the speed with which AI has emerged. “What we’re witnessing isn’t just an incremental expansion, it’s a rush to construct power-hungry, mega-scale data centers,” he told Network World. The dot.com reversal might be the wrong comparison; it dented the NASDAQ and hurt tech investment, but the damage to organizations investing in e-commerce was relatively limited. AI, by contrast, might have wider effects for large enterprises because so many have pinned their business prospects on its potential. “Your reliance on these large providers means you are indirectly exposed to the stability of their debt. If a correction occurs, the fallout can impact the services you rely on,” said Hasan.

Intel sees supply shortage, will prioritize data center technology

“Capacity constraints, especially on Intel 10 and Intel 7 [Intel’s semiconductor manufacturing process], limited our ability to fully meet demand in Q3 for both data center and client products,” said Zinsner, adding that Intel isn’t about to add capacity to Intel 10 and 7 when it has moved beyond those nodes. “Given the current tight capacity environment, which we expect to persist into 2026, we are working closely with customers to maximize our available output, including adjusting pricing and mix to shift demand towards products where we have supply and they have demand,” said Zinsner. For that reason, Zinzner projects that the fourth quarter will be roughly flat versus the third quarter in terms of revenue. “We expect Intel products up modestly sequentially but below customer demand as we continue to navigate supply environment,” said Zinsner. “We expect CCG to be down modestly and PC AI to be up strongly sequentially as we prioritize wafer capacity for server shipments over entry-level client parts.”

How to set up an AI data center in 90 days

“Personally, I think that a brownfield is very creative way to deal with what I think is the biggest problem that we’ve got right now, which is time and speed to market,” he said. “On a brownfield, I can go into a building that’s already got power coming into the building. Sometimes they’ve already got chiller plants, like what we’ve got with the building I’m in right now.” Patmos certainly made the most of the liquid facilities in the old printing press building. The facility is built to handle anywhere from 50 to over 140 kilowatts per cabinet, a leap far beyond the 1–2 kW densities typical of legacy data centers. The chips used in the servers are Nvidia’s Grace Blackwell processors, which run extraordinarily hot. To manage this heat load, Patmos employs a multi-loop liquid cooling system. The design separates water sources into distinct, closed loops, each serving a specific function and ensuring that municipal water never directly contacts sensitive IT equipment. “We have five different, completely separated water loops in this building,” said Morgan. “The cooling tower uses city water for evaporation, but that water never mixes with the closed loops serving the data hall. Everything is designed to maximize efficiency and protect the hardware.” The building taps into Kansas City’s district chilled water supply, which is sourced from a nearby utility plant. This provides the primary cooling resource for the facility. Inside the data center, a dedicated loop circulates a specialized glycol-based fluid, filtered to extremely low micron levels and formulated to be electronically safe. Heat exchangers transfer heat from the data hall fluid to the district chilled water, keeping the two fluids separate and preventing corrosion or contamination. Liquid-to-chip and rear-door heat exchangers are used for immediate heat removal.

INNIO and VoltaGrid: Landmark 2.3 GW Modular Power Deal Signals New Phase for AI Data Centers

Why This Project Marks a Landmark Shift The deployment of 2.3 GW of modular generation represents utility-scale capacity, but what makes it distinct is the delivery model. Instead of a centralized plant, the project uses modular gas-reciprocating “power packs” that can be phased in step with data-hall readiness. This approach allows staged energization and limits the bottlenecks that often stall AI campuses as they outgrow grid timelines or wait in interconnection queues. AI training loads fluctuate sharply, placing exceptional stress on grid stability and voltage quality. The INNIO/VoltaGrid platform was engineered specifically for these GPU-driven dynamics, emphasizing high transient performance (rapid load acceptance) and grid-grade power quality, all without dependence on batteries. Each power pack is also designed for maximum permitting efficiency and sustainability. Compared with diesel generation, modern gas-reciprocating systems materially reduce both criteria pollutants and CO₂ emissions. VoltaGrid markets the configuration as near-zero criteria air emissions and hydrogen-ready, extending allowable runtimes under air permits and making “prime-as-a-service” viable even in constrained or non-attainment markets. 2025: Momentum for Modular Prime Power INNIO has spent 2025 positioning its Jenbacher platform as a next-generation power solution for data centers: combining fast start, high transient performance, and lower emissions compared with diesel. While the 3 MW J620 fast-start lineage dates back to 2019, this year the company sharpened its data center narrative and booked grid stability and peaking projects in markets where rapid data center growth is stressing local grids. This momentum was exemplified by an 80 MW deployment in Indonesia announced earlier in October. The same year saw surging AI-driven demand and INNIO’s growing push into North American data-center markets. Specifications for the 2.3 GW VoltaGrid package highlight the platform’s heat tolerance, efficiency, and transient response, all key attributes for powering modern AI campuses. VoltaGrid’s 2025 Milestones VoltaGrid’s announcements across 2025 reflect

Inside Google’s multi-architecture revolution: Axion Arm joins x86 in production clusters

Matt Kimball, VP and principal analyst with Moor Insights and Strategy, pointed out that AWS and Microsoft have already moved many workloads from x86 to internally designed Arm-based servers. He noted that, when Arm first hit the hyperscale datacenter market, the architecture was used to support more lightweight, cloud-native workloads with an interpretive layer where architectural affinity was “non-existent.” But now there’s much more focus on architecture, and compatibility issues “largely go away” as Arm servers support more and more workloads. “In parallel, we’ve seen CSPs expand their designs to support both scale out (cloud-native) and traditional scale up workloads effectively,” said Kimball. Simply put, CSPs are looking to monetize chip investments, and this migration signals that Google has found its performance-per-dollar (and likely performance-per-watt) better on Axion than x86. Google will likely continue to expand its Arm footprint as it evolves its Axion chip; as a reference point, Kimball pointed to AWS Graviton, which didn’t really support “scale up” performance until its v3 or v4 chip. Arm is coming to enterprise data centers too When looking at architectures, enterprise CIOs should ask themselves questions such as what instance do they use for cloud workloads, and what servers do they deploy in their data center, Kimball noted. “I think there is a lot less concern about putting my workloads on an Arm-based instance on Google Cloud, a little more hesitance to deploy those Arm servers in my datacenter,” he said. But ultimately, he said, “Arm is coming to the enterprise datacenter as a compute platform, and Nvidia will help usher this in.” Info-Tech’s Jain agreed that Nvidia is the “biggest cheerleader” for Arm-based architecture, and Arm is increasingly moving from niche and mobile use to general-purpose and AI workload execution.

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.

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

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

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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