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MARAD approves Energy Transfer’s $1-billion Blue Marlin crude oil export port

The US Maritime Administration (MARAD) approved Energy Transfer’s $1-billion Blue Marlin offshore crude oil export project off Louisiana Nov. 5, marking the fourth oil and gas deepwater port approval under President Donald Trump’s second administration. The proposed Blue Marlin port would have capacity to export up to 2 million b/d of crude oil, with loading […]

The US Maritime Administration (MARAD) approved Energy Transfer’s $1-billion Blue Marlin offshore crude oil export project off Louisiana Nov. 5, marking the fourth oil and gas deepwater port approval under President Donald Trump’s second administration.

The proposed Blue Marlin port would have capacity to export up to 2 million b/d of crude oil, with loading rates of up to 80,000 bbl/hr, including onto very large crude carriers (VLCCs). Located 99 miles off Cameron Parish, La., the project includes conversion of an existing 36-in. Stingray natural gas pipeline to transport crude oil from Energy Transfer’s Nederland terminal in Texas to the offshore infrastructure.

The US Federal Energy Regulatory Commission previously authorized abandonment and sale of Stingray pipeline infrastructure for conversion to crude oil service. Energy Transfer has yet to receive final US Environmental Protection Agency air permits and certain state approvals.

The project’s commercial development schedule remains uncertain.

MARAD approved Blue Marlin shortly after its Oct. 28 approval of the $8.2-billion ST LNG project offshore Texas, as the agency pursues new procedures to streamline deepwater port licensing. The Trump administration also has approved Delfin LNG, a floating LNG export project offshore Louisiana, and Texas GulfLink, a crude oil export project offshore Texas.

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What’s next for Nvidia?

That’s if he wants it. One industry watcher told this reporter that several years ago, he asked several Nvidia vice presidents if they wanted the big chair, because Nvidia had no clear successor to Huang and to a man they said no way. “I can’t and don’t want to do

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AMD takes on Intel and Nvidia with new 256-core EPYC server CPUs

AMD EPYC, Intel Xeon, and Nvidia Vera represent three different approaches to the evolving data-centre CPU market, added Rawat. “AMD competes through high core density, memory capabilities and power efficiency, while Intel leverages its established enterprise ecosystem, platform compatibility and customer relationships. Nvidia is taking a different approach with Vera,

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ExxonMobil takes FID for Longtail development offshore Guyana

The development, in the southeastern portion of the block, will target non-associated gas and condensate-rich reservoirs. Subject to future investment decisions, market demand, and development of supporting infrastructure, gas from the project could be transported to shore by pipeline. The development will use a floating production, storage, and offloading (FPSO) vessel designed to process 1.2 bcfd of gas and produce as much as 250,000 b/d of condensate. The project is expected to include about 45 subsea production and injection wells. “By developing these gas and condensate resources, we’re unlocking new value for Guyana while delivering advantaged energy to meet growing global demand,” said Dan Ammann, president, ExxonMobil Upstream Company. ExxonMobil currently produces about 900,000 b/d of oil from four developments in the Stabroek block. Its fifth project, Uaru, is expected to start up in fourth-quarter 2026, increasing total block production capacity to more than 1 million b/d. Earlier this year, the operator and co-venturers produced the 1 billionth bbl of oil from Guyana’s Stabroek block, less than 7 years after first production began in December 2019 with Liza field. Construction also continues on the Whiptail and Hammerhead developments, the sixth and seventh approved projects on the block. Whiptail is slated to start production in 2027, followed by Hammerhead in 2029. ExxonMobil Guyana Ltd. operates the Stabroek block with a 45% interest. Hess Guyana Exploration Ltd. holds 30%, and CNOOC Petroleum Guyana Ltd. holds 25%.

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MARAD approves Energy Transfer’s $1-billion Blue Marlin crude oil export port

The US Maritime Administration (MARAD) approved Energy Transfer’s $1-billion Blue Marlin offshore crude oil export project off Louisiana Nov. 5, marking the fourth oil and gas deepwater port approval under President Donald Trump’s second administration. The proposed Blue Marlin port would have capacity to export up to 2 million b/d of crude oil, with loading rates of up to 80,000 bbl/hr, including onto very large crude carriers (VLCCs). Located 99 miles off Cameron Parish, La., the project includes conversion of an existing 36-in. Stingray natural gas pipeline to transport crude oil from Energy Transfer’s Nederland terminal in Texas to the offshore infrastructure. The US Federal Energy Regulatory Commission previously authorized abandonment and sale of Stingray pipeline infrastructure for conversion to crude oil service. Energy Transfer has yet to receive final US Environmental Protection Agency air permits and certain state approvals. The project’s commercial development schedule remains uncertain. MARAD approved Blue Marlin shortly after its Oct. 28 approval of the $8.2-billion ST LNG project offshore Texas, as the agency pursues new procedures to streamline deepwater port licensing. The Trump administration also has approved Delfin LNG, a floating LNG export project offshore Louisiana, and Texas GulfLink, a crude oil export project offshore Texas.

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IEA sees oil market surplus returning as Gulf exports recover

The global oil market is showing signs of rebalancing as recovering crude exports from the Middle East lift supply, although persistent disruptions to refined product markets, particularly diesel, continue to weigh on consumers, the International Energy Agency (IEA) said. In its Nov. 13 Oil Market Report, IEA said global oil supply increased 2.3 million b/d month-on-month to 105.4 million b/d in October, following a 3 million-b/d increase in September. Output has risen 5.3 million b/d since August as Gulf exports recovered despite continued attacks on energy infrastructure and commercial tankers. The stronger supply outlook has prompted the agency to raise its fourth-quarter 2026 supply estimate by 3.3 million b/d. Global supply is now expected to decline by an average 4.8 million b/d for the full year before rebounding by 6.6 million b/d in 2027 to average 108.1 million b/d. The recovery in exports has eased market tightness and pushed crude prices lower. North Sea Dated crude fell 32% from an early-October high of $136/bbl to about $93/bbl at the time of the report, although prices remained $22/bbl above prewar levels. Gulf oil exports, excluding Oman, reached 18.4 million b/d in October, about 26% below prewar levels. Crude exports accounted for most of the recovery, reaching 15 million b/d, equivalent to 82% of prewar volumes. However, IEA cautioned that continued attacks on shipping remain a significant downside risk to the supply outlook. Demand under pressure Global oil demand is forecast to decline by 2.7 million b/d in 2026 to 102.3 million b/d, reflecting disruptions to refined product and liquefied petroleum gas exports from the Gulf, elevated fuel prices, and weaker consumption across major markets. The contraction is expected to moderate in fourth-quarter 2026 to 2.7 million b/d year-on-year, compared with an average decline of 4.4 million b/d in the second and

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What’s next for California’s climate laws following an appeals court split decision

The Ninth Circuit Court of Appeals issued a split decision on California’s climate disclosure laws, Senate Bill 253 and Senate Bill 261, on Monday, allowing some emissions reporting requirements to proceed, while blocking others on the basis of them being considered in part or completely unconstitutional under the First Amendment. In the decision, the federal appellate panel partially upheld and partially overturned a district court’s decision from August 2025, which declined to enjoin the laws. The U.S. Chamber of Commerce and other business associations filed the lawsuit, requesting to temporarily block implementation of both climate laws while their constitutionality was under review. Implementation of SB 261 was already temporarily halted pending review by the Ninth Circuit last November.  SB 253, or the Climate Corporate Data Accountability Act, requires companies with more than $1 billion in revenue to report scope 1 and scope 2 emissions, with eventual scope 3 disclosures. SB 261, or the Climate-Related Financial Risk Act, requires companies with more than $500 million in revenue to publicly disclose their climate-related financial risks and countermeasures. Both climate disclosure regulations were signed into law in October 2023 by California Gov. Gavin Newsom and have since faced a spate of legal challenges. The ruling came a day before the inaugural emissions disclosure deadline for SB 253. Breaking down the split decision The Nov. 9 decision allowed for the reporting of a company’s direct emissions to proceed under SB 253’s scope 1 and scope 2 disclosure requirements, affirming the lower court’s decision. The court ruled such disclosures “regulate commercial speech,” which the appellate panel defined as factual and objective information on a company’s own operations. However, the appeals court reversed the lower court’s ruling when it came to SB 253’s scope 3 disclosure requirements, which ask companies to report the indirect emissions generated

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Repsol to add renewable hydrogen at Tarragona refining complex

Repsol SA’s board has approved a project to install a 150-Mw renewable hydrogen electrolyzer for production of renewable hydrogen at the operator’s 190,000-b/d Tarragona integrated refining and petrochemicals industrial complex along northeastern Spain’s Costa Daurada of the Mediterranean Sea. To be developed with partner Enagás Renovable SA (25%), the green hydrogen project will require an investment of about €400 million and enable production of more than 22,000 tonnes/year (tpy) of renewable hydrogen, Respol said in a release Nov. 12. Repsol, which will operate and hold a 75% stake in the new plant, confirmed hydrogen produced by the project would be used to support Tarragona’s refining and production processes, as well as for production of chemical products. A portion of the hydrogen additionally would serve as feedstock for production of renewable methanol at the operator’s co-located Ecoplanta operations that, by 2029, will process up to 400,000 tpy municipal solid waste into 240,000 tpy renewable fuels and other circular products. The electrolyzer also could supply renewable hydrogen to the local natural gas network and Spain’s planned Hydrogen Backbone network in the future, Repsol said. Once operable, the company estimates the renewable hydrogen plant would enable the Tarragona site to avoid up to 250,000 tpy of carbon dioxide (CO2) emissions. The project has already been selected to receive up to €104 million under Spain’s regional Hydrogen Valley initiative—a public-private effort to develop a local hydrogen ecosystem—promoted by the Ministry for the Ecological Transition and the Demographic Challenge and funded through Spain’s Recovery, Transformation, and Resilience Plan with NextGenerationEU funds. Now in the engineering phase, Repsol said the plant’s electrolyzer will use recovered industrial water as well as incorporate technology designed to maximize energy efficiency of the production process as part of the operator’s broader ongoing strategy to further reduce environmental impacts of its global

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EIA: US crude oil inventories up 4.7 million bbl

US crude oil inventories for the week ended Nov. 6, excluding the Strategic Petroleum Reserve, increased by 4.7 million bbl from the previous week, according to data from the US Energy Information Administration (EIA). The report was released a day later than usual due to the due to the closure of the Federal government on Wednesday, Nov. 11. At 414.4 million bbl, US crude oil inventories are 4% below the 5-year average for this time of year, the EIA report indicated. Gasoline inventories increased 1.8 million bbl, 1% above the 5-year average. Propane-propylene inventories increased 100,000 bbl, 12% above the 5-year average. Total commercial petroleum inventories increased by 11.4 million bbl for the week. Distillate inventories increased 4.1 million bbl, 8% below the 5-year average. US crude oil refinery inputs averaged 17.0 million b/d for the week ended Nov. 6, which was 322,000 b/d more than the previous week’s average. Refineries operated at 95.2% of capacity. Gasoline output averaged 9.6 million b/d, and distillate production decreased to 5.1 million b/d. Crude oil imports increased 325,000 b/d to 6.7 million b/d. The 4-week average of 6.3 million b/d is 14% above the year-ago level. Gasoline imports averaged 202,000 b/d; distillate imports averaged 99,000 b/d. Over the past four weeks, total product supplied averaged 20.8 million b/d, up 0.9% year over year. The 4-week average for gasoline product supplied decreased 1.0% year over year to 8.7 million b/d, while the 4-week average for distillate product supplied increased 4.2% to 3.9 million b/d. The 4-week average for jet fuel product supplied increased 1.8% year over year.

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How TI’s ADC34DSO75 Catches the Nanosecond Power Glitches Behind AI Data Center Downtime

Today’s advanced AI data center can be viewed as a vast, complex and interdependent digital organism in which a virtually infinite number of components must be tracked all the time, in real time. It’s a monitoring job of staggering proportions. At stake is the operation of highly critical workloads and the maintenance of return on investment for high-cost compute equipment. At risk is sub-optimal performance or, in worst-case scenarios, the nightmare of data center downtime. Sponsored Resources: Why traditional telemetry misses nanosecond power-rail events Telemetry has long been relied upon to monitor data center servers, test and measurement equipment, wireless infrastructure and other systems for real-time information about voltage, current, power, temperature and overall system health. But most systems operate at millisecond-level intervals or slower, which is six orders of magnitude longer than the transient events that now occur at the processor power rails and the tools meant to observe them. The requirements and high stakes of today’s AI data centers and workloads have called for a new generation of advanced, nanosecond-level telemetry gear. Texas Instruments has established a leadership position in this sector. The company has developed the first analog-to-digital converter (ADC) to enable 24/7, low-power, event-based remote monitoring at nanosecond resolution. Let’s unpack this statement and examine why TI’s new monitoring technology is so important for the data center industry. What is the TI ADC34DSO75?    We’re talking specifically about TI’s ADC34DSO75, the industry’s highest-performance, 3 gigasamples per second (GSPS) ADC, delivering thousands of times faster performance than current offerings. Launched at the Open Compute Project Global Summit conference in October, the ADC34DSO75 addresses the shortcomings of existing monitoring solutions that can’t detect the nanosecond-level power-rail glitches that cause costly data center downtime. The ADC34DSO75 combines ultra-high-speed sampling with advanced on-chip digital signal processing in a small form factor,

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SC26 Preview: AI-HPC Convergence Takes Center Stage in Chicago

As the high-performance computing community prepares to gather in Chicago for SC26, November 15–20, the latest episode of the Data Center Frontier Show offers a timely preview of the technologies, market developments, and infrastructure challenges expected to shape this year’s conference. Hosted by DCF Contributing Editor Doug Black, the conversation brings together Lois McKinnis, Argonne Distinguished Fellow and senior computational scientist at Argonne National Laboratory; Addison Snell, founder and CEO of Intersect 360 Research; and Earl Joseph, CEO of Hyperion Research. The episode also inaugurates Data Center Frontier’s new Frontier Computing channel, expanding DCF’s coverage of the technologies and infrastructure driving the convergence of high-performance computing, AI, QC and next-generation scientific discovery. The central theme is unmistakable. AI is no longer simply an adjunct to traditional supercomputing. It is changing how scientific computing itself is performed. “We’re really moving beyond focusing just on bigger machines, faster machines,” McKinnis observes, pointing to the growing integration of AI into scientific software development, simulations, and research workflows. Joseph underscores the acceleration, citing new Hyperion research finding that 70% of respondents are already using AI for code generation. The panel also examines the U.S. Department of Energy’s Genesis Mission, a sweeping effort to link supercomputers, large-scale AI infrastructure, and cloud resources in support of scientific discovery. Joseph calls Genesis “the first time I’ve ever seen something that’s truly a broad national resource,” while Snell emphasizes that investments in AI infrastructure must be matched by investments in science itself. For data center professionals, the discussion turns to increasingly consequential questions about the economics and sustainability of the AI buildout. Snell warns that the industry’s focus on rapid construction has outpaced serious discussion of infrastructure lifecycles and upgrades. Joseph highlights the mounting difficulty of financing supercomputers costing $100 million or more when new GPU generations arrive

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Nvidia’s leadership crisis puts enterprise AI’s dependence on one company under scrutiny

“More broadly, it throws into doubt the company’s leadership and security practices, and ignites questions around board-level governance and oversight,” he said. The ‘default choice’ in the market Huang founded Nvidia in 1993, initially targeting the gaming market. But the company pivoted in recent years to meet the intensive compute demands of AI. Its advanced GPUs not only excel at rendering graphics, but can handle an enormous number of simultaneous computations, making them a natural fit for neural networks and LLMs. The company began focusing more on developing chips and architecture for AI tools and data centers, and has continued to ink new deals and establish partnerships with tech companies serving nearly every level of the stack, including Anthropic, Meta, Dell, HPE, Microsoft, AWS, Google Cloud, Accenture, Marvell Technology, Hugging Face and many others.

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Jensen Huang Resigns as NVIDIA CEO, Sending Shockwaves Through AI Data Center Industry

NVIDIA co-founder Jensen Huang resigned Thursday morning (November 12) as president, CEO and board member of the world’s dominant AI chipmaker, a stunning leadership change that introduces new uncertainty into the global artificial intelligence infrastructure boom. In an official announcement, NVIDIA confirmed that Chief Financial Officer Colette Kress will serve as interim CEO while the board conducts a search for Huang’s permanent successor. The company also appointed longtime director Harvey C. Jones as its first board chairman. The departure ends Huang’s 33-year leadership of the company he co-founded in 1993 and comes amid a rapidly escalating controversy involving his reported personal relationships, potential Chinese intelligence activity and questions about corporate governance. According to Reuters, NVIDIA shares fell more than 10% in premarket trading Thursday as investors weighed the implications for the approximately $4 trillion company and the wider AI technology sector. The company’s announcement did not specify a reason for Huang’s resignation. National Security Investigation Precedes Leadership Change The leadership shakeup follows several days of increasing scrutiny over Huang’s reported relationship with a businesswoman whom U.S. authorities suspect of connections to Chinese intelligence, alongside separate reporting concerning a relationship with a senior NVIDIA executive. On November 8, NVIDIA’s board announced an independent investigation into whether Huang had been targeted by a foreign intelligence operation. At the time, directors stated that they had no reason to believe company secrets or national security had been compromised. The controversy subsequently attracted congressional attention, including calls for Huang’s resignation and questions about semiconductor export controls and the security of advanced AI technology. The espionage allegations remain contested, and no compromise of NVIDIA technology has been publicly established. For the data center industry, however, the immediate question extends beyond the circumstances of Huang’s departure. It concerns the potential disruption of an infrastructure ecosystem increasingly organized

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Google’s Utah Deal Puts Geothermal Power on the Data Center Map

In Taiwan, the Work Begins With Access to Land Google’s first geothermal procurement agreements in Asia call for an initial 10 MW of new generation on Taiwan’s grid to support local data centers and offices. When Google and developer Baseload Capital announced the agreements in April 2025, a Google energy executive told Taiwan Public Television Service that the companies expected operations to begin in 2029. The original timetable allowed roughly four years between signing a customer and delivering electricity. Baseload’s development work in Hualien County illustrates one reason such projects take time. In November 2025, the company reported that members of the Hongye Tribe had voted to approve a public-land lease for geothermal exploration. Baseload opened a local office, reached an agreement with the community, and secured an exploration permit for a two-year program of drilling in stages. The company has described Hongye separately from Google’s contracted supply. What the Hualien project documents is an early milestone rarely visible in a power purchase announcement: the developer secured community consent before drilling could establish what the field might produce. Kenya Has the Generating Field. The Campus Remains Unresolved. In Kenya’s Rift Valley, the appeal of Olkaria was evident when Microsoft and G42 announced their digital investment initiative in 2024. Kenya already had a fleet of geothermal generating stations at Olkaria. G42 and local partners proposed building a campus there, powered by geothermal electricity and hosting Microsoft Azure services for a new East Africa cloud region. Two difficulties emerged. In May 2026, Semafor reported that President William Ruto had cited insufficient available power as an obstacle to the project. Separately, Reuters, citing Bloomberg, reported disagreements over payment guarantees. Microsoft and G42 had sought a commitment from the Kenyan government to buy a certain amount of computing capacity annually. Kenya’s principal secretary for

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Alberta’s Gigawatt Play: Why Building Data Centers Means Building an Industry

For Alberta’s emerging data center industry, the difference between a roadmap and an excavator has become increasingly consequential. A few years ago, Western Canada’s data center conversation revolved around the possibilities: abundant energy resources, available land, a favorable climate and the prospect of attracting hyperscale investment to a region better known for oil, gas and other industrial development. Today, earthmoving equipment is preparing the ground for what is expected to become Canada’s largest data center, and the questions facing the province have changed accordingly. The shift was on display at Data Centre West 2026, held in Calgary in September, where some 500 industry and government leaders gathered to examine the infrastructure and policy requirements of Alberta’s rapidly expanding digital economy. But for conference founder Vlad Oujegov, the most revealing development wasn’t simply the appearance of projects measured in gigawatts. It was the growing recognition that building those projects will require Alberta to develop an entire supporting industry, while confronting the environmental, political and community questions that increasingly accompany large-scale AI infrastructure. “The theme last year was the data center roadmap,” Oujegov told Data Center Frontier Editor in Chief Matt Vincent during a new episode of the Data Center Frontier Show podcast. “This year’s theme really to me was about execution and actually getting things done, actually seeing projects materialize and construction beginning.” Oujegov is president and founder of the Western Canada Data Centre Alliance, which organizes Data Centre West, and serves as National Data Center Power Systems Lead at Schneider Electric. His perspective draws on both Alberta’s emerging development pipeline and the wider industrial ecosystem now being assembled around it. In DCF’s earlier reporting from Data Centre West 2026, the central question was how quickly Alberta could convert growing hyperscale demand into deliverable capacity. The latest podcast conversation takes that

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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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