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BP Halts Share Buybacks

BP Plc is halting share buybacks to shore up its balance sheet as pressure mounts on the UK energy giant to deliver on its turnaround efforts.  The company is slashing a $750 million quarterly stock repurchases program that had already been reduced last year, according to a fourth-quarter earnings report Tuesday. BP also withdrew its […]

BP Plc is halting share buybacks to shore up its balance sheet as pressure mounts on the UK energy giant to deliver on its turnaround efforts. 

The company is slashing a $750 million quarterly stock repurchases program that had already been reduced last year, according to a fourth-quarter earnings report Tuesday. BP also withdrew its standing guidance of returning 30% to 40% of operating cash flow to shareholders. 

The quarter capped a tumultuous year for BP that started with activist investor Elliott Investment Management pushing for drastic change and ended with Chairman Albert Manifold ousting Murray Auchincloss from the helm. Oil prices have fallen since it outlined a strategic shift last year.

Oil prices are trading below the roughly $73 a barrel BP assumed for 2026 in its plan last year. BP also said upstream production is expected to be slightly lower than last year.

Like rival Shell Plc, BP has been slower to increase production than its US peers. On a positive note, BP said the big Bumerangue discovery in Brazil has 8 billion barrels of liquids in place, split 50%-50% between crude and condensate.

So far this year, the shares of the two London-based companies have lagged behind in dollar terms among the top five oil majors, including European peer TotalEnergies SE, which has been expanding aggressively in Africa.  

BP said cost cuts will be deepened by as much as $1.5 billion through the end of 2027, thanks to the divestment of lubricant business Castrol. As part of its turnaround plan last year, the company had announced targets of $4 billion to $5 billion of cost cuts by the end of 2027.

BP said at the end of last year it will raise about $6 billion from the sale of a majority stake in Castrol. 

Net income of $1.54 billion came in line with the average analyst estimate of $1.53 billion. 

Meg O’Neill, the Woodside Energy Group Ltd. chief executive officer picked to replace Auchincloss, takes over this coming April. Her track record as a champion of fossil fuels suggest she’ll speed up a shift away from low-returning clean energy projects that has been welcomed by shareholders.

As flagged last month, BP took a writedown of about $4 billion from its energy transition business in the fourth quarter. That included Archaea Energy, the biogas business BP agreed to buy for $4.1 billion in 2022, as well as its solar and battery unit Lightsource and offshore wind assets.

Asset impairments charges since the end of 2022 — when BP first began retreating from its low-carbon ambitions — have piled up to nearly $25 billion, RBC analyst Biraj Borkhataria said before the earnings report. 

BP purchased Archaea Energy in 2022 as part of its expansion into lower-carbon fuels. But the renewable natural gas business that was supposed to benefit the environment and BP’s net zero emissions targets has faltered, as have BP’s climate ambitions.

The assets that were part of the writedowns had been core to BP’s green goals, when former CEO Bernard Looney in 2020 announced a move into low-carbon ventures and away from oil and gas.



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DKnife targets network gateways in long running AitM campaign

Beyond update hijacking, the framework supports DNS manipulation, binary replacement, and selective traffic forwarding, giving attackers control over how specific requests are handled. Indicators point to China-Nexus development and targeting Several aspects of DKnife’s design and operation suggested ties to China-aligned threat actors. Talos identified configuration data and code comments written in

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Four new vulnerabilities found in Ingress NGINX

NGINX is a reverse proxy/load balancer that generally acts as the front-end web traffic receiver and directs it to the application service for data transformation. Ingress NGINX is a version used in Kubernetes as the controller for traffic coming into the infrastructure. It takes care of mapping traffic to pods

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Transocean to Buy Valaris in Near $6B Deal

Transocean Ltd and Valaris Limited announced, in a joint statement, the signing of a definitive agreement to combine the two companies. Under the agreement, Transocean will acquire Valaris in an all-stock transaction valued at approximately $5.8 billion, the statement noted. The shareholding percentages of the combined company, on a fully diluted basis, will be approximately 53 percent for Transocean and 47 percent for Valaris, according to the statement. Valaris shareholders will receive a fixed exchange ratio of 15.235 shares of Transocean stock for each common share of Valaris under the terms of the all-stock transaction, the statement highlighted. Based on the closing prices of Transocean and Valaris on February 6, the transaction implies a combined enterprise value of approximately $17 billion, the statement noted. The transaction was unanimously approved by the boards of directors of both companies and is expected to close in the second half of 2026, subject to regulatory approvals and customary closing conditions, and approvals by the shareholders of each company, the joint statement said. The statement outlined that the deal “creates an industry leader with a diversified offshore fleet of 73 rigs, including 33 ultra-deepwater drillships, nine semisubmersibles and 31 modern jackups, to meet emerging growth opportunities”. It also “expands reach and customer access in world’s most attractive offshore basins” and “unlocks more than $200 million in identified cost synergies”, the statement highlighted, adding that it “increases cash flow, accelerates deleveraging, and strengthens financial flexibility”. Keelan Adamson, Transocean President and Chief Executive Officer, said in the statement, “this transaction creates a very attractive investment in the offshore drilling industry, differentiated by the best fleet, proven people, leading technologies, and unequalled customer service”. “The powerful combination is well-timed to capitalize on an emerging, multi-year offshore drilling upcycle. Investors and our global customers will benefit from our expanded fleet of best-in-class, high-specification rigs,” he added. “We have identified more than $200 million in

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BP Halts Share Buybacks

BP Plc is halting share buybacks to shore up its balance sheet as pressure mounts on the UK energy giant to deliver on its turnaround efforts.  The company is slashing a $750 million quarterly stock repurchases program that had already been reduced last year, according to a fourth-quarter earnings report Tuesday. BP also withdrew its standing guidance of returning 30% to 40% of operating cash flow to shareholders.  The quarter capped a tumultuous year for BP that started with activist investor Elliott Investment Management pushing for drastic change and ended with Chairman Albert Manifold ousting Murray Auchincloss from the helm. Oil prices have fallen since it outlined a strategic shift last year. Oil prices are trading below the roughly $73 a barrel BP assumed for 2026 in its plan last year. BP also said upstream production is expected to be slightly lower than last year. Like rival Shell Plc, BP has been slower to increase production than its US peers. On a positive note, BP said the big Bumerangue discovery in Brazil has 8 billion barrels of liquids in place, split 50%-50% between crude and condensate. So far this year, the shares of the two London-based companies have lagged behind in dollar terms among the top five oil majors, including European peer TotalEnergies SE, which has been expanding aggressively in Africa.   BP said cost cuts will be deepened by as much as $1.5 billion through the end of 2027, thanks to the divestment of lubricant business Castrol. As part of its turnaround plan last year, the company had announced targets of $4 billion to $5 billion of cost cuts by the end of 2027. BP said at the end of last year it will raise about $6 billion from the sale of a majority stake in Castrol.  Net income of $1.54 billion came

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Oil Settles Higher as Hormuz Risks Resurface

Oil edged higher after the US advised ships to steer clear of Iranian waters when navigating the Strait of Hormuz, reviving a risk premium that had ebbed in recent days amid nuclear talks. West Texas Intermediate crude futures rose 1.3% to settle above $64 a barrel after the US Department of Transportation said in a maritime advisory on Monday that American-flagged ships should stay as far as possible from Iranian waters. The agency cited a recent incident in which Iran’s Islamic Revolutionary Guard Corps harassed a US-flagged tanker as it was transiting through the waterway last week. The guidance stoked investor fears of a short-term disruption in the vital Hormuz chokepoint, through which about a third of the world’s oil flows, as well as a broader conflagration in the oil-rich Middle East region. Iran has threatened to close Hormuz during times of geopolitical tension. The development reversed bearish momentum that followed pledges by Iran and the US to continue talks following what they described as positive discussions in Oman on Friday. Tehran said the session, aimed at defusing tensions over the Islamic Republic’s nuclear program, was “a step forward.” US President Donald Trump, who has repeatedly threatened Tehran with airstrikes, said there would be another meeting this week. The US leader is also due to see Israeli Prime Minister Benjamin Netanyahu on Feb. 11, while preparing tariffs against countries doing business with Tehran. Crude has pushed higher this year despite widespread concerns about a looming glut, with gains supported by geopolitical tensions as well as halts to some flows, including from Kazakhstan. Still, prices fell last week on signs of progress between Iran and the US. India Flows Traders were also looking at oil flows to India. The country’s imports of Russian oil are expected to drop by about half

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OEUK Flags ‘Prolonged Bout of Severe Weather’ in North Sea

In a statement posted on its website last Thursday, industry body Offshore Energies UK (OEUK) noted that, “amid a prolonged bout of severe weather” in the UK North Sea, “some companies” were “removing non essential staff from their sites as supplies are running short”. OEUK’s Health and Safety Manager, Graham Skinner, said in the statement, “we’re proud of the resilience of our workforce and we’re proud of the fact our industry keeps the lights on whatever happens”. “Although we get this sort of weather every two or three years or so, it can be quite uncomfortable and there will be people in the workforce who are experiencing it for the first time,” he added. “The waves are up to six meters [19 feet], about the height of an average house, which isn’t that big by North Sea standards. The problem is that the stormy weather has gone on for so long, supply boats can’t deliver,” Skinner continued. “That means fresh water and fresh food start to run short so it’s better to take non essential people off platform so there’s enough to go round the people who are left,” he went on to state. A shipping forecast issued by the Met Office, and hosted on its website, on behalf of the Maritime and Coastguard Agency, at 11:30 UTC on February 9, for the period 12:00 UTC on February 9 to 12:00 UTC on February 10, stated that “there are warnings of gales in FitzRoy and Southeast Iceland”. On the Met Office site, the sea state in FitzRoy is described as “rough or very rough, becoming very rough later” and the sea state in Southeast Iceland is described as “rough or very rough”. The Met Office website is issuing UK weather warnings for Monday, Tuesday, and Wednesday at the time of writing. In a statement posted on its

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Energy Department Launches Genesis Mission Consortium to Accelerate AI-Driven Scientific Discovery and American innovation

 WASHINGTON—The U.S. Department of Energy (DOE) today announced the launch of the Genesis Mission Consortium, a historic public-private partnership advancing the Department’s Genesis Mission to harness the power of artificial intelligence (AI) to accelerate scientific discovery, strengthen national security, and ensure America leads in energy and emerging technologies. Building on President Trump’s Executive Orders Launching The Genesis Mission and Removing Barriers to American Leadership In Artificial Intelligence, the consortium brings together technical capabilities and expertise from the Department of Energy, National Laboratories, private sector leaders, and academic institutions to usher in a new era of science and technology exploration. “The Genesis Mission Consortium represents a bold step toward transforming the way we approach scientific challenges,” said DOE Under Secretary for Science and Genesis Mission Lead Dr. Darío Gil. “Thanks to President Trump’s leadership, we’re uniting government, industry, and academia to create a powerful engine for innovation that will drive breakthroughs across multiple disciplines.” The consortium will help identify high-value partnerships among its members and external stakeholders, strengthening collaborative responses to funding opportunities. It will amplify DOE’s outreach by promoting solicitations, executing agreements, and tracking project successes. Functioning as a collaborative hub, the consortium will serve as a single, coordinated access point for members and their resources. To advance technical priorities, the consortium will facilitate member-driven working groups focused on AI model development and validation, data integration and standards, high-performance computing and cloud infrastructure, and robotics and automation. These working groups will provide an efficient mechanism for engaging industry and academic organizations in co-creation efforts. The Genesis Mission Consortium will also host regular events, including annual member meetings, workshops, and technology showcases, providing members with high-impact networking and collaboration opportunities. The consortium will be administered by TechWerx, a DOE partnership intermediary operated by RTI International. For more information on the Genesis Mission Consortium and how to get involved, visit www.genesismissionconsortium.org.

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Russia Crude Output Shrinks

Russia’s crude output declined for a second straight month in January as the world’s third largest oil producer faces difficulty in marketing its barrels because of US sanctions. The nation pumped an average of 9.28 million barrels a day of crude oil last month, according to people with knowledge of the data, who asked not to be identified discussing classified information. The figure — which doesn’t include output of condensate — is 46,000 barrels a day below an already-reduced level in December, and almost 300,000 barrels a day lower than what Russia is allowed to produce under an agreement with the Organization of the Petroleum Exporting Countries and allies. Russia has classified its data on oil production, exports and refinery operations, making independent assessments difficult. Its Energy Ministry didn’t immediately respond to a Bloomberg request for a comment on the January output level and future production plans. The decline in production comes as the amount of Russian crude held on tankers continues to grow, indicating that some cargoes are taking significant time to find buyers amid growing US pressure on the Kremlin. Earlier this month, US President Donald Trump said he eliminated an extra 25% tariff he had imposed on India in exchange for New Delhi halting oil purchases from Russia.  While India confirmed the trade deal, it has not commented on details including oil. Still, nearly all state-owned and private Indian refiners have paused buying any spot cargoes since Trump first mentioned the deal in a social media post about a week ago. By the start of February, accumulated volumes of Russian crude on water reached 143 million barrels, almost doubling from a year ago and creeping up by more than a quarter compared to late November. As India has pulled back from purchases, some tankers with sanctioned barrels are now heading for

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US pushes voluntary pact to curb AI data center energy impact

Others note that cost pressure isn’t limited to the server rack. Danish Faruqui, CEO of Fab Economics, said the AI ecosystem is layered from silicon to software services, creating multiple points where infrastructure expenses eventually resurface. “Cloud service providers are likely to gradually introduce more granular pricing models across cloud, AI, and SaaS offerings, tailored by customer type, as they work to absorb the costs associated with the White House energy and grid compact,” Faruqui said.   This may not show up as explicit energy surcharges, but instead surface through reduced discounts, higher spending commitments, and premiums for guaranteed capacity or performance. “Smaller enterprises will feel the impact first, while large strategic customers remain insulated longer,” Rawat said. “Ultimately, the compact would delay and redistribute cost pressure; it does not eliminate it.” Implications for data center design The proposal is also likely to accelerate changes in how AI facilities are designed. “Data centers will evolve into localized microgrids that combine utility power with on-site generation and higher-level implementation of battery energy storage systems,” Faruqui said. “Designing for grid interaction will become imperative for AI data centers, requiring intelligent, high-speed switching gear, increased battery energy storage capacity for frequency regulation, and advanced control systems that can manage on-site resources.”

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Intel teams with SoftBank to develop new memory type

However, don’t expect anything anytime soon. Intel’s Director of Global Strategic Partnerships Sanam Masroor outlined the plans in a blog post. Operations are expected to begin in Q1 2026, with prototypes due in 2027 and commercial products by 2030. While Intel has not come out and said it, that memory design is almost identical to HBM used in GPU accelerators and AI data centers. HBM sits right on the GPU die for immediate access to the GPU, unlike standard DRAM which resides on memory sticks plugged into the motherboard. HBM is much faster than DDR memory but is also much more expensive to produce. It’s also much more profitable than standard DRAM which is why the big three memory makers – Micron, Samsung, and SK Hynix – are favoring production of it.

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Nvidia’s $100 Billion OpenAI Bet Shrinks and Signals a New Phase in the AI Infrastructure Cycle

One of the most eye-popping figures of the AI boom – a proposed $100 billion Nvidia commitment to OpenAI and as much as 10 gigawatts of compute for the company’s Stargate AI infrastructure buildout – is no longer on the table. And that partial retreat tells the data center industry something important. According to multiple reports surfacing at the end of January, Nvidia has paused and re-scoped its previously discussed, non-binding investment framework with OpenAI, shifting from an unprecedented capital-plus-infrastructure commitment to a much smaller (though still massive) equity investment. What was once framed as a potential $100 billion alignment is now being discussed in the $20-30 billion range, as part of OpenAI’s broader effort to raise as much as $100 billion at a valuation approaching $830 billion. For data center operators, infrastructure developers, and power providers, the recalibration matters less for the headline number and more for what it reveals about risk discipline, competitive dynamics, and the limits of vertical circularity in AI infrastructure finance. From Moonshot to Measured Capital The original September 2025 memorandum reportedly contemplated not just capital, but direct alignment on compute delivery: a structure that would have tightly coupled Nvidia’s balance sheet with OpenAI’s AI-factory roadmap. By late January, however, sources indicated Nvidia executives had grown uneasy with both the scale and the structure of the deal. Speaking in Taipei on January 31, Nvidia CEO Jensen Huang pushed back on reports of friction, calling them “nonsense” and confirming Nvidia would “absolutely” participate in OpenAI’s current fundraising round. But Huang was also explicit on what had changed: the investment would be “nothing like” $100 billion, even if it ultimately becomes the largest single investment Nvidia has ever made. That nuance matters. Nvidia is not walking away from OpenAI. But it is drawing a clearer boundary around

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

Each month Data Center Frontier, in partnership with Pkaza, posts some of the hottest data center career opportunities in the market. Here’s a look at some of the latest data center jobs posted on the Data Center Frontier jobs board, powered by Pkaza Critical Facilities Recruiting. Looking for Data Center Candidates? Check out Pkaza’s Active Candidate / Featured Candidate Hotlist Onsite Engineer – Critical FacilitiesCharleston, SC This is NOT a traveling position. Having degreed engineers seems to be all the rage these days. I can also use this type of candidate in following cities: Ashburn, VA; Moncks Corner, SC; Binghamton, NY; Dallas, TX or Indianapolis, IN. Our client is an engineering design and commissioning company that is a subject matter expert in the data center space. This role will be onsite at a customer’s data center. They will provide onsite design coordination and construction administration, consulting and management support for the data center / mission critical facilities space with the mindset to provide reliability, energy efficiency, sustainable design and LEED expertise when providing these consulting services for enterprise, colocation and hyperscale companies. This career-growth minded opportunity offers exciting projects with leading-edge technology and innovation as well as competitive salaries and benefits. Electrical Commissioning Engineer Ashburn, VA This traveling position is also available in: New York, NY; White Plains, NY;  Richmond, VA; Montvale, NJ; Charlotte, NC; Atlanta, GA; Hampton, GA; New Albany, OH; Cedar Rapids, IA; Phoenix, AZ; Salt Lake City, UT; Dallas, TX; Kansas City, MO; Omaha, NE; Chesterton, IN or Chicago, IL. *** ALSO looking for a LEAD EE and ME CxA Agents and CxA PMs *** Our client is an engineering design and commissioning company that has a national footprint and specializes in MEP critical facilities design. They provide design, commissioning, consulting and management expertise in the critical facilities space. They

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Operationalizing AI at Scale: Google Cloud on Data Infrastructure, Search, and Enterprise AI

The AI conversation has been dominated by model announcements, benchmark races, and the rapid evolution of large language models. But in enterprise environments, the harder problem isn’t building smarter models. It’s making them work reliably with real-world data. On the latest episode of the Data Center Frontier Show Podcast, Sailesh Krishnamurthy, VP of Engineering for Databases at Google Cloud, pulled back the curtain on the infrastructure layer where many ambitious AI initiatives succeed, or quietly fail. Krishnamurthy operates at the intersection of databases, search, and AI systems. His perspective underscores a growing reality across enterprise IT: AI success increasingly depends on how organizations manage, integrate, and govern data across operational systems, not just how powerful their models are. The Disconnect Between LLMs and Reality Enterprises today face a fundamental challenge: connecting LLMs to real-time operational data. Search systems handle documents and unstructured information well. Operational databases manage transactions, customer data, and financial records with precision. But combining the two remains difficult. Krishnamurthy described the problem as universal. “Inside enterprises, knowledge workers are often searching documents while separately querying operational systems,” he said. “But combining unstructured information with operational database data is still hard to do.” Externally, customers encounter the opposite issue. Portals expose personal data but struggle to incorporate broader contextual information. “You get a narrow view of your own data,” he explained, “but combining that with unstructured information that might answer your real question is still challenging.” The result: AI systems often operate with incomplete context. Vector Search Moves Into the Database Vector search has emerged as a bridge between structured and unstructured worlds. But its evolution over the past three years has changed how enterprises deploy it. Early use cases focused on semantic search, i.e. finding meaning rather than exact keyword matches. Bug tracking systems, for example, began

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Transmission at the Breaking Point: Why the Grid Is Becoming the Defining Constraint for AI Data Centers

Regions in a Position to Scale California (A- overall)California continues to lead in long-term, scenario-based transmission planning. CAISO’s most recent transmission plan identifies $4.8 billion in new projects to accommodate approximately 76 gigawatts of additional capacity by 2039, explicitly accounting for data center growth alongside broader electrification. For data center developers, California’s challenge is less about planning quality and more about execution. Permitting timelines, cost allocation debates, and political scrutiny remain significant hurdles. Plains / Southwest Power Pool (B- overall, A in regional planning)SPP stands out nationally for embracing ultra-high-voltage transmission as a backbone strategy. Its recent Integrated Transmission Plans approve more than $16 billion in new projects, including multiple 765-kV lines, with benefit-cost ratios exceeding 10:1. This approach positions the Plains region as one of the most structurally “AI-ready” grids in North America, particularly for multi-gigawatt campuses supported by wind, natural gas, and emerging nuclear resources. Midwest / MISO (B overall)MISO’s Long-Range Transmission Planning framework aligns closely with federal best practices, co-optimizing generation and transmission over long planning horizons. While challenges remain—particularly around interregional coordination—the Midwest is comparatively well positioned for sustained data center growth. Regions Facing Heightened Risk Texas / ERCOT (D- overall)Texas has approved massive new transmission investments, including 765-kV projects tied to explosive load growth in the Permian Basin. However, the report criticizes ERCOT’s planning for remaining largely siloed and reliability-driven, with limited long-term scenario analysis and narrow benefit assessments. For data centers, ERCOT still offers speed to market, but increasingly with risks tied to congestion, price volatility, and political backlash surrounding grid reliability. Southeast (F overall)The Southeast receives failing grades across all categories, with transmission development remaining fragmented, utility-driven, and largely disconnected from durable regional planning frameworks. As AI data centers increasingly target the region for its land availability and tax incentives, the lack of

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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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