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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 […]

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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 more work with less people. Labor is a common challenge across these industries, yet we rely on them to provide the food, the fuel, fiber, infrastructure and the landscaping care that we depend upon every day,” Hindman said.

These facts by themselves aren’t political; they’re about business and providing food for the world. Hindman noted there is a $15 trillion infrastructure ap that needs to be closed by 2040. He said John Deere loves to solve these problems and it is taking its tech stack, three decades in the making, and applying it across more machines to safely run autonomously in complex environments. It will add the tech to both new equipment and existing vehicles.

“Our agriculture, construction, and commercial landscaping customers all have work that must get done at certain times of the day and year, yet there is not enough available and skilled labor to do the work,”
said Hindman. “Autonomy can help address this challenge. That’s why we’re extending our technology stack to enable more machines to operate safely and autonomously in unique and complex environments. This will not only benefit our customers, but all of us who rely on them to provide the food, fuel, fiber, infrastructure, and landscaping care that we depend on every day.”

Building on Deere’s autonomous technology first revealed at CES 2022, the company’s second generation autonomy kit combines advanced computer vision, AI, and cameras to help the machines navigate their environments. The company is using connectivity, renewable fuels and electrification.

Autonomy Expanding to More Machines

John Deere’s Autonomous Articulated Dump Truck.

Autonomous 9RX Tractor for Large-Scale Agriculture: Tillage is one of the busiest times of the year for farmers. With the second-generation autonomy kit, featuring 16 individual cameras arranged in pods to enable a 360-degree view of the field, farmers can step away from the machine and focus their time on other important jobs. The advanced autonomy kit also calculates depth more accurately at larger distances, allowing the tractor to pull more equipment and drive faster.

Willy Pell, CEO of John Deere’s Blue River Technology, said the company added a lot more cameras since the first generation and it coordinates those cameras relative to each other. It allows the machine to do operations 40% faster. An autonomy kit works for every type of job needed. The compute sits on the edge, inside the tractor, and they process every single pixel. They’re also rugged, Hindman said. The team has had to figure out how to deal with things like insects, which can cause problems at night when the tractors are running and the insects get in the way of the cameras, Pell said.

Autonomous 5ML Orchard Tractor for Air Blast Spraying: Protecting crops through air blast spraying is a challenging and repetitive job. Featuring the latest autonomy kit with added Lidar sensors to address the dense canopies found in orchards, the initial machine will be offered with a diesel engine. A battery electric tractor of comparable size and capacity to existing diesel 5M/ML models on the market today will follow. 

What a tractor sees with its sensors while moving down a row.

Igino Cafiero, director of high value crop autonomy at John Deere, said in a briefing that such tractors have to operate in dense areas of foliage that can grow as high as 30 feet. That creates accuracy challenges for GPS navigation and obstacle detection. The company added LIDAR sensors to detect obstacles and drive down a row while flagging humans, pipes, or other objects.

A self-driving dump truck being loaded.
A self-driving dump truck being loaded.

460 P-Tier Autonomous Articulated Dump Truck (ADT) for Quarry Operations: Quarries supply the essential raw materials vital for building roads, buildings, and infrastructure, and it’s a complex process to mine, process, and transport materials. Using the second-generation kit, the ADT will handle the repetitive tasks of transporting material around the quarry to facilitate different steps in the cycle.

Maya Sripadam, senior product manager at John Deere’s Blue River Technology, said there are eight quarries within a 12-mile radius of the Mandalay Bay in Las Vegas. That’s pretty common. She noted that the world’s population is expected to grow from eight billion to nearly 10 billion by 2050, and that increases demand on the food supply and the need for roads and more.

UN Habitat estimates we need to build 96,000 new houses a day to provide enough housing for the increased population. Quarries supply those materials to the tune of thousands of tons of material per day.

Operating these machines is tough, as it requires precise operation with rudimentary tools and rugged places. Operators often have to rely on instructions via walkie-talkie to move 92,000 pounds of material — the weight of seven African elephants — around a quarry safely, Sripadam. They’re often operating day and night on a regular schedule.

The dump trucks are built in Davenport, Iowa, and they use the tech component stacks developed over 30 years. Each truck uses connectivity for satellites internet, advanced controls and high-performance GPUs. The autonomy kit sits atop a truck and gives it a 360-degree view of the land around it. It helps it navigate obstacles or pull over for a faster moving vehicle to pass. Trucks can operate autonomously without supervision in some work and be supervised by humans in others.

John Deere’s autonomous mower.

Autonomous Battery Electric Mower for Commercial Landscaping: Commercial landscaping is a highly competitive industry and having the staff to support different bids is essential. The autonomous commercial mower leverages the same camera technology as other Deere autonomous machines, but on a reduced scale since the machine has a smaller footprint. With two cameras on the front, left, right, and rear, 360-degree coverage is achieved, and staff can focus on other aspects of the job.

Matt Potter, director of robotics and mobility technology at John Deere, said in a briefing that landscaping places also face a chronic shortage of labor. He the mower taps the same autonomy kit that the tractors use but it gets by with fewer cameras. As an electric mower, it operates quietly and can be used early in the morning without waking the humans.

Select new machines will be autonomy ready with retrofit kits available for certain existing machines, providing customers with multiple paths to adoption based on where they are in their technology journey.

John Deere’s Autonomous Electric Battery Mower.

The machines are managed via John Deere Operations Center Mobile, the company’s cloud-based platform. By swiping left to right to start, the machine can be started once placed in the appropriate spot.

Through the app, users also have access to live video, images, data and metrics, and the ability to adjust various factors like speed. In the event of any job quality anomalies or machine health issues, users will be notified remotely so they can make necessary adjustments.

The big message is that the food that we eat and the work that goes into it — through manual labor or advanced technology — can’t be taken for granted, said Hindman. And he noted that farmers don’t want to spend their days sitting in these machines, given what they can do.

At CES 2025, John Deere will have booth #5016 in the West Hall at the Las Vegas Convention Center.

John Deere’s Autonomous Diesel Orchard Tractor

The company’s leaders are also speaking at these sessions on January 8:

  • At 9 a.m., Deanna Kovar, President for the Worldwide Agriculture & Turf Division at John Deere will speak on a panel titled, “Tech Without Borders: The Benefits of Tech for all Communities.” The discussion will take place in the Las Vegas Convention Center’s North Hall, Level 2, N258.
  • At 1 p.m., Sarah Schinckel, Director of Emerging Technologies in the Intelligent Solutions Group(ISG) at John Deere will speak on a panel titled, “AI or Die? Why Farms Must Embrace the AI Revolution to Survive.” The discussion will take place in the Las Vegas Convention Center’s West Hall, Level 2, W218.
  • At 3 p.m., Gaurav Bansal, VP of Engineering at Blue River Technology (a John Deere company) will speak on a panel titled, “Robot Farm 2050: A Look at Robotics & The Future of Farming.” The discussion will take place in the Las Vegas Convention Center’s West Hall, Level 2, W218.
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Á la carte energy market will give Western states choice, flexibility and reliability

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India Told to Drop Russian Oil for US Trade Deal

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FERC scraps plan to update gas infrastructure policy after DOE directive

At the Trump administration’s request, the US Federal Energy Regulatory Commission (FERC), an independent agency, abandoned its plan Sept. 12 to update the policy it uses to evaluate natural gas pipeline and LNG projects. The decision to scrap the long-running proceeding to revise the 1999 certificate policy for new natural gas facilities could indicate that the Department of Energy (DOE) intends to take a larger role in FERC policy, law firm Akin Gump Strauss Hauer & Feld LLP said in a recent blog post. While FERC’s adoption of the request to end the proceedings will not result in any immediate changes to FERC policy, Akins said “it does signal that the DOE intends to be more involved in FERC policy making going forward and may be the first in a string of DOE efforts to reshape energy policy within FERC’s traditional purview.” FERC had until the end of September to act on a directive from Energy Secretary Chris Wright to terminate the proceeding that the commission has worked on since 2018. Wright said the move was necessary to remove industry uncertainty. “We believe that the 1999 Certificate Policy Statement, as subsequently applied by the Commission, continues to provide the appropriate framework for reviewing proposed natural gas projects in a legally durable manner, pursuant to the Natural Gas Act and consistent with judicial precedent, as it has for over 25 years. Therefore, we are now withdrawing the draft Updated Certificate Policy Statement and closing the proceeding,” FERC wrote in the Sep. 12 order. The commission added that the topics addressed in the proceeding were “better considered on a case-by-case basis.” By terminating the proceeding, FERC would now have to initiate a new docket and develop a new record if it wants to seek a policy change in the future, Akins said.

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bp scales back biofuels ambitions, shelves Rotterdam project amid strategic shift

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ExxonMobil sanctions Hammerhead development offshore Guyana

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@import url(‘https://fonts.googleapis.com/css2?family=Inter:[email protected]&display=swap’); a { color: #1796c1; } .ebm-page__main h1, .ebm-page__main h2, .ebm-page__main h3, .ebm-page__main h4, .ebm-page__main h5, .ebm-page__main h6 { font-family: Inter; } body { line-height: 150%; letter-spacing: 0.025em; font-family: Inter; } button, .ebm-button-wrapper { font-family: Inter; } .label-style { text-transform: uppercase; color: var(–color-grey); font-weight: 600; font-size: 0.75rem; } .caption-style { font-size: 0.75rem; opacity: .6; } #onetrust-pc-sdk [id*=btn-handler], #onetrust-pc-sdk [class*=btn-handler] { background-color: #1796c1 !important; border-color: #1796c1 !important; } #onetrust-policy a, #onetrust-pc-sdk a, #ot-pc-content a { color: #1796c1 !important; } #onetrust-consent-sdk #onetrust-pc-sdk .ot-active-menu { border-color: #1796c1 !important; } #onetrust-consent-sdk #onetrust-accept-btn-handler, #onetrust-banner-sdk #onetrust-reject-all-handler, #onetrust-consent-sdk #onetrust-pc-btn-handler.cookie-setting-link { background-color: #1796c1 !important; border-color: #1796c1 !important; } #onetrust-consent-sdk .onetrust-pc-btn-handler { color: #1796c1 !important; border-color: #1796c1 !important; background-color: undefined !important; } Welcome to Nomads at the Summit, a new podcast series from Data Center Frontier in partnership with the Nomad Futurist Foundation. Recorded live at the 2025 Data Center Frontier Trends Summit (Aug. 26-28), here we sit down with industry leaders, innovators, and change-makers shaping the future of digital infrastructure. Join hosts Nabeel Mahmood and Phillip Koblence of Nomad Futurist, alongside DCF editorial leadership including Editor at Large Melissa Farney and Senior Editor David Chernicoff, for these candid conversations that highlight the ideas, talent, and technologies driving the next chapter of the data center industry. Whether you attended the DCF Trends Summit in person or are just now tuning in from afar, Nomads at the Summit gives you a behind-the-scenes look at the people and innovations defining what’s next in digital infrastructure. <!–> EPISODE LIST ]–> Waste Heat to Water – The Path Towards Water Positive Data Centers In this DCF Trends-Nomads at the Summit Podcast episode, Matt Grandbois, Vice President at AirJoule, introduces a game-changing approach to one of the data center industry’s most pressing challenges: water sustainability. As power-hungry, high-density environments collide with growing water scarcity

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Balancing AI’s opportunities and challenges to serve enterprises

AI has taken the technology industry by storm, with enterprises deploying emerging applications to create business value. Amid this shift, operators are leveraging network automation, optical innovation and more to support enterprise AI use cases. Still, the technology ecosystem must balance AI’s opportunities with its challenges. While AI can improve operations, it can also leave companies more vulnerable to cyberattacks. As organizations deploy more AI tools and employees increasingly use them, the overall attack surface expands and opens more security gaps. This article explores how internet carriers are building their networks to support enterprises, while also discussing how operators are establishing trust with customers. Table stakes: reliability, diversity and reach AI’s requirements are similar to content distribution, cloud networking and previous industry shifts, but place even greater pressure on carrier-delivered enterprise network services.  In these services, network diversity is integral, allowing carriers to eliminate single points of failure in the event of an outage, then quickly reroute traffic through the next best available path. This improved reliability is vital for enabling real-time enterprise AI operations amid increased instances of network disruption due to geopolitical sabotage or accidental damage. As more hyperscalers build sprawling AI data center campuses, network reach will also prove even more crucial. By continuously expanding their network footprints, carriers can help enterprises access these sites no matter where they’re located, with operators’ high-capacity connectivity infrastructure facilitating the transfer of massive data volumes between these campuses. Similar to how content distribution networks rely on a robust network underlay, backbone connectivity provides the high-capacity, long-haul transport underpinning the delivery of AI inferencing responses. While the backbone itself does not cache or deliver these responses, its densely interconnected networks ensure that this AI traffic reaches regional and access networks, which then distribute responses to end users. Lightspeed: optical innovation With

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Microsoft’s new cooling tech targets AI’s thermal bottleneck as hyperscalers hit power ceilings

Rising thermal pressure on AI hardware AI workloads and high-performance computing have placed unprecedented strain on data center infrastructure. Thermal dissipation has emerged as one of the toughest bottlenecks, with traditional methods such as airflow and cold plates increasingly unable to keep pace with new generations of silicon. “Modern accelerators are throwing out thermal loads that air systems simply cannot contain, and even advanced water loops are straining. The immediate issues are not only the soaring TDP of GPUs, but also grid delays, water scarcity, and the inability of legacy air-cooled halls to absorb racks running at 80 or 100 kilowatts,” said Sanchit Vir Gogia, CEO and chief analyst at Greyhound Research. “Cold plates and immersion tanks have extended the runway, but only marginally. They still suffer from the resistance of thermal interfaces that smother heat at the die. The friction lies in the last metre of the thermal path, between junction and package, and that is where performance is being squandered.” Cooling costs: the next data center budget crisis Cooling isn’t just a technical challenge but also an economic one. Data centers spend heavily to manage the immense heat generated by servers, networking gear, and GPUs. Hence, the cost of cooling a data center is also a significant expense. “As per 2025 AI infra buildouts TCO analysis, over 45%-47% of data center power budget typically goes into cooling, which could further expand to 65%-70% without advancement in cooling method efficiency,” said Danish Faruqui, CEO at Fab Economics. “In 2024, Nvidia Hopper H100 had 700 watts of power requirements per GPU, which scaled in 2025 to double with Blackwell B200 and Blackwell Ultra B300 to 1000 W and 1400 watts per GPU. Going forward in 2026, it will again more than double by Rubin and Rubin Ultra GPU to 1800W

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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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