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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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IBM FlashSystems gain AI-assisted telemetry, analytics

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Oil Gains As Middle East Tensions Rise

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OPEC Says Oil Production Declined Last Month

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Ukraine Hits Lukoil Refinery

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TotalEnergies Cuts Buyback to Lower End of Range

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EIA Sees Brent Price Dropping in 2026 and 2027

In its latest short term energy outlook (STEO), which was released on February 10, the U.S. Energy Information Administration (EIA) projected that the average Brent spot price will drop in 2026 and 2027. According to this STEO, the EIA sees the Brent spot price coming in at $57.69 per barrel in 2026 and $53.00 per barrel in 2027. The Brent spot price averaged $69.04 per barrel in 2025, the STEO showed. A quarterly breakdown included in the EIA’s latest STEO showed that the organization expects the Brent spot price to come in at $64.44 per barrel in the first quarter of this year, $57.32 per barrel in the second quarter, $55.35 per barrel in the third quarter, $54.00 per barrel in the fourth quarter, and $53.00 per barrel across the first, second, third, and fourth quarters of next year. In the STEO, the EIA highlighted that the Brent crude oil spot price averaged $67 per barrel in January, which it pointed out was $4 per barrel higher than the average in December. The EIA noted that daily Brent crude oil prices increased from an average of $62 per barrel on January 2 to $72 per barrel on January 30. “Crude oil prices rose in response to disruptions to crude oil production in the United States and Kazakhstan,” the EIA highlighted in the STEO. “Despite the near-term increase in prices and short-term disruptions to oil supply, we forecast that strong growth in global oil production will result in high global oil inventory builds over the forecast, causing crude oil prices to fall,” it added. “We forecast that Brent spot prices will average $58 per barrel in 2026 and $53 per barrel in 2027, down from an average of $69 per barrel in 2025,” it continued. In its STEO, the EIA said

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USA Allows Oilfield Contractors to Go to Work in VEN Fields

The US government issued a general license to allow oilfield-service companies to work in Venezuela as the Trump administration eases sanctions and pushes to rebuild the nation’s crude infrastructure. The license issued by the Treasury Department allows US firms to explore, develop and produce oil and natural gas in Venezuela under certain limited conditions, according to a statement Tuesday. The move is the latest in a series of steps Washington has taken to entice US companies to revive output from Venezuela’s vast crude reserves after last month’s capture of strongman Nicolás Maduro. In January, the US issued a general license that allowed for a wide range of crude operations, including exporting, transporting, refining and buying and selling crude. The general license announced Tuesday involves tasks such as geological mapping, reservoir analysis and related tasks that augment the commencement of oil production.  However, the license does not allow new joint ventures in Venezuela. US people and firms will need to provide detailed plans to the State Department and Department of Energy for any work in the country, according to the statement. The Treasury Department is also preparing to issue a general license allowing companies to pump oil in Venezuela, Bloomberg reported earlier this month.  Oilfield service companies are hired by producers to asses discoveries, drill wells, and enhance output from older assets. SLB Ltd., Halliburton Co. and Baker Hughes Co. dominate the sector. SLB has been working in Venezuela for Chevron Corp., operating under a US license held by the supermajor. The other large contractors scaled back or shut down their primary operations in the country as the previous regime tightened control over the energy industry.  WHAT DO YOU THINK? Generated by readers, the comments included herein do not reflect the views and opinions of Rigzone. All comments are subject to editorial review. Off-topic, inappropriate

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Energy providers seek flexible load strategies for data center operations

“In theory, yes, they’d have to wait a little bit longer while their queries are routed to a data center that has capacity,” said Lawrence. The one thing the industry cannot do is operate like it has in the past, where data center power was tuned and then forgotten for six months. Previously, data centers would test their power sources once or twice a year. They don’t have that luxury anymore. They need to check their power sources and loads far more regularly, according to Lawrence. “I think that for that for the data center industry to continue to survive like we all need it, there’s going to have to be some realignment on the incentives to why somebody would become flexible,” said Lawrence. The survey suggests that utilities and load operators expect to expand their demand response activities and budgets in the near term. Sixty-three percent of respondents anticipate DR program funding to grow by 50% or more over the next three years. While they remain a major source of load growth and system strain, 57% of respondents indicate that onsite power generation from data centers will be most important to improving grid stability over the next five years. One of the proposed fixes to the power shortage has been small modular nuclear reactors. These have gained a lot of traction in the marketplace even if they have nothing to sell yet. But Lawrence said that that’s not an ideal solution for existing power generators, ironically enough.

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Nokia predicts huge WAN traffic growth, but experts question assumptions

Consumer, which includes both mobile access and fixed access, including fixed wireless access. Enterprise and industrial, which covers wide-area connectivity that supports knowledge work, automation, machine vision, robotics coordination, field support, and industrial IoT. AI, including applications that people directly invoke, such as assistants, copilots, and media generation, as well as autonomous use cases in which AI systems trigger other AI systems to perform functions and move data across networks. The report outlines three scenarios: conservative, moderate, and aggressive. “Our goal is to present scenarios that fall within a realistic range of possible outcomes, encouraging stakeholders to plan across the full spectrum of high-impact demand possibilities,” the report says. Nokia’s prediction for global WAN traffic growth ranges from a 13% CAGR for the conservative scenario to 16% CAGR for moderate and 22% CAGR for aggressive. Looking more closely at the moderate scenario, it’s clear that consumer traffic dominates. Enterprise and industrial traffic make up only about 14% to 17% of overall WAN traffic, although their share is expected to grow during the 10-year forecast period. “On the consumer side, the vast majority of traffic by volume is video,” says William Webb, CEO of the consulting firm Commcisive. Asked whether any of that consumer traffic is at some point served up by enterprises, the answer is a decisive “no.” It’s mostly YouTube and streaming services like Netflix, he says. In short, that doesn’t raise enterprise concerns. Nokia predicts AI traffic boom AI is a different story. “Consumer- and enterprise-generated AI traffic imposes a substantial impact on the wide-area network (WAN) by adding AI workloads processed by data centers across the WAN. AI traffic does not stay inside one data center; it moves across edge, metro, core, and cloud infrastructure, driving dense lateral flows and new capacity demands,” the report says. An

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Cisco amps up Silicon One line, delivers new systems and optics for AI networking

Those building blocks include the new G300 as well as the G200 51.2 Tbps chip, which is aimed at spine and aggregation applications, and the G100 25.6 Tbps chip, which is aimed at leaf operations. Expanded portfolio of Silicon One P200-powered systems Cisco in October rolled out the P200 Silicon One chip and the high-end, 51.2 Tbps 8223 router aimed at distributed AI workloads. That system supports Octal Small Form-Factor Pluggable (OSFP) and Quad Small Form-Factor Pluggable Double Density (QSFP-DD) optical form factors that help the box support geographically dispersed AI clusters. Cisco grew the G200 family this week with the addition of the 8122X-64EF-O, a 64x800G switch that will run the SONiC OS and includes support for Cisco 800G Linear Pluggable Optics (LPO) connectivity. LPO components typically set up direct links between fiber optic modules, eliminating the need for traditional components such as a digital signal processor. Cisco said its P200 systems running IOS XR software now better support core routing services to allow data-center-to-data-center links and data center interconnect applications. In addition, Cisco introduced a P200-powered 88-LC2-36EF-M line card, which delivers 28.8T of capacity. “Available for both our 8-slot and 18-slot modular systems, this line card enables up to an unprecedented 518.4T of total system bandwidth, the highest in the industry,” wrote Guru Shenoy, senior vice president of the Cisco provider connectivity group, in a blog post about the news. “When paired with Cisco 800G ZR/ZR+ coherent pluggable optics, these systems can easily connect sites over 1,000 kilometers apart, providing the high-density performance needed for modern data center interconnects and core routing.”

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NetBox Labs ships AI copilot designed for network engineers, not developers

Natural language for network engineers Beevers explained that network operations teams face two fundamental barriers to automation. First, they lack accurate data about their infrastructure. Second, they aren’t software developers and shouldn’t have to become them. “These are not software developers. They are network engineers or IT infrastructure engineers,” Beevers said. “The big realization for us through the copilot journey is they will never be software developers. Let’s stop trying to make them be. Let’s let these computers that are really good at being software developers do that, and let’s let the network engineers or the data center engineers be really good at what they’re really good at.”  That vision drove the development of NetBox Copilot’s natural language interface and its capabilities. Grounding AI in infrastructure reality The challenge with deploying AI  in network operations is trust. Generic large language models hallucinate, produce inconsistent results, and lack the operational context to make reliable decisions. NetBox Copilot addresses this by grounding the AI agent in NetBox’s comprehensive infrastructure data model. NetBox serves as the system of record for network and infrastructure teams, maintaining a semantic map of devices, connections, IP addressing, rack layouts, power distribution and the relationships between these elements. Copilot has native awareness of this data structure and the context it provides. This enables queries that would be difficult or impossible with traditional interfaces. Network engineers can ask “Which devices are missing IP addresses?” to validate data completeness, “Who changed this prefix last week?” for change tracking and compliance, or “What depends on this switch?” for impact analysis before maintenance windows.

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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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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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