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Nvidia’s Nemotron Model Families will advance AI agents

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Nvidia announced Nemotron Model Families to advance agentic AI as part of its bevy of AI announcements at CES 2025 today. Available as Nvidia NIM microservices, open Llama Nemotron large language models and Cosmos Nemotron vision […]

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Nvidia announced Nemotron Model Families to advance agentic AI as part of its bevy of AI announcements at CES 2025 today.

Available as Nvidia NIM microservices, open Llama Nemotron large language models and Cosmos Nemotron vision language models can supercharge AI agents on any accelerated system.

Artificial intelligence is entering a new era — agentic AI — where teams of specialized agents can help people solve complex problems and automate repetitive tasks. Nvidia made the announcement as part of Nvidia CEO Jensen Huang’s opening keynote today at CES 2025.

With custom AI agents, enterprises across industries can manufacture intelligence and achieve unprecedented productivity. These advanced AI agents require a system of multiple generative AI models optimized for agentic AI functions and capabilities. This complexity means that the need for powerful, efficient, enterprise-grade models has never been greater.

“AI agents is the next robotic industry and likely to be a multibillion-dollar opportunity,” Huang said.

To provide a foundation for enterprise agentic AI, Nvidia today announced the Llama Nemotron family of open large language models (LLMs). Built with Llama, the models can help developers create and deploy AI agents across a range of applications —- including customer support, fraud detection, and product supply chain and inventory management optimization.

To be effective, many AI agents need both language skills and the ability to perceive the world and respond with the appropriate action.

Nvidia Nemotron
Nvidia Nemotron

With new Nvidia Cosmos Nemotron vision language models (VLMs) and Nvidia NIM microservices for video search and summarization, developers can build agents that analyze and respond to images and video from autonomous machines, hospitals, stores and warehouses, as well as sports events, movies and news. For developers seeking to generate physics-aware videos for robotics and autonomous vehicles, Nvidia today separately announced Nvidia Cosmos world foundation models.

Open Llama Nemotron Models Optimize Compute Efficiency, Accuracy for AI Agents Built with Llama foundation models — one of the most popular commercially viable open source model collections, downloaded over 650 million times — Nvidia Llama Nemotron models provide optimized building blocks for AI agent development.

Llama Nemotron models are pruned and trained with Nvidia’s latest techniques and high-quality datasets for enhanced agentic capabilities. They excel at instruction following, chat, function calling, coding and math, while being size-optimized to run on a broad range of Nvidia accelerated computing resources.

“Agentic AI is the next frontier of AI development, and delivering on this opportunity requires full-stack optimization across a system of LLMs to deliver efficient, accurate AI agents,” said Ahmad Al-Dahel, vice president and head of GenAI at Meta, in a statement. “Through our collaboration with Nvidia and our shared commitment to open models, the Nvidia Llama Nemotron family built on Llama can help enterprises quickly create their own custom AI agents.”

Leading AI agent platform providers including SAP and ServiceNow are expected to be among the first to use the new Llama Nemotron models.

“AI agents that collaborate to solve complex tasks across multiple lines of the business will unlock a whole new level of enterprise productivity beyond today’s generative AI scenarios,” said Philipp Herzig, chief AI officer at SAP, in a statement. “Through SAP’s Joule, hundreds of millions enterprise users will interact with these agents to accomplish their goals faster than ever before. Nvidia’s new open Llama Nemotron model family will foster the development of multiple specialized AI agents to transform business processes.”

“AI agents make it possible for organizations to achieve more with less effort, setting new standards for business transformation,” said Jeremy Barnes, vice president of platform AI at ServiceNow, in a statement. “The improved performance and accuracy of Nvidia’s open Llama Nemotron models can help build advanced AI agent services that solve complex problems across functions, in any industry.”

The Nvidia Llama Nemotron models use Nvidia NeMo for distilling, pruning and alignment. Using these techniques, the models are small enough to run on a variety of computing platforms while providing high accuracy as well as increased model throughput.

The Llama Nemotron model family will be available as downloadable models and as Nvidia NIM microservices that can be easily deployed on clouds, data centers, PCs and workstations. They offer enterprises industry-leading performance with reliable, secure and seamless integration into their agentic AI application workflows.

Customize and Connect to Business Knowledge With Nvidia NeMo

The Llama Nemotron and Cosmos Nemotron model families are coming in Nano, Super and Ultra sizes to provide options for deploying AI agents at every scale.

● Nano: The most cost-effective model optimized for real-time applications with low latency, ideal for deployment on PCs and edge devices.

● Super: A high-accuracy model offering exceptional throughput on a single GPU.

● Ultra: The highest-accuracy model, designed for data-center-scale applications demanding the highest performance.

Enterprises can also customize the models for their specific use cases and domains with Nvidia NeMo microservices to simplify data curation, accelerate model customization and evaluation, and apply guardrails to keep responses on track.

With Nvidia NeMo Retriever, developers can also integrate retrieval-augmented generation (RAG) capabilities to connect models to their enterprise data.

And using Nvidia Blueprints for agentic AI, enterprises can quickly create their own applications using Nvidia’s advanced AI tools and end-to-end development expertise. In fact, Nvidia Cosmos Nemotron, Nvidia Llama Nemotron and NeMo Retriever supercharge the new Nvidia Blueprint for video search and summarization, announced separately today.

NeMo, NeMo Retriever and Nvidia Blueprints are all available with the Nvidia AI Enterprise software platform.

Availability

Llama Nemotron and Cosmos Nemotron models will be available as hosted APIs and for download on build.nvidia.com and on Hugging Face. Access for development, testing and research is free for members of the Nvidia Developer Program.

Enterprises can run Llama Nemotron and Cosmos Nemotron NIM microservices in production with the Nvidia AI Enterprise software platform on accelerated data center and cloud infrastructure.

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It’s not your model — AI has a data movement problem

But that can be the wrong lever. When you examine the full end-to-end transaction, the model usually isn’t the problem. Take the extraordinary scale of AI traffic as it moves from a branch office to a centralized security stack, then to a cloud region, then to a data-hosted backend somewhere

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Ørsted builds compliance into automation, speeds firewall changes

Taking on a firewall process One process Ørsted initially targeted for automation was firewall rule management. In the past, an internal customer submitted a firewall request through ServiceNow, and a network security engineer reviewed the request, checking IP addresses, fully qualified domain names, and directory groups. Depending on the type,

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OPEC+ warns soaring shipping, insurance costs impede oil flows

Disruptions to international energy flows have pushed shipping and insurance costs to unprecedented levels of more than one-third of commodity value, impeding the movement of crude oil and petroleum products and adding inflationary pressure, OPEC+ ministers said following an Oct. 12 meeting in Riyadh. The ministers met on the sidelines of the 17th International Energy Forum (IEF) ministerial meeting and the 25th WPC Energy Congress to review market conditions. They stressed the need to safeguard international maritime routes. Elevated transportation and insurance costs are being passed through the oil value chain, prolonging the financial burden on producing and consuming countries and weighing on global economic growth, they said. The statement, as reported, did not identify the routes or commodities behind the cost estimate or explain how it was calculated. Separately, Russian Deputy Prime Minister Alexander Novak said costs had risen five- to tenfold on some routes, citing vessel shortages, military risks, and the closure of the Strait of Hormuz. Ministers reaffirmed their commitment to decisions adopted at the June 7, 2026, OPEC and non-OPEC ministerial meeting. The group said consultations with all OPEC+ countries would continue through existing mechanisms, including the Joint Ministerial Monitoring Committee and ministerial meetings. Ministers also said they would monitor the situation and work with governments, industry stakeholders, and international organizations, including the IEF and International Energy Agency (IEA), to improve global shipping conditions.

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Insights: US shale maturity and the future of North American supply

North America’s oil supply outlook is entering a new phase, according to Enverus’ latest long-term analysis. In this Insights episode of the Oil & Gas Journal ReEnterprised podcast, Mikaila Adams, content strategist and managing editor, speaks with Dane Gregoris, managing director at Enverus, and discusses the firm’s conclusion that US shale is “aging, not broken.” While the United States is expected to remain the continent’s dominant producer, Enverus sees growth slowing markedly compared with the past two decades as operators work through increasingly mature inventories and confront geological constraints that are becoming harder to offset through efficiency gains alone. The conversation examines the data behind that assessment, including declining productivity per lateral foot, changing inventory quality, and the methodology Enverus uses to estimate remaining drilling locations across North America’s major basins. Gregoris explains why the firm expects US production to remain relatively stable over the next decade rather than continue the rapid expansion that defined the shale revolution, and why rising marginal supply costs could become an increasingly important market signal. A significant portion of the discussion focuses on the Permian basin, which Enverus still views as the cornerstone of North American oil supply well into the 2040s. At the same time, the report suggests that even the Permian is experiencing the effects of resource maturation. Gregoris discusses evidence that operators are moving down the quality curve and shares his perspective on emerging technologies, including ultra-long laterals, lightweight proppants, and advanced surfactants, that could improve recoveries and alter the industry’s long-term outlook. The report’s second major theme is the growing strategic importance of Canada. As US shale growth moderates, Enverus sees Canada’s oil sands and liquids-rich plays as increasingly important sources of future supply. Gregoris explains why Canada’s resource base offers substantially longer inventory duration than most US plays and

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Energy Secretary Secures Mid-Atlantic Grid Ahead of Anticipated Stressed System Conditions

WASHINGTON—U.S. Secretary of Energy Chris Wright issued an emergency order to mitigate blackout risks in the mid-Atlantic ahead of a period of elevated demand, a high rate of planned generator outages during the autumn maintenance season, and numerous planned transmission outages. The order directs PJM Interconnection, L.L.C. (PJM) to dispatch specified units and to order their operation as needed to maintain reliability and authorizes PJM to direct backup generation resources to operate as a last resort before declaring an Energy Emergency Alert (EEA) 3 or during an EEA 3.  PJM is authorized to call upon its Transmission Owners and Electric Distribution Companies to implement the order as needed. The order was issued pursuant to an application from PJM submitted on October 11, 2026.  “This order will help ensure millions of American families and businesses across the mid-Atlantic have access to affordable, reliable, and secure electricity by making additional power generation, including backup power, available to use as needed,” said U.S. Secretary of Energy Chris Wright. “While past leaders’ energy subtraction policies have made the grid more vulnerable to the risk of blackouts when the sun doesn’t shine or the wind doesn’t blow, this administration remains committed to using every available tool to prevent blackouts.”  DOE estimates more than 35 GW of unused backup generation remains available nationwide.  The order is effective October 13, 2026, through October 16, 2026. 

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Middle East supply risks overshadow Russian diesel deal

Escalating security risks in the Middle East are keeping oil markets on edge, with renewed attacks on Saudi Arabia and commercial vessels near the Strait of Hormuz, raising concerns over regional crude exports. The developments have overshadowed US President Donald Trump’s announcement of additional Russian diesel supplies and a proposed Russia-Ukraine energy ceasefire. Oil prices rose more than 2% on Oct. 12, with Brent climbing to $107/bbl and US West Texas Intermediate (WTI) reaching $93.7/bbl. Both benchmarks hit their highest levels since Sept. 29, reversing earlier losses. The gains followed renewed attacks on Saudi Arabia and commercial shipping in the Gulf region. Yemen’s Iran-aligned Houthi movement claimed responsibility for a Saturday strike on Riyadh’s international airport, while additional attacks were reported Sunday. Separately, a tanker was struck by a drone near Sohar, Oman, and another vessel was damaged while transiting the Strait of Hormuz, according to the United Kingdom Maritime Trade Operations agency (UKMTO). The incidents have renewed concerns over further disruption to shipping through the Strait of Hormuz, threatening the recovery in Middle East crude exports recorded in September. Goldman Sachs raised its December Brent price forecast to $90/bbl from $85/bbl, citing an estimated geopolitical risk premium of slightly more than $20/bbl. “We maintain our base case that continued adaptation of Mideast supply will eventually reduce crude oil prices, while potential renewed escalation still poses significant net upside risk,” Goldman Sachs said in a note Oct. 11. Russian diesel deal, energy ceasefire Trump announced on Oct. 9 an agreement with Russian President Vladimir Putin to increase diesel supplies to the US and international markets. Trump said Russia would initially supply more than 300,000 tonnes of diesel, followed by 500,000 tonnes in November and 1 million tonnes thereafter. The US Treasury Department also authorized certain Russian diesel transactions under a

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Energy Department Authorizes Strategic Petroleum Reserve Exchange to Address Supply Disruptions Due to Hurricane

WASHINGTON—The U.S. Department of Energy (DOE) today announced the authorization of an emergency exchange of up to 4 million barrels of crude oil from the Strategic Petroleum Reserve (SPR) to address supply disruptions due to inclement weather in the Gulf of America. Under the terms of the exchanges, participating companies will return the borrowed crude oil with additional premium barrels in 2027, helping replenish and strengthen the SPR at no additional cost to taxpayers.  “With this emergency exchange, the Energy Department is acting swiftly to help maintain refinery operations, limit disruptions to fuel supplies, and ensure American families and businesses continue to have access to affordable, reliable, and secure energy” said U.S. Secretary of Energy Chris Wright. “In addition to helping minimize supply disruptions, these emergency exchanges will also require Exxon and BP to return more barrels to the Reserve than are currently being withdrawn, saving taxpayers millions of dollars. Rest assured, the Trump Administration is committed to strengthening America’s energy security at every opportunity.” The Department has authorized exchanges of up to 2 million barrels each for ExxonMobil and BP America. ExxonMobil’s exchange will accelerate deliveries of previously awarded SPR crude oil to address immediate supply needs.  DOE will continue working with industry partners to support reliable fuel supplies and respond to hurricane-related disruptions.  For more information about the Strategic Petroleum Reserve, visit energy.gov.

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Energy Department Supports FERC’s Call for PJM to Protect Ratepayers and Build More Reliable Power

WASHINGTON—The U.S. Department of Energy (DOE) announced its support for the Federal Energy Regulatory Commission’s (FERC) guidance that would help ensure lower electricity costs for American families and businesses across the PJM Interconnection LLC’s (PJM) region spanning across the mid-Atlantic. DOE filed a Notice of Intervention and Statement of Position with FERC supporting its recommendation for PJM’s proposed Reliability Backstop Procurement. FERC recommends PJM submit revised tariff provisions to implement appropriate cost allocation and other reforms. FERC’s recommendations are consistent with President Trump’s Ratepayer Protection Pledge, ensuring large electricity users pay for the generation and infrastructure needed to serve them.  This action follows the Trump Administration’s call in January 2026 for PJM to adopt market rules to strengthen grid reliability and reduce electricity costs. Specifically, the Administration asked PJM to hold an emergency power auction and to accelerate the development of reliable power generation. The Trump administration was joined by governors from all 13 states who participate in the PJM grid. “The Trump Administration remains committed to doing everything it can to lower electricity costs, grow the supply of American energy and strengthen grid reliability,” said U.S. Secretary of Energy Chris Wright. “That’s why President Trump created the Ratepayer Protection Pledge, and the Energy Department supports having large electricity users pay for reliable new power generation.” “In January, the Trump Administration recognized early warning signs of capacity shortfalls in PJM and joined the Governors of all 13 PJM states in issuing a Statement of Principles to PJM, calling for PJM to adopt market rules to strengthen grid reliability and reduce electricity costs for American families and businesses,” said U.S. Deputy Secretary of Energy James P. Danly. “By increasing transparency and preventing unjust cost shifts onto existing customers, the proposed reforms advance President Trump’s Ratepayer Protection Pledge while ensuring Americans continue

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AMD unveils Helion as agentic AI fuels demand for data center CPUs

AMD has introduced Helion, an open blueprint for data center racks that aims to give CPUs a larger role in running AI agents while allowing customers to configure GPU resources around their inference requirements. Based on Open Compute Project (OCP) specifications, the architecture supports different combinations of computing hardware. AMD cited examples including CPU-only racks for hyperscalers, powered by sixth-generation EPYC processors with up to 32,768 cores, and all-in-one enterprise racks accommodating up to 16 Instinct MI350P GPUs. AMD has listed networking bandwidth of up to 102 Tbps for Helion, although the company has not specified how that figure is calculated. The specification represents a planned rack capability rather than demonstrated performance in customer environments.

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Land & Expand: North America’s Data Center Pipeline Expands Under Pressure

Land & Expand is Data Center Frontier’s periodic look at the latest data center development news, including new sites, land acquisitions and campus expansions across North America. This latest installment finds the development pipeline continuing to expand, even as the requirements for bringing large-scale projects online grow more complicated. Developers are securing land, planning new power infrastructure and advancing campuses measured in hundreds of megawatts or more. At the same time, local governments and residents are demanding greater clarity on electricity costs, water consumption, noise, tax incentives and the long-term effects of industrial-scale computing facilities. A succession of development disclosures and project milestones through September and early October 2026 illustrates both the geographical reach of North America’s expanding data center pipeline and the growing difficulty of measuring how much proposed capacity will ultimately be delivered. The projects range from preliminary discussions and newly secured development sites to campuses already under construction. Some are advancing through formal permitting and power studies; others remain contingent on customers, financing or local approvals. Together, they reveal an industry still expanding aggressively, but operating under increasingly complex development conditions. Fluidstack: Cameron County, Texas — Up to 1.5 GW One of the largest newly disclosed projects is Fluidstack’s AI data center development in Cameron County in the Rio Grande Valley. The project surfaced publicly September 10 when Cameron County announced that it had issued Fluidstack a worksite permit for property near Harlingen. The permit authorizes preliminary site work, including grading, utilities and related infrastructure, rather than construction of the data center buildings themselves. Fluidstack subsequently disclosed considerably more detail on September 21, saying construction had begun on a $4 billion first phase capable of supporting as much as 1.5 GW. Fluidstack expects the project to generate more than 2,500 construction jobs and several hundred permanent positions. 

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DCF Global: Five Markets Redrawing the AI Infrastructure Map

The Global Constraint Is Execution These five markets demonstrate that the worldwide AI infrastructure buildout is no longer organized around a single development model. Spain is using permitting reform to attract investment. China is concentrating construction around energy resources. India is translating enormous capital commitments into an expanding development pipeline. Latin America is combining hyperscale growth with national industrial objectives. And Southeast Asia is creating interconnected infrastructure markets whose boundaries increasingly extend beyond individual cities and countries. Not every market is competing for the same business. Sovereign cloud services, enterprise applications, AI training clusters, and large-scale inference platforms carry different requirements involving power, connectivity, latency, data residency, and operating economics. But the infrastructure questions remain remarkably consistent. Can a project obtain enough electricity? Can transmission and supporting networks be delivered on schedule? Will the supply chain provide the required equipment? Can the facility be constructed and commissioned efficiently? And will the development retain the regulatory certainty and community acceptance required to operate for decades? The gap between announced development and actual capacity is becoming a defining measurement of the industry. Cushman & Wakefield estimates that Asia-Pacific alone had approximately 26.5 GW of data center capacity in its development pipeline during H1 2026. Of that total, roughly 4.8 GW was under construction, with another 21.7 GW in planning. Those figures reveal both the extraordinary scale of the opportunity and the considerable infrastructure work still required to realize it. What the Global Buildout Means for North America For U.S. data center operators, developers, engineering firms, equipment suppliers, and investors, international expansion is not a separate story. It is increasingly part of the same global competition for capital, equipment, power infrastructure, and specialized expertise. The transformers, switchgear, generators, advanced cooling systems, fiber networks, and electrical distribution equipment required by a major AI campus

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Bidding war over key component could eliminate third hard disk maker

What if the three remaining hard disk manufacturers became two? Seagate Technology and Western Digital control 90% of the market, according to market researcher TrendForce, with Toshiba picking up the crumbs. Seagate and WD both make their own magnetic drive heads, but Toshiba relies on a third party, TDK, which also sells to Seagate and WD when they need extra capacity. Seeking to guarantee supplies of this critical component, Toshiba made a bid for TDK’s drive head business earlier this year, according to Bloomberg. Concerned that this could affect its ability to meet the growing demand for hard disks from AI data centers, Seagate made a counteroffer, Bloomberg reported. TDK is staying mum.

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Oracle reportedly lands $7B GPU deal for Tencent

Oracle has reportedly signed a five-year, $7 billion agreement to provide Chinese technology conglomerate Tencent with access to roughly 100,000 advanced AI accelerators deployed in Oracle data centers across Southeast Asia, helping Tencent to sidestep restrictions on advanced AI equipment.  The deal, first reported by the Financial Times, would represent Tencent’s largest overseas cloud commitment with a U.S. provider. Neither Oracle nor Tencent has publicly confirmed the agreement or disclosed the specific AI processors involved. Under the reported terms, Tencent would pay about 30% of the contract value upfront—roughly $2.1 billion—with the remainder paid over the five-year term. That would give Oracle a substantial source of upfront funding for the expensive data center infrastructure required to build out the infrastructure.

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NVIDIA’s DSX Ready Brings Power and Cooling Into the AI Factory Blueprint

NVIDIA is extending its influence over AI infrastructure beyond the GPU, server rack and network, introducing qualification requirements for the power and cooling systems that increasingly determine the scale and performance of AI data centers. The company’s new NVIDIA DSX Ready program, announced September 21, establishes requirements for specific infrastructure products intended for use with NVIDIA’s DSX AI factory reference designs. Its first two categories—battery energy storage systems (BESS) and coolant distribution units (CDUs)—address two of the most pressing engineering challenges in AI infrastructure: managing rapidly changing electrical demand and removing heat from increasingly dense computing systems. The initial qualified suppliers are Hitachi Energy, LG Energy Solution and Tesla for battery storage, and LG Electronics, LiquidStack and Vertiv for liquid cooling. While the announcement might initially resemble another NVIDIA partner program, its technical details suggest something more consequential. The company is establishing performance criteria for the electrical and mechanical equipment supporting its computing platforms, connecting those requirements to an expanding ecosystem of qualified suppliers. Subsequent partner announcements offer a clearer view of what that means in practice. They describe battery systems designed to respond to AI load fluctuations, coolant distribution equipment operating at multi-megawatt capacities, and integrated cooling architectures intended to make more of a data center’s available power usable for computing. The initiative also coincides with the arrival of Chris Malone, formerly a data center infrastructure executive at OpenAI, Meta and Google, as NVIDIA’s vice president of the DSX Platform. Together, the developments point toward a closer relationship between computing architecture and facility engineering, with NVIDIA seeking to influence not only the processors deployed in AI factories but the infrastructure requirements that support their operation. From Reference Design to Infrastructure Qualification DSX Ready is an extension of the broader NVIDIA DSX AI Factory Platform, introduced in May 2026. As

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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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