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Mobile demands spur enterprise Wi-Fi upgrades

Performance requirements (reduced latency, jitter, packet drops): 67.1% Increased bandwidth consumption: 59.9% User mobility (roaming, broader coverage): 53.3% Connectivity for operational technology (industrial systems, medical imaging, video surveillance): 50.0% Return-to-office policies driving up office occupancy: 48.7% Density requirements (users congregating): 44.7% End-of-life network equipment: 40.8% Need for location-based services: 40.1% “End-of-life equipment is not the […]

  • Performance requirements (reduced latency, jitter, packet drops): 67.1%
  • Increased bandwidth consumption: 59.9%
  • User mobility (roaming, broader coverage): 53.3%
  • Connectivity for operational technology (industrial systems, medical imaging, video surveillance): 50.0%
  • Return-to-office policies driving up office occupancy: 48.7%
  • Density requirements (users congregating): 44.7%
  • End-of-life network equipment: 40.8%
  • Need for location-based services: 40.1%

“End-of-life equipment is not the huge driver you’d think,” McGillicuddy said. Instead, he said the research shows that the upgrades are driven by fundamental changes in how networks are being used.

Among the trends that are reshaping Wi-Fi requirements is hybrid work—managing both remote and on-premises access creates complexity. In addition, collaborative space usage and a shift from assigned desks has led to employees working from myriad building locations, requiring enterprises to rethink network coverage and roaming capabilities.

The applications and devices in use today are also impacting Wi-Fi design choices. Bandwidth-intensive applications, such as real-time video and collaboration, are highly sensitive to network conditions. And employees are connecting not only laptops but also smartphones, wearables, and other Wi-Fi-enabled devices, which can increase concurrent connections and coverage demands.

Unified network access and security

On the security front, enterprises are prioritizing unified solutions for on-premises and remote access, focusing on stronger, more flexible security to support zero-trust environments, according to EMA.

“Security is always top of mind for networking teams,” McGillicuddy said. “Despite the fact that it’s the cybersecurity team that gets all the credit for security, the enterprise network team is often responsible for rolling out a secure infrastructure.”

Hybrid work has revealed that organizations often manage on-premises access and remote access through separate, siloed technologies, according to McGillicuddy. The research found that 100% of IT professionals surveyed want a unified platform for both. EMA survey respondents shared that they believe the benefits of universal network access management are:

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Mobile demands spur enterprise Wi-Fi upgrades

Performance requirements (reduced latency, jitter, packet drops): 67.1% Increased bandwidth consumption: 59.9% User mobility (roaming, broader coverage): 53.3% Connectivity for operational technology (industrial systems, medical imaging, video surveillance): 50.0% Return-to-office policies driving up office occupancy: 48.7% Density requirements (users congregating): 44.7% End-of-life network equipment: 40.8% Need for location-based services: 40.1%

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Anthropic signs billion-dollar deal with Google Cloud

US-based AI company Anthropic has signed a major deal with Google Cloud that is said to be worth tens of billions of dollars. As part of the deal, Anthropic will have access to up to one million of Google’s purpose-built Tensor Processing Unit (TPU) AI accelerators. “Anthropic and Google have

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US electric utilities entering investment ‘super cycle,’ says Morningstar DBRS

U.S. electric utilities are entering a five-year capital expenditure “super-cycle” as they build out transmission and generation networks to meet new demand from data centers, Morningstar DBRS said in a Monday research note. “Investment in electricity infrastructure is projected to be $1.4 trillion from 2025 to 2030, double the amount invested in the prior 10 years,” the firm said. And based on data from the North American Electric Reliability Corp., Morningstar said many regions can expect load growth to increase from previously estimated 6.1% to around 11.6% over the next decade. “The challenges posed by the rapid buildout of data centers are overlaid on existing concerns for most utilities, including decarbonization and guaranteeing the reliability of grid infrastructure while increasing the contribution of renewable power,” Morningstar said. “The projected surge in demand provides opportunities for utilities that must be counterbalanced with structural changes and regulatory support for utilities and rate payers.” “We anticipate that regulated utilities with supportive regulatory commissions, solid credit ratings, and access to capital markets will deploy the needed capex to take advantage of the data center boom,” Bukola Folashakin, Morningstar assistant vice president of corporate ratings, said in a statement. “We expect this capex investment in turn to make such utility locations attractive for more data center construction, potentially creating a cycle of increased revenue for as long as data centers remain economically viable.” Some states — Morningstar named California, Texas, and Louisiana — will see elevated risks of resource inadequacy next year that “in extreme conditions, could trigger electricity shortfalls,” according to the note. Morningstar’s analysis mirror’s recent capital expenditure estimates from the Edison Electric Institute, which expects U.S electricity generation to grow “for the foreseeable future.” The group, which represents investor-owned utilities, said generation rose 3% in 2024 and generation investments as a share of

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Residential electricity prices up more than 6% in August: EIA

Dive Brief: The retail price of electricity for residential customers was up 6.1% in August over the same month last year, reaching an average of 17.62 cents/kWh, according to the U.S. Energy Information Administration’s monthly update on electricity released Friday.  Total net generation and retail sales were down slightly, by 0.8% and 0.5% respectively, which experts attributed to a mild summer in much of the eastern part of the country. Nationally, there were 9.1% fewer cooling days this August compared to August 2024, though parts of the West saw between 5% and 50% more.  Natural gas prices were up 47.4% to just over $3/MMBtu, per Henry Hub, and natural gas consumption fell 5.6%.  Dive Insight: Aaron Denman, who heads Bain & Company’s Americas utilities and renewables practice, said the reasons behind the rise in prices are complicated and nuanced, and vary depending on region. “I think if you look at aggregate headline numbers, it’s hard to blame data centers for much of the increase, and I think part of that is just because it’s still such a small percentage of the overall load,” Denman said. “But I think when you get into specific regions, they’re so large, they’re so meaningful, that you can start to see some of that impact.” He said Bain’s projections put data centers at about 40% to 60% of new load growth in the coming years, with manufacturing and electrification making up most of the remainder. He said the longterm fundamentals remain strong for load growth, despite some recent negative economic data. U.S. factory activity shrank in September for a seventh consecutive month, according to Bloomberg. “This [much] load growth, this fast, is going to put upward pressure on residential prices,” Denman said. “We’re going to need to see creative solutions to minimize the impact on particularly residential

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EIA Shows Production Has Outweighed Demand All Year

In its latest short term energy outlook (STEO), which was released on October 7, the U.S. Energy Information Administration (EIA) showed that world petroleum and other liquid fuels production outweighed consumption in the first, second, and third quarters of this year. According to the STEO, in the third quarter, production averaged 107.43 million barrels per day and consumption averaged 104.83 million barrels per day. In the second quarter, production came in at 105.06 million barrels per day and consumption was 104.05 million barrels per day, and in the first quarter, production averaged 103.62 million barrels per day and consumption was 102.33 million barrels per day, the STEO highlighted. The last time consumption came in higher than demand was in the third quarter of 2024, according to the STEO, which showed that, in that quarter, production averaged 103.09 million barrels per day and consumption averaged 103.45 million barrels per day. In the first quarter of last year, production was 102.60 million barrels per day and consumption was 101.79 million barrels per day, in the second quarter of 2024 production was 103.23 million barrels per day and consumption was 102.93 million barrels per day, and in the fourth quarter of last year production was 103.83 million barrels per day and consumption was 103.46 million barrels per day, the STEO showed. Looking ahead, the STEO projected that production will average 107.31 million barrels per day in the fourth quarter of this year. The EIA forecast in the STEO that consumption will come in at 104.72 million barrels per day in the fourth quarter. In its latest STEO, the EIA projected that production will average 106.39 million barrels per day in the first quarter of next year, 106.97 million barrels per day in the second quarter, 107.55 million barrels per day in the third

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IEA Boss Says Oil Glut Will ‘Moderate’ Prices After Recent Gains

Oil prices are expected to “moderate” because of ample supply, according to the International Energy Agency.  “I don’t expect a major shake-up in the oil markets thanks to growing production coming from the Americas,” OPEC+’s change in policy to increase output and slowing demand growth, IEA Executive Director Fatih Birol said in an interview with Jennifer Zabasajja on Bloomberg Television. “As a result of all these trends I expect moderate oil prices in the next days and weeks to come.” Speculation that the US and China will reach a trade deal this week will only provide a “slight boost” to oil prices, barring any other major geopolitical events, he said.  The oil market will be in surplus as output from the “American quintet” — the US, Canada, Brazil, Guyana and Argentina — outpaces the growth in demand, largely driven by China’s pivot away from heavy industry and combustion vehicles, Birol said. The IEA raised its estimate for a record oil glut in 2026 earlier this month.  Crude prices jumped almost 8% last week after fresh US sanctions on Russia’s biggest producers triggered concerns over physical flows. Refiners in India, a major market for Russian oil, said they’d stop buying while some in China also hit the panic button. 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 or insulting comments will be removed.

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Wind PPA prices rising faster than solar under Trump administration

Dive Brief: Solar power purchase agreement prices in North America rose 4% from the second to third quarter of 2025, while wind prices rose nearly 5%, according to data from the LevelTen Energy PPA marketplace. Wind PPAs have increased nearly 14% since last year. Market analysts disagree about which specific policies have driven the increase in costs. LevelTen Energy attributes the rise to tariffs and permitting challenges, while energy transition firm Trio blames financing costs. Both say demand growth has played a role. Additional rounds of tariffs announced by the Trump administration could increase PPA costs by another 10% to 15%, according to Joey Lange, senior managing director for clean energy supply at Trio. Dive Insight: With multiple policies poised to increase energy costs, it’s unclear exactly which factors are driving up PPA prices. Wind PPAs have seen the greatest price hikes since the election of President Donald Trump, rising a little over $9/MWh since the third quarter of 2024, according to LevelTen Energy. The average solar PPA costs $3.19/MWh more than it did this time last year. Developers of both resources have reported to LevelTen Energy that they’ve sidelined projects they don’t believe will make the deadline for federal tax incentives under the One Big Beautiful Bill Act, according to Rob Collier, vice president of the LevelTen Energy marketplace. That has reduced the number of clean energy projects on the market, even as many large buyers have sped up their procurement ahead of those same OBBBA deadlines, Collier said. Wind projects face additional price pressure from newly restrictive federal permitting policies, Collier said. Wind is also seen as more desirable by corporate procurement teams looking to meet 24-7 clean energy goals, according to Lange. But tariffs have had the biggest cost impact to date, Collier said. “What we’re hearing from

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Surging load growth requires flexibility, new approaches: FERC’s See

In the face of surging load growth forecasts, Lindsay See, a Federal Energy Regulatory Commission commissioner, called for flexibility and new approaches to grid development during a meeting held Thursday by WIRES Group, a transmission trade group. “I … never want to be the person who is saying no to something just because we haven’t done it before,” See said. “I think there’s an onus on all of us in the sector to make sure that we are being nimble and are open to new solutions.” In the last year, FERC has received innovative proposals for speeding grid interconnections for proposed generating facilities, See noted. “When we are looking at those proposals — speaking for myself, but also the conversations I’ve had with my colleagues — we are really looking for ways that we can apply those predictable standards in our statutes, but that allow this kind of nimbleness and creativity moving forward, because I think it is going to require not being static in terms of the approaches that we’ve used before in order to meet the urgency of this moment,” she said. While FERC is guided by statutes to set fair and predictable rules, “there’s a pretty broad range, in my view, of what ‘just and reasonable’ can be, especially when we have new situations and urgency,” See said. FERC uses a “just and reasonable” standard when it sets electric rates. See said she was cautious about prescriptive rulemakings in a time of rapid change. “I don’t want to be the one who is stifling innovation and new changes that we’re seeing happen,” See said. “I really approach that as trying to be in listening mode a lot to figure out where would guidance and uniformity be helpful for the industry … and where is it potentially a hindrance.”

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Intel sees supply shortage, will prioritize data center technology

“Capacity constraints, especially on Intel 10 and Intel 7 [Intel’s semiconductor manufacturing process], limited our ability to fully meet demand in Q3 for both data center and client products,” said Zinsner, adding that Intel isn’t about to add capacity to Intel 10 and 7 when it has moved beyond those nodes. “Given the current tight capacity environment, which we expect to persist into 2026, we are working closely with customers to maximize our available output, including adjusting pricing and mix to shift demand towards products where we have supply and they have demand,” said Zinsner. For that reason, Zinzner projects that the fourth quarter will be roughly flat versus the third quarter in terms of revenue. “We expect Intel products up modestly sequentially but below customer demand as we continue to navigate supply environment,” said Zinsner. “We expect CCG to be down modestly and PC AI to be up strongly sequentially as we prioritize wafer capacity for server shipments over entry-level client parts.”

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How to set up an AI data center in 90 days

“Personally, I think that a brownfield is very creative way to deal with what I think is the biggest problem that we’ve got right now, which is time and speed to market,” he said. “On a brownfield, I can go into a building that’s already got power coming into the building. Sometimes they’ve already got chiller plants, like what we’ve got with the building I’m in right now.” Patmos certainly made the most of the liquid facilities in the old printing press building. The facility is built to handle anywhere from 50 to over 140 kilowatts per cabinet, a leap far beyond the 1–2 kW densities typical of legacy data centers. The chips used in the servers are Nvidia’s Grace Blackwell processors, which run extraordinarily hot. To manage this heat load, Patmos employs a multi-loop liquid cooling system. The design separates water sources into distinct, closed loops, each serving a specific function and ensuring that municipal water never directly contacts sensitive IT equipment. “We have five different, completely separated water loops in this building,” said Morgan. “The cooling tower uses city water for evaporation, but that water never mixes with the closed loops serving the data hall. Everything is designed to maximize efficiency and protect the hardware.” The building taps into Kansas City’s district chilled water supply, which is sourced from a nearby utility plant. This provides the primary cooling resource for the facility. Inside the data center, a dedicated loop circulates a specialized glycol-based fluid, filtered to extremely low micron levels and formulated to be electronically safe. Heat exchangers transfer heat from the data hall fluid to the district chilled water, keeping the two fluids separate and preventing corrosion or contamination. Liquid-to-chip and rear-door heat exchangers are used for immediate heat removal.

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INNIO and VoltaGrid: Landmark 2.3 GW Modular Power Deal Signals New Phase for AI Data Centers

Why This Project Marks a Landmark Shift The deployment of 2.3 GW of modular generation represents utility-scale capacity, but what makes it distinct is the delivery model. Instead of a centralized plant, the project uses modular gas-reciprocating “power packs” that can be phased in step with data-hall readiness. This approach allows staged energization and limits the bottlenecks that often stall AI campuses as they outgrow grid timelines or wait in interconnection queues. AI training loads fluctuate sharply, placing exceptional stress on grid stability and voltage quality. The INNIO/VoltaGrid platform was engineered specifically for these GPU-driven dynamics, emphasizing high transient performance (rapid load acceptance) and grid-grade power quality, all without dependence on batteries. Each power pack is also designed for maximum permitting efficiency and sustainability. Compared with diesel generation, modern gas-reciprocating systems materially reduce both criteria pollutants and CO₂ emissions. VoltaGrid markets the configuration as near-zero criteria air emissions and hydrogen-ready, extending allowable runtimes under air permits and making “prime-as-a-service” viable even in constrained or non-attainment markets. 2025: Momentum for Modular Prime Power INNIO has spent 2025 positioning its Jenbacher platform as a next-generation power solution for data centers: combining fast start, high transient performance, and lower emissions compared with diesel. While the 3 MW J620 fast-start lineage dates back to 2019, this year the company sharpened its data center narrative and booked grid stability and peaking projects in markets where rapid data center growth is stressing local grids. This momentum was exemplified by an 80 MW deployment in Indonesia announced earlier in October. The same year saw surging AI-driven demand and INNIO’s growing push into North American data-center markets. Specifications for the 2.3 GW VoltaGrid package highlight the platform’s heat tolerance, efficiency, and transient response, all key attributes for powering modern AI campuses. VoltaGrid’s 2025 Milestones VoltaGrid’s announcements across 2025 reflect

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Inside Google’s multi-architecture revolution: Axion Arm joins x86 in production clusters

Matt Kimball, VP and principal analyst with Moor Insights and Strategy, pointed out that AWS and Microsoft have already moved many workloads from x86 to internally designed Arm-based servers. He noted that, when Arm first hit the hyperscale datacenter market, the architecture was used to support more lightweight, cloud-native workloads with an interpretive layer where architectural affinity was “non-existent.” But now there’s much more focus on architecture, and compatibility issues “largely go away” as Arm servers support more and more workloads. “In parallel, we’ve seen CSPs expand their designs to support both scale out (cloud-native) and traditional scale up workloads effectively,” said Kimball. Simply put, CSPs are looking to monetize chip investments, and this migration signals that Google has found its performance-per-dollar (and likely performance-per-watt) better on Axion than x86. Google will likely continue to expand its Arm footprint as it evolves its Axion chip; as a reference point, Kimball pointed to AWS Graviton, which didn’t really support “scale up” performance until its v3 or v4 chip. Arm is coming to enterprise data centers too When looking at architectures, enterprise CIOs should ask themselves questions such as what instance do they use for cloud workloads, and what servers do they deploy in their data center, Kimball noted. “I think there is a lot less concern about putting my workloads on an Arm-based instance on Google Cloud, a little more hesitance to deploy those Arm servers in my datacenter,” he said. But ultimately, he said, “Arm is coming to the enterprise datacenter as a compute platform, and Nvidia will help usher this in.” Info-Tech’s Jain agreed that Nvidia is the “biggest cheerleader” for Arm-based architecture, and Arm is increasingly moving from niche and mobile use to general-purpose and AI workload execution.

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AMD Scales the AI Factory: 6 GW OpenAI Deal, Korean HBM Push, and Helios Debut

What 6 GW of GPUs Really Means The 6 GW of accelerator load envisioned under the OpenAI–AMD partnership will be distributed across multiple hyperscale AI factory campuses. If OpenAI begins with 1 GW of deployment in 2026, subsequent phases will likely be spread regionally to balance supply chains, latency zones, and power procurement risk. Importantly, this represents entirely new investment in both power infrastructure and GPU capacity. OpenAI and its partners have already outlined multi-GW ambitions under the broader Stargate program; this new initiative adds another major tranche to that roadmap. Designing for the AI Factory Era These upcoming facilities are being purpose-built for next-generation AI factories, where MI450-class clusters could drive rack densities exceeding 100 kW. That level of compute concentration makes advanced power and cooling architectures mandatory, not optional. Expected solutions include: Warm-water liquid cooling (manifold, rear-door, and CDU variants) as standard practice. Facility-scale water loops and heat-reuse systems—including potential district-heating partnerships where feasible. Medium-voltage distribution within buildings, emphasizing busway-first designs and expanded fault-current engineering. While AMD has not yet disclosed thermal design power (TDP) specifications for the MI450, a 1 GW campus target implies tens of thousands of accelerators. That scale assumes liquid cooling, ultra-dense racks, and minimal network latency footprints, pushing architectures decisively toward an “AI-first” orientation. Design considerations for these AI factories will likely include: Liquid-to-liquid cooling plants engineered for step-function capacity adders (200–400 MW blocks). Optics-friendly white space layouts with short-reach topologies, fiber raceways, and aisles optimized for module swaps. Substation adjacency and on-site generation envelopes negotiated during early land-banking phases. Networking, Memory, and Power Integration As compute density scales, networking and memory bottlenecks will define infrastructure design. Expect fat-tree and dragonfly network topologies, 800 G–1.6 T interconnects, and aggressive optical-module roadmaps to minimize collective-operation latency, aligning with recent disclosures from major networking vendors.

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Study Finds $4B in Data Center Grid Costs Shifted to Consumers Across PJM Region

In a new report spanning 2022 through 2024, the Union of Concerned Scientists (UCS) identifies a significant regulatory gap in the PJM Interconnection’s planning and rate-making process—one that allows most high-voltage (“transmission-level”) interconnection costs for large, especially AI-scale, data centers to be socialized across all utility customers. The result, UCS argues, is a multi-billion-dollar pass-through that is poised to grow as more data center projects move forward, because these assets are routinely classified as ordinary transmission infrastructure rather than customer-specific hookups. According to the report, between 2022 and 2024, utilities initiated more than 150 local transmission projects across seven PJM states specifically to serve data center connections. In 2024 alone, 130 projects were approved with total costs of approximately $4.36 billion. Virginia accounted for nearly half that total—just under $2 billion—followed by Ohio ($1.3 billion) and Pennsylvania ($492 million) in data-center-related interconnection spending. Yet only six of those 130 projects, about 5 percent, were reported as directly paid for by the requesting customer. The remaining 95 percent, representing more than $4 billion in 2024 connection costs, were rolled into general transmission charges and ultimately recovered from all retail ratepayers. How Does This Happen? When data center project costs are discussed, the focus is usually on the price of the power consumed, or megawatts multiplied by rate. What the UCS report isolates, however, is something different: the cost of physically delivering that power: the substations, transmission lines, and related infrastructure needed to connect hyperscale facilities to the grid. So why aren’t these substantial consumer-borne costs more visible? The report identifies several structural reasons for what effectively functions as a regulatory loophole in how development expenses are reported and allocated: Jurisdictional split. High-voltage facilities fall under the Federal Energy Regulatory Commission (FERC), while retail electricity rates are governed by state public utility

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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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