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Outdated billing systems are holding back the energy transition

Across the US, utilities are making significant advancements in the energy transition, one such being electrification: switching end-use devices like heating systems and vehicles away from fossil fuels and onto electric fuel. Because electrification – and the associated demand increase – could increase system costs if demand is left unmanaged, a subsequent trend has emerged: […]

Across the US, utilities are making significant advancements in the energy transition, one such being electrification: switching end-use devices like heating systems and vehicles away from fossil fuels and onto electric fuel. Because electrification – and the associated demand increase – could increase system costs if demand is left unmanaged, a subsequent trend has emerged: demand management at the grid-edge. Utilities are investing in new solutions to serve customer demand (particularly from new grid-edge devices like EVs and heat pumps) more efficiently. An important tool in a utility’s demand management toolbox is pricing innovation – that is, developing new rate designs that more accurately communicate to customers the costs and benefits of their use of the power system. With new time-of-use rate designs, dynamic pricing models, location-based incentives, utilities have a wealth of solutions at their disposal. But to implement these pricing innovations at scale, utilities will need modern billing technologies that can keep up.

Implementing rate design innovation requires more than just smart meters

Over the last decade, US utilities have invested billions of dollars into advanced metering infrastructure (AMI). The transition away from manually-read meters to communications-enabled smart meters has allowed utilities to collect more granular consumption data from end customers. The value of these AMI investments relates to the outcomes utilities are able to achieve with this new, granular meter data. Utilities across the US are seeking to deliver value from their AMI investments by implementing time-varying rates for customers, something they weren’t able to do without granular meter data. However, many utilities are finding that even with modernized metering equipment, the process of implementing new rate designs proves difficult and expensive if their customer IT systems (specifically, billing) have yet to be modernized. Coding a new rate design or product offering into a legacy billing system can take months to years and cost millions of dollars. This implementation bottleneck posed by legacy billing technology comes at the expense of market innovation and system efficiency – and ultimately borne by ratepayers.

What features should modern utility billing technology include?

Ability to utilize new types of data for billing purposes: utilities are collecting new types and formats of data that could be used for price-setting and billing, from increasingly-granular consumption data (collected by smart meters) to individual preference information (collected through customer surveys). Billing technology must be able to efficiently make use of those new data types as they become available.

Configurability for new rate designs and pricing:  as utilities explore new rate design offerings, they are moving from traditional flat volumetric rates to variable pricing structures that more accurately reflect marginal costs and benefits. Often implementing these has taken months or years to complete, costing millions of dollars in the process. Billing systems — and their necessary upgrades — should not serve as a bottleneck to rate design innovation.

Easily integrated with the full customer IT stack: designing new products and programs will only pay off if customers actually make use of those new offerings. To ensure robust uptake and enrollment, utilities will need to actively engage their customers regarding new products and programs, through tailored marketing and outreach, creative enrollment solutions, rate comparisons, etc. To do it well, this engagement will require a utility’s billing system to work with its other backend customer IT systems and seamlessly pass information between them.

Modern billing technology in action: Octopus Energy’s Fan Club and Agile Octopus Tariff

Octopus Energy, a retail energy supplier serving 7.95 million customers, is known for their innovative rate designs. In 2021, Octopus Energy’s British retail business launched a new product for electric customers called Fan Club. Fan Club is designed to increase popular support for onshore wind development by offering customers who live near certain onshore wind projects a discount off their electric supply rate in hours when those projects generate electricity.

Using Kraken’s billing platform, Octopus Energy cross-references a customer’s account-level zip code against the zip code of participating wind turbines (to check for participation eligibility) and then calculates and assigns bill credits to individual participants based on precise time-varying determinants (e.g. energy market prices, wind speed, etc.). Without Kraken, these billing processes may have otherwise been performed by different software programs, which could have been complicated and expensive to execute. With Kraken, Octopus Energy was able to implement Fan Club all from a single billing platform, in a matter of weeks.

Agile Octopus is another innovative smart rate that exposes customers directly to wholesale electricity market prices, using half-hourly market data. Customers enrolled on Agile Octopus are exposed to “plunge pricing,” which occurs in hours when more electricity is generated than consumed, resulting in negative price events. Customers receive alerts when wholesale prices drop below zero and can use an API from Kraken to program their smart devices (e.g. EVs) to charge when prices are negative. By consuming electricity when prices are negative, customers get paid for the electricity they use. This rate design is incredibly complex to bill because it relies on dynamic wholesale prices as key billing determinants. To implement this rate for customers, Octopus Energy required a modern billing system — which they found in Kraken.

Modern billing technology is foundational to the energy transition

To implement advanced rate designs that accelerate the energy transition and make full use of new data that is being collected at the grid edge, utilities will need to modernize their customer billing technology. Information technology vendors like Kraken are enabling this modernization by developing billing systems that allow for agility, scalability and innovation.

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AI for IT stalls as network complexity rises

There are a number of network-related issues that are driving enterprises to delay or abandon their AI projects, according to IDC’s special report on AI in networking. Organizations expect business benefits, including improved IT service levels, to come from using AI across their network infrastructure, according to IDC’s special report

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Vår Energi lets 3-year contract for harsh-environment rig for NCS work

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CERT-EU blames Trivy supply chain attack for Europa.eu data breach

Back door credentials The Trivy compromise dates to February, when TeamPCP exploited a misconfiguration in Trivy’s GitHub Actions environment, now identified as CVE-2026-33634, to establish a foothold via a privileged access token, according to Aqua Security. Discovering this, Aqua Security rotated credentials but, because some credentials remain valid during this

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Latin America returns to the energy security conversation at CERAWeek

With geopolitical risk central to conversations about energy, and with long-cycle supply once again in focus, Latin America’s mix of hydrocarbons and export potential drew renewed attention at CERAWeek by S&P Global in Houston. Argentina, resource story to export platform Among the regional stories, Argentina stood out as Vaca Muerta was no longer discussed simply as a large unconventional resource, but whether the country could turn resource quality into sustained export capacity.  Country officials talked about scale: more operators, more services, more infrastructure, and a larger industrial base around the unconventional play. Daniel González, Vice Minister of Energy and Mining for Argentina, put it plainly: “The time has come to expand the Vaca Muerta ecosystem.” What is at stake now is not whether the basin works, but whether the country can build enough above-ground capacity and regulatory consistency to keep development moving. Horacio Marín, chairman and chief executive officer of YPF, offered an expansive version of that argument. He said Argentina’s energy exports could reach $50 billion/year by 2031, backed by roughly $130 billion in cumulative investment in oil, LNG, and transportation infrastructure. He said Argentine crude output could reach 1 million b/d by end-2026. He said Argentina wants to be seen less as a recurrent frontier story and more as a future supplier with scale. “The time to invest in Vaca Muerta is now,” Marín said. The LNG piece is starting to take shape. Eni, YPF, and XRG signed a joint development agreement in February to move Argentina LNG forward, with a first phase planned at 12 million tonnes/year. Southern Energy—backed by PAE, YPF, Pampa Energía, Harbour Energy, and Golar LNG—holds a long-term agreement with SEFE for 2 million tonnes/year over 8 years. The movement by global standards is early-stage and relatively modest, but it adds to Argentina’s export

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Market Focus: LNG supply shocks expose limited market flexibility

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Libya’s NOC, Chevron sign MoU for technical study for offshore Block NC146

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Finder Energy advances KTJ Project with development area approval

Finder Energy Holdings Ltd. received regulatory approval for a development area covering the Kuda Tasi and Jahal oil fields offshore Timor‑Leste, enabling progression toward field development. Autoridade Nacional do Petróleo (ANP) approved an 88‑sq km development area over the Kuda Tasi and Jahal oil fields (KTJ Project) within PSC 19‑11 offshore Timor‑Leste, representing the first stage of the regulatory approvals process for the project. The declaration of the development area is a precursor to the field development plan (FDP), which Finder is currently preparing for submission to ANP in second‑quarter 2026. Upon approval of the FDP, the development area would secure tenure for up to 25 years or until production ceases, allowing Finder to conduct development and production operations within the area, subject to applicable regulatory approvals and conditions. The company said its upside strategy centers on the potential for the Petrojarl I FPSO to serve as a central processing and export hub for future tiebacks of surrounding discoveries, contingent on successful appraisal and/or exploration activities within PSC 19‑11. Alternatively, longer tie‑back distances could be accommodated through a secondary standalone development in the southern portion of the PSC. Finder is continuing technical evaluation of appraisal and exploration opportunities to generate drilling targets. PSC 19‑11 lies within the Laminaria High oil province of Timor‑Leste. The KTJ Project contains an estimated 25 million bbl of gross 2C contingent resources, with identified upside of an additional 23 million bbl gross 2C contingent resources and 116 million bbl gross 2U prospective resources. Finder operates PSC 19‑11 with a 66% working interest.

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Newly formed Polar LNG aims to develop nearshore LNG project on Alaska’s North Slope

Polar Train LNG LLC, a newly launched company aiming to build an LNG plant (Polar LNG) on Alaska’s North Slope, has appointed Joel Riddle as president and chief executive officer. “Alaska’s North Slope holds one of the most significant undeveloped natural gas resources in the world,” said Riddle, adding “Polar LNG is uniquely positioned to bring this resource online—delivering reliable energy for Alaska and a strategic supply for the United States… and provides trusted energy to our allies.” In a release Mar. 31, the company said it is advancing a nearshore project at Prudhoe Bay, citing “one of the shortest LNG shipping routes from North America to key Asian markets, approximately 3,600 miles to Japan compared to over 10,000 miles from the US Gulf Coast.” The company is aiming for first LNG from the 7-million tonnes/year plant—to be developed nearshore with modular infrastructure—in 2029-2030 at a cost of $8–9 billion. According to Polar LNG, natural gas would be sourced from existing infrastructure at Prudhoe Bay and transported via a short pipeline to a nearshore plant. There, a modular gravity-based structure would process and liquefy the gas. LNG would then be loaded onto specialized ice-class carriers for year-round export. The company is exploring potential repurposing of sanctioned equipment built for Russia’s Arctic LNG 2 project and is seeking permission from the US govenment to acquire parts impacted by the sanctions, according to reports. Before joining Polar LNG, Riddle served as managing director and chief executive officer of Tamboran Resources Ltd.

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Asia bears brunt of energy shock as Middle East war disrupts liquid flows

Asia is facing a dual energy crisis marked by both soaring prices and physical supply disruptions as escalating war in the Middle East constrains flows through the Strait of Hormuz, according to a new report by Morningstar DBRS. The report highlights that roughly one-fifth of global crude oil and LNG supply has been affected by disruptions at the critical chokepoint, with Asia absorbing the majority of the impact due to its heavy dependence on imported hydrocarbons. About 83% of oil and LNG shipments passing through Hormuz are destined for Asian markets, amplifying the region’s exposure. Asia’s structural reliance on Middle Eastern energy imports has intensified the shock. Countries such as Japan and South Korea import nearly all of their energy needs, while China and India depend heavily on foreign supplies, much of it sourced from the Gulf. This dependence, combined with limited alternative shipping routes, has turned what initially appeared to be a price-driven shock into a broader supply and logistics crisis. Governments across the region have begun implementing emergency measures, including fuel rationing, price controls, and strategic reserve releases, to manage shortages and rising costs. Policy responses vary In North Asia, policymakers are leveraging stronger buffers. Japan has tapped strategic oil reserves and introduced subsidies to cushion consumers, while South Korea is relying on LNG stockpiles and fuel-switching capabilities. China has deployed administrative controls to stabilize domestic fuel prices and restrict refined product exports. By contrast, parts of South and Southeast Asia are more vulnerable. India has introduced tax relief and prioritized gas allocation, while countries such as the Philippines and Vietnam have declared energy emergencies and rolled out conservation measures. Several ASEAN (the Association of Southeast Asian Nations) economies have even implemented partial work-from-home policies to curb fuel consumption. Broader economic spillovers intensify Beyond energy markets, the disruption

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Two New England states say no to new data centers

It’s getting harder and harder for governments to ignore the impact that data centers are having on their communities, consuming vast amounts of water and driving up electricity prices, experts say. According to a Pew Research Center analysis, data centers consumed 183 terawatt-hours of electricity in 2024, more than 4% of total U.S. electricity use. That demand is projected to more than double to 426 terawatt-hours by 2030. The impact is significant. In 2023, data centers consumed about 26% of Virginia’s electricity supply, although Virginia is notable for having an extremely dense collection of data centers. Alan Howard, senior analyst for infrastructure at Omdia, says he is not surprised at all. “The amount of national press coverage regarding what is arguably a limited number of data center ‘horror’ stories has many jurisdictions and states spooked over the potential impacts data center projects might have,” he said. It’s an evolution that’s been coming for some time whereby local legislators have embraced the idea that they don’t want to learn the hard way as others already have, he argues. “All that said, it seems unlikely that there will be broad bans on data center development that would cripple the industry. There’s lots of places to go in the U.S. and developers have warmed up to siting projects in places amenable to their needs, although not ideally convenient,” said Howard.

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Nscale Expands AI Factory Strategy With Power, Platform, and Scale

Nscale has moved quickly from startup to serious contender in the race to build infrastructure for the AI era. Founded in 2024, the company has positioned itself as a vertically integrated “neocloud” operator, combining data center development, GPU fleet ownership, and a software stack designed to deliver large-scale AI compute. That model has helped it attract backing from investors including Nvidia, and in early March 2026 the company raised another $2 billion at a reported $14.6 billion valuation. Reuters has described Nscale’s approach as owning and operating its own data centers, GPUs, and software stack to support major customers including Microsoft and OpenAI. What makes Nscale especially relevant now is that it is no longer content to operate as a cloud intermediary or capacity provider. Over the past year, the company has increasingly framed itself as an AI hyperscaler and AI factory builder, seeking to combine land, power, data center shells, GPU procurement, customer offtake, and software services into a single integrated platform. Its acquisition of American Intelligence & Power Corporation, or AIPCorp, is the clearest signal yet of that shift, bringing energy infrastructure directly into the center of Nscale’s business model. The AIPCorp transaction is significant because it gives Nscale more than additional development capacity. The company said the deal includes the Monarch Compute Campus in Mason County, West Virginia, a site of up to 2,250 acres with a state-certified AI microgrid and a power runway it says can scale beyond 8 gigawatts. Nscale also said the acquisition establishes a new division, Nscale Energy & Power, headquartered in Houston, extending its platform further into power development. That positioning reflects a broader shift in the AI infrastructure market. The central bottleneck is no longer simply access to GPUs. It is the ability to assemble power, cooling, land, permits, data center

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Google Research touts memory-compression breakthrough for AI processing

The last time the market witnessed a shakeup like this was China’s DeepSeek, but doubts emerged quickly about its efficacy. Developers found DeepSeek’s efficiency gains required deep architectural decisions that had to be built in from the start. TurboQuant requires no retraining or fine-tuning. You just drop it straight into existing inference pipelines, at least in theory. If it works in production systems with no retrofitting, then data center operators will get tremendous performance gains on existing hardware. Data center operators won’t have to throw hardware at the performance problem. However, analysts urge caution before jumping to conclusions. “This is a research breakthrough, not a shipping product,” said Alex Cordovil, research director for physical infrastructure at The Dell’Oro Group. “There’s often a meaningful gap between a published paper and real-world inference workloads.” Also, Dell’Oro notes that efficiency gains in AI compute tend to get consumed by more demand, known as the Jevons paradox. “Any freed-up capacity would likely be absorbed by frontier models expanding their capabilities rather than reducing their hardware footprint.” Jim Handy, president of Objective Analysis, agrees on that second part. “Hyperscalers won’t cut their spending – they’ll just spend the same amount and get more bang for their buck,” he said. “Data centers aren’t looking to reach a certain performance level and subsequently stop spending on AI. They’re looking to out-spend each other to gain market dominance. This won’t change that.” Google plans to present a paper outlining TurboQuant at the ICLR conference in Rio de Janeiro running from April 23 through April 27.

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Amazon Middle East datacenter suffers second drone hit as Iran steps up attacks

Amazon was contacted for comment on the latest Bahrain drone incident, but said it had nothing to add beyond the statement in its current advisory. Denial of infrastructure Doing the damage is the Shaheed 136, a small and unsophisticated drone designed to overwhelm defenders with numbers. If only one in twenty reaches its target, the price-performance still exceeds that of more expensive systems. When aimed at critical infrastructure such as datacenters, the effect is also psychological; the threat of an attack on its own can be enough to make it difficult for organizations to continue using an at-risk facility.  Iran’s targeting of the Bahrain datacenter is unlikely to be random. Amazon opened its ME-SOUTH-1 AWS presence in 2019, and it is still believed to be the company’s largest site in the Middle East. Earlier this week, the Islamic Revolutionary Guard Corps (IRGC) Telegram channel explicitly threatened to target at least 18 US companies operating in the region, including Microsoft, Google, Nvidia, and Apple. This follows similar threats to an even longer list of US companies made on the IRGC-affiliated Tasnim News Agency in recent weeks. That strategy doesn’t bode well for US companies that have made large investments in Middle Eastern datacenter infrastructure in recent years, drawn by the growing wealth and influence of countries in the region. This includes Amazon, which has announced plans to build a $5.3 billion datacenter in Saudi Arabia, due to become available in 2026. If this is now under threat, whether by warfare or the hypothetical possibility of attack, that will create uncertainty.

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

Each month Data Center Frontier, in partnership with Pkaza, posts some of the hottest data center career opportunities in the market. Here’s a look at some of the latest data center jobs posted on the Data Center Frontier jobs board, powered by Pkaza Critical Facilities Recruiting. Looking for Data Center Candidates? Check out Pkaza’s Active Candidate / Featured Candidate Hotlist Power Applications Engineer Pittsburgh, PA This position is also available in: Denver, CO and Andrews, SC.  Our client is a leading provider and manufacturer of industrial electrical power equipment used in industrial applications for mission critical operations. They help their customers save money by reducing energy and operating costs and provide solutions for modernizing their customer’s existing electrical infrastructure. This company provides cooling solutions to many of the world’s largest organizations and government facilities and enterprise clients, colocation providers and hyperscale companies. This career-growth minded opportunity offers exciting projects with leading-edge technology and innovation as well as competitive salaries and benefits. Electrical Commissioning Engineer Ashburn, VA This traveling position is also available in: New York, NY; White Plains, NY;  Dallas, TX; Richmond, VA; Montvale, NJ; Charlotte, NC; Atlanta, GA; Hampton, GA; New Albany, OH; Cedar Rapids, IA; Phoenix, AZ; Salt Lake City, UT;  Kansas City, MO; Omaha, NE; Chesterton, IN or Chicago, IL. *** ALSO looking for a LEAD EE and ME CxA Agents and CxA PMs. ***  Our client is an engineering design and commissioning company that has a national footprint and specializes in MEP critical facilities design. They provide design, commissioning, consulting and management expertise in the critical facilities space. They have a mindset to provide reliability, energy efficiency, sustainable design and LEED expertise when providing these consulting services for enterprise, colocation and hyperscale companies. This career-growth minded opportunity offers exciting projects with leading-edge technology and innovation as well as competitive

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No joke: data centers are warming the planet

The researchers also made use of a database provided by the International Energy Agency (IEA) that the authors pointed out contains more than 11,000 locations worldwide, of which 8,472 have been detected to dwell outside of highly dense urban areas. The latter locations were then used to “quantify the effect of data centers on the environment in terms of the LST gradient that could be measured on the areas surrounding each data center.” Asking the wrong question Asked if AI data centers are really causing local warming, or if this phenomenon is overstated, Sanchit Vir Gogia, chief analyst at Greyhound Research, said, “the signal is real, but the industry is asking the wrong question. The research shows a consistent rise in land surface temperature of around 2°C  following the establishment of large data centre facilities.” The debate, however, “has quickly shifted to causality: whether this is driven by operational heat from compute, or by land transformation during construction. That distinction matters scientifically, but it does not change the strategic implication.” Land surface temperature, said Gogia, is not the same as air temperature, and that gap will be used to challenge the findings. “But dismissing the signal on that basis would be a mistake,” he noted. “Data centers concentrate energy use, replace natural surfaces with heat-retaining materials, and continuously reject heat into the environment. Those are known drivers of thermal change.” He added, “the uncomfortable truth is this: Even if the exact mechanism is debated, the outcome aligns with first principles. Infrastructure at this scale alters its surroundings. The industry does not yet have a clean way to separate construction impact from operational impact, and that ambiguity makes the risk harder to model, not easier. This is not overstated, it is under-interpreted.” Location strategy must change But will the findings change

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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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OpenAI acquires TBPN

Fidji Simo shared this message with the company earlier today: I’m excited to share that we’ve acquired TBPN⁠(opens in a new window). This acquisition brings

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