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OpenAI–Broadcom alliance signals a shift to open infrastructure for AI

The decision also reflects a future of AI workloads running on heterogeneous computing and networking infrastructure, said Lian Jye Su, chief analyst at Omdia. “While it makes sense for enterprises to first rely on Nvidia’s full stack solution to roll out AI, they will generally integrate alternative solutions such as AMD and self-developed chips for cost […]

The decision also reflects a future of AI workloads running on heterogeneous computing and networking infrastructure, said Lian Jye Su, chief analyst at Omdia.

“While it makes sense for enterprises to first rely on Nvidia’s full stack solution to roll out AI, they will generally integrate alternative solutions such as AMD and self-developed chips for cost efficiency, supply chain diversity, and chip availability,” Su said. “This means data center networking vendors will need to consider interoperability and open standards as ways to address the diversification of AI chip architecture.”

Hyperscalers and enterprise CIOs are increasingly focused on how to efficiently scale up or scale out AI servers as workloads expand. Nvidia’s GPUs still underpin most large-scale AI training, but companies are looking for ways to integrate them with other accelerators.

Neil Shah, VP for research at Counterpoint Research, said that Nvidia’s recent decision to open its NVLink interconnect to ecosystem players earlier this year gives hyperscalers more flexibility to pair Nvidia GPUs with custom accelerators from vendors such as Broadcom or Marvell.

“While this reduces the dependence on Nvidia for a complete solution, it actually increases the total addressable market for Nvidia to be the most preferred solution to be tightly paired with the hyperscaler’s custom compute,” Shah said.

Most hyperscalers have moved toward custom compute architectures to diversify beyond x86-based Intel or AMD processors, Shah added. Many are exploring Arm or RISC-V designs that can be tailored to specific workloads for greater power efficiency and lower infrastructure costs.

Shifting AI infrastructure strategies

The collaboration also highlights how networking choices are becoming as strategic as chip design itself, suggesting a change in how AI workloads are powered and connected.

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Intel details new efficient Xeon processor line

The new chips will be able to support up to 12-channel DDR5 memory with speeds of up to 8000 MT/s, a substantial increase over the 8 channels of 6400MT/s in the prior generation. In addition to that, the platform will support up to 6 UPI 2.0 links with up to

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Oil Prices Fall to Lowest Point in 5 Months

Oil prices fell to their lowest point in five months on Tuesday, extending their downward trend. That’s what Daniel Takieddine, Co-founder and CEO of Sky Links Capital Group, said in a market analysis sent to Rigzone today. “Mounting concerns of a global supply surplus weighed on the market, compounded by renewed trade tensions between the U.S. and China,” Takieddine stated in the analysis. “The latest International Energy Agency (IEA) market report added to the concerns and forecasts a growing oversupply of oil,” he added. “The IEA has increased its global supply growth projections to three million barrels per day for this year and 2.4 million for 2026, pointing to production hikes from OPEC+ and robust output from the Americas,” he continued. “In contrast, the agency has lowered its demand growth estimates to approximately 700,000 barrels per day for both years, reinforcing expectations of a significant surplus,” Takieddine warned. The Sky Links Capital Group CEO went on to state in the analysis that trade tensions are injecting fresh uncertainty into the market. “A brief rebound in prices on Monday, sparked by hopes for de-escalation in U.S.-China trade talks, quickly faded,” he said. “The market was further affected by a reduced geopolitical risk premium as hopes for stability in the Middle East grew,” he added. Looking ahead, Takieddine noted in the analysis that markets could closely monitor U.S.-China relations, OPEC+ supply, and upcoming inventory data from the EIA (Energy Information Administration) “to determine the market’s next direction”. “Without a positive surprise from inventory reports or broader macroeconomic data, prices could remain under pressure,” he warned. In a separate statement sent to Rigzone this morning, Naeem Aslam, Chief Market Analyst at Zay Capital Markets, highlighted that the Brent and West Texas Intermediate oil prices were “reflecting the balance between geopolitical tensions, economic policies, and

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Repsol Starts Renewable Gasoline Production at Tarragona Complex

Repsol SA has declared a “technological milestone” with the start of “industrial-scale” production of 100 percent renewable gasoline at its complex in Tarragona, Spain, making a case for combustion engines. “This new product, made entirely from renewable sources, is fully compatible with gasoline vehicles without the need for any modifications”, the Spanish energy company said in a press release. “Its use reduces net CO2 emissions by more than 70 percent compared to conventional gasoline. “Nexa 95 Gasoline of 100 percent renewable origin – Repsol’s highest-quality 95-octane product – is already available at 20 service stations in Spain, in the Madrid and Catalonia regions”. Repsol expects to deploy the product at 30 stations by yearend by expanding in other parts of the country including the cities of Bilbao, Tarragona, Valencia and Zaragoza. The formulation was developed with Honeywell, according to Repsol. In 2024 Repsol launched Nexa 100 Percent Renewable Diesel, which it says is designed for all diesel engines. Repsol said the development of the products demonstrate that “decarbonizing transport with renewable liquid fuels is a viable solution for combustion engine vehicles, whether gasoline, diesel or hybrid”. “These vehicles today represent 97 percent of the Spanish and European vehicle fleet, and 87 percent of sales in Spain so far this year”, it said. “To meet the climate targets set by Spain and the European Union, it is essential to recognize the role of 100 percent renewable fuels and, consequently, to reconsider the EU regulation on CO2 emission standards, which proposes a ban on combustion engines by 2035. The uncertainty caused by this measure has led to considerable aging of Spain’s vehicle fleet, with an average age of 14.5 years and 8.5 million vehicles – nearly one-third of the total fleet – over 20 years old. “To accelerate the development of renewable fuels, it is essential to establish

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North America Adds 1 Rig Week on Week

North America added one rig week on week, according to Baker Hughes’ latest North America rotary rig count, which was released on October 10. The total U.S. rig count dropped by two week on week and the total Canada rig count increased by three during the same period, taking the total North America rig count up to 740, comprising 547 rigs from the U.S. and 193 rigs from Canada, the count outlined. Of the total U.S. rig count of 547, 529 rigs are categorized as land rigs, 15 are categorized as offshore rigs, and three are categorized as inland water rigs. The total U.S. rig count is made up of 418 oil rigs, 120 gas rigs, and nine miscellaneous rigs, according to Baker Hughes’ count, which revealed that the U.S. total comprises 480 horizontal rigs, 55 directional rigs, and 12 vertical rigs. Week on week, the U.S. offshore and inland water rig counts remained unchanged, and the country’s land rig count dropped by two, Baker Hughes highlighted. The U.S. oil rig count dropped by four, its gas rig count increased by two, and miscellaneous rig count remained unchanged, week on week, the count showed. The U.S. directional rig count dropped by three week on week, while the country’s horizontal rig count increased by one and its vertical rig count remained unchanged, the count revealed. A major state variances subcategory included in the rig count showed that, week on week, Texas dropped six rigs, Oklahoma dropped three rigs, Wyoming dropped one rig, New Mexico added four rigs, Utah added two rigs, and Louisiana and North Dakota each added one rig. A major basin variances subcategory included in Baker Hughes’ rig count showed that, week on week, the Granite Wash basin dropped two rigs and the Eagle Ford, DJ-Niobrara and Permian basins

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Midad to Invest $5.4B in Algerian Production Sharing Contract

Sonatrach signed a production sharing contract (PSC) with Midad Energy for the Illizi South area, nearly 100 kilometers (62.14 miles) south of In Amenas, Algeria’s national oil and gas company said Monday. The Saudi company, through its Netherlands-based subsidiary Midad Energy North Africa BV, agreed to shoulder the full exploration and development cost. That is expected to be $5.4 billion, including $288 million for exploration, Sonatrach said in a statement on its website. The PSC is expected to produce, according to Sonatrach, a total of 993 million barrels of oil equivalent consisting of 125 billion cubic meters (4.41 trillion cubic feet) of gas for marketing and 204 million barrels of liquids, including 103 million barrels of liquefied petroleum gas and 101 million barrels of condensate. The contract lasts 30 years, including seven years for exploration, Sonatrach said. The contract is extendable by 10 years, it said. “This program includes also the use of the latest technological and digital solutions”, Sonatrach said. “Furthermore, calling on local content and subcontracting with national supplier under the execution of this contract will be prioritized”. Sonatrach chair and chief executive Rachid Hachichi and Midad Energy North Africa counterpart Sheikh Abdulelah Bin Mohammed Bin Abdullah Al-Aiban signed the PSC in the presence of Algerian Hydrocarbons and Mines Minister Mohamed Arkab and Saudi Ambassador to Algeria Abdullah Bin Nasser Abdullah Al-Busairi, according to Sonatrach. On July 21 Sonatrach announced it has entered five hydrocarbon contracts under Algeria’s 2024 bidding round. Ahara in Illizi province was signed with QatarEnergy and France’s TotalEnergies SE. Guern El Guessa II in the provinces of Bechar, Beni Abbes, El Bayadh and Timimoun was signed with China Petroleum and Chemical Corp (Sinopec). Toual II in the provinces of Ouargla and Illizi was signed with Austria’s Zangas Hoch- und Tiefbau GmbH and Switzerland’s Filada AG.

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Valeura Raises Production at Nong Yao in Gulf of Thailand

Valeura Energy Inc has completed a 10-well infill drilling campaign at the Nong Yao oilfield in the Gulf of Thailand, increasing the company’s net production before royalties to 24,800 barrels per day (bpd) in the last seven days of the third quarter. “The campaign was primarily production-oriented and resulted in the company’s working interest share oil production before royalties from the Nong Yao field increasing from approximately 7,996 bpd prior to the first new wells coming on stream, to a recent rate of 11,562 bpd, over the seven-day period ending September 30, 2025”, Canada’s Valeura said in an operations update on its website. “The company anticipates that the reservoirs encountered may add to the ultimate production potential of the Nong Yao field and can thereby further extend its economic life”. The campaign involved all three wellhead infrastructure facilities in Nong Yao, Valeura said. The Nong Yao B segment of the campaign “included some of the most technically challenging wells ever drilled in the Gulf of Thailand basin, influenced by both geological complexity and also their extended reach from the wellhead platform, in one instance measuring a total drilled length of over 9,800′”, Valeura noted. Valeura operates Nong Yao with a 90 percent stake through License G11/48, in which Palang Sophon Co Ltd owns the remaining 10 percent. Nong Yao held proven and probable gross pre-royalties reserves of 16.9 million as of yearend 2024, according to Valuera. The field produces medium sweet crude from Miocene-age reservoirs, according to the company. Elsewhere in the Gulf of Thailand, work is progressing on the Wassana oilfield redevelopment project. Wassana’s newbuild wellhead production facility is on track to start up in the second quarter of 2027, Valeura added. “The Wassana redevelopment project is intended to increase production, reduce unit costs and create a hub for

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Putin Relaxes Rules for Fuel Subsidies to Refiners

Russian President Vladimir Putin relaxed the rules on fuel subsidies to the nation’s refiners, allowing them to continue receiving billions of rubles in aid amid intensified Ukrainian attacks on the industry.  Refineries will remain eligible for subsidies even if market wholesale prices for diesel and gasoline significantly exceed threshold prices, according to a presidential decree published on Sunday. The changes will stay in place from Oct. 1 until May 1. The subsidies are designed to encourage Russian oil producers to keep supplying gasoline and diesel to the domestic market, even when export prices become more attractive. Under current rules, the government is legally bound to pay the subsidy if the market wholesale price of gasoline doesn’t exceed 10% of the threshold price, with the range for diesel at 20%. Refineries won’t receive state payments after that level.   Russia paid 1.8 trillion rubles ($22 billion) in fuel subsidies last year, while payments over the first nine months of 2025 fell to 716 billion rubles. Since early August, Ukraine has intensified attacks on the Russian oil industry, with repeated strikes on refineries resulting in a drop of crude-processing rates, exacerbating a fuel crunch and leading to rising domestic prices.  Last month Deputy Prime Minister Alexander Novak said the fuel-price hike that triggers subsidies will be increased by 10 percentage points from September. The maximum allowed market-price hike would be raised to 20% of the threshold price for gasoline and 30% for diesel.  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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OpenAI–Broadcom alliance signals a shift to open infrastructure for AI

The decision also reflects a future of AI workloads running on heterogeneous computing and networking infrastructure, said Lian Jye Su, chief analyst at Omdia. “While it makes sense for enterprises to first rely on Nvidia’s full stack solution to roll out AI, they will generally integrate alternative solutions such as AMD and self-developed chips for cost efficiency, supply chain diversity, and chip availability,” Su said. “This means data center networking vendors will need to consider interoperability and open standards as ways to address the diversification of AI chip architecture.” Hyperscalers and enterprise CIOs are increasingly focused on how to efficiently scale up or scale out AI servers as workloads expand. Nvidia’s GPUs still underpin most large-scale AI training, but companies are looking for ways to integrate them with other accelerators. Neil Shah, VP for research at Counterpoint Research, said that Nvidia’s recent decision to open its NVLink interconnect to ecosystem players earlier this year gives hyperscalers more flexibility to pair Nvidia GPUs with custom accelerators from vendors such as Broadcom or Marvell. “While this reduces the dependence on Nvidia for a complete solution, it actually increases the total addressable market for Nvidia to be the most preferred solution to be tightly paired with the hyperscaler’s custom compute,” Shah said. Most hyperscalers have moved toward custom compute architectures to diversify beyond x86-based Intel or AMD processors, Shah added. Many are exploring Arm or RISC-V designs that can be tailored to specific workloads for greater power efficiency and lower infrastructure costs. Shifting AI infrastructure strategies The collaboration also highlights how networking choices are becoming as strategic as chip design itself, suggesting a change in how AI workloads are powered and connected.

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Inside Nvidia’s ‘grid-to-chip’ vision: How Vera Rubin and Spectrum-XGS push toward AI giga-factories

Vera Rubin MGX brings together Nvidia’s Vera CPUs and Rubin CPX GPUs, all using the same open MGX rack footprint as Blackwell. The system allows for numerous configurations and integrations. “MGX is a flexible, modular building block-based approach to server and rack scale design,” Delaere said. “It allows our ecosystem to create a wide range of configurations, and do so very quickly.” Vera Rubin MGX will deliver almost eight times more performance than Nvidia’s GB 300 for certain types of calculation, he said. The architecture is liquid-cooled and cable-free, allowing for faster assembly and serviceability. Operators can quickly mix and match components such as CPUs, GPUs, or storage, supporting interoperability, Nvidia said. Matt Kimball, principal data center analyst at Moor Insights and Strategy, highlighted the modularity and cleanness of the MGX tray design. “This simplifies the manufacturing process significantly,” he said. For enterprises managing tens or even hundreds of thousands of racks, “this design enables a level of operational efficiency that can deliver real savings in time and cost.” Nvidia is also showing innovation with cooling, Kimball said. “Running cooling to the midplane is a very clean design and more efficient.”

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Cisco seriously amps-up Silicon One chip, router for AI data center connectivity

Some say deep buffers shouldn’t be used to handle this type of traffic; the contention is that these buffers fill and drain, creating jitter in the workloads, and that slows things down, Chopra told Network World. “But the real source of that challenge is not the buffers. It’s a poor congestion management scheme and poor load balancing with AI workloads, which are completely deterministic and predictable. You can actually proactively figure out how to place flows across the network and avoid the congestion,” he said. The 8223’s deep-buffer design provides ample memory to temporarily store packets during congestion or traffic bursts, an essential feature for AI networks where inter-GPU communication can create unpredictable, high-volume data flows, according to Gurudatt Shenoy, vice president of Cisco Provider Connectivity. “Combined with its high-radix architecture, the 8223 allows more devices to connect directly, reducing latency, saving rack space, and further lowering power consumption. The result is a flatter, more efficient network topology supporting high-bandwidth, low-latency communication that is critical for AI workloads,” Shenoy wrote in a blog post. NOS options Notably, the first operating systems that the 8223 supports are the Linux Foundation’s Software for Open Networking in the Cloud (SONiC) and Facebook open switching system (FBOSS) – not Cisco’s own IOS XR.  IXR will be supported, too, but at a later date, according to Cisco.  SONiC decouples network software from the underlying hardware and lets it run on hundreds of switches and ASICs from multiple vendors while supporting a full suite of network features such as Border Gateway Protocol (BGP), remote direct memory access (RDMA), QoS, and Ethernet/IP. One of the keys to SONiC is its switch-abstraction interface, which defines an API to provide a vendor-independent way of controlling forwarding elements such as a switching ASIC, an NPU, or a software switch in a uniform

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Utilities Race to Meet Surging Data Center Demand With New Power Models

Over the last 18 months or so, the energy generation industry and its public utilities have been significantly impacted by the AI data center boom. It has been demonstrated across North America that the increase in demand for power, as driven by the demand for hyperscale and AI data centers, greatly exceeds the ability of the industry to actually generate and deliver power to meet the demand. We have covered many of the efforts being made to control the availability of power. In response, utilities and regulators have begun rethinking how to manage power availability through means such as: temporary moratoriums on new data center interconnections; the creation of new rate classes; cogeneration and load-sharing agreements; renewable integration; and power-driven site selection strategies.  But the bottom line is that in many locations utilities will need to change the way they work and how and where they spend their CAPEX budgets. The industry has already realized that their demand forecast models are hugely out of date, and that has had a ripple effect on much of the planning done by public utilities to meet the next generation of power demand. Most utilities now acknowledge that their demand forecasting models have fallen behind reality, triggering revisions to Integrated Resource Plans (IRPs) and transmission buildouts nationwide. This mismatch between forecast and actual demand is forcing a fundamental rethink of capital expenditure priorities and long-term grid planning. Spend More, Build Faster Utilities are sharply increasing CAPEX and rebalancing their resource portfolios—not just for decarbonization, but to keep pace with multi-hundred-megawatt data center interconnects. This trend is spreading across the industry, not confined to a few isolated utilities. Notable examples include: Duke Energy raised its five-year CAPEX plan to $83 billion (a 13.7% increase) and plans to add roughly 5 GW of natural gas capacity

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Duos Pairs Mobile Power and Modular Edge Data Centers for Rapid Texas Rollout

Duos Technology Group has launched the fifth of its AI edge data centers, part of a plan to deploy 15 units by the end of 2025. The projects are executed through Duos Edge AI, a subsidiary focused on modular, rapidly installed edge data centers (EDCs) in underserved markets, beginning with school districts and regional carrier hubs across Texas. The newest site is being deployed on-premises with the Dumas Independent School District in Dumas, Texas. High-Density Edge Design Duos’ EDCs emphasize very high rack densities (100 kW+ per rack), SOC 2 Type II compliance, N+1 power with dual generators, and a 90-day build/turn-up cycle. Each site is positioned approximately 12 miles from end users, cutting latency for real-time workloads. To meet the power demands of these edge deployments, Duos formed Duos Energy and partnered with Fortress/APR Energy to deliver behind-the-meter mobile gas turbines. This approach allows compute to go live in 90 days without waiting years for utility interconnection upgrades. The goal is straightforward: move power and compute close to demand, with rapid deployment. Duos’ modular pods are designed for exurban and rural locations as localized compute hubs for carriers, schools, healthcare systems, and municipal users. The rugged design pairs high-density racks with the short deployment cycle and proximity targeting, enabling a wide range of applications. With Dumas ISD now live, Duos has five sites in Texas, including Amarillo/Region 16, Victoria/Region 3, Dumas ISD, and multiple Corpus Christi locations. Mobile Power vs. Modular Compute While Duos doesn’t consistently describe its data center units as “mobile,” they are modular and containerized, engineered for rapid, site-agnostic deployment. The “mobile” label more explicitly applies to Duos’ power strategy—a turbine fleet that can be fielded or re-fielded to match demand. From an operator’s perspective, the combined proposition functions like a mobile platform: pre-integrated compute pods

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Report: AMD could be Intel’s next foundry customer

[ Related: More Intel news and insights ] AMD has lagged behind Nvidia in the AI business but has done well in the federal supercomputing business, holding numerous top spots with supercomputers like El Capitan and Frontier. Manufacturing its chips in the United States would be a good way to get the Trump administration off its back given its push for domestic manufacturing of semiconductors. The Trump administration is pushing for 50% of chips sold in America to be manufactured domestically, and tariffs on chips that are not. It also faces outbound restrictions. Earlier this year, AMD faced export restrictions GPUs meant for China as part of U.S. export controls against China’s AI business. “I believe this is a smart move by AMD to secure capacity in the local market without fighting against Nvidia and Apple and their deeper pockets for the limited capacity at TSMC,” said Alvi Nguyen, senior analyst with Forrester Research.” With the US investment in Intel, followed by Nvidia, this is can be seen as diversifying their supply chain and providing cheaper, locally sourced parts.” For Intel, this will continue a streak of good news it has enjoyed recently. “Having customers take up capacity at their foundries will go a long way in legitimizing their semiconductor processes and hopefully create the snowball effect of getting even more US-based customers,” said Nguyen. In recent weeks, Intel has partnered with Nvidia to jointly make PC and data center chips. Nvidia also took a $5B stake in Intel. Earlier the Trump administration made a $11.1B, or 10%, stake in Intel.

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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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Can we repair the internet?

From addictive algorithms to exploitative apps, data mining to misinformation, the internet today can be a hazardous place. Books by three influential figures—the intellect behind

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