Deepening our partnership with the UK AI Security Institute

Stay Ahead, Stay ONMINE

Deepening our partnership with the UK AI Security Institute

Today, we’re announcing an expanded partnership with the UK AI Security Institute (AISI) through a new Memorandum of Understanding focused on foundational security and safety research, to help ensure artificial intelligence is developed safely and benefits everyone.The research partnership with AISI is an important part of our broader collaboration with the UK government on accelerating safe and beneficial AI progress.Building on a foundation of collaborationAI holds immense potential to benefit humanity by helping treat disease, accelerate scientific discovery, create economic prosperity and tackle climate change. For these benefits to be realised, we must put safety and responsibility at the heart of development. Evaluating our models against a broad spectrum of potential risks remains a critical part of our safety strategy, and external partnerships are an important element of this work.This is why we have partnered with the UK AISI since its inception in November 2023 to test our most capable models. We are deeply committed to the UK AISI’s goal to equip governments, industry and wider society with a scientific understanding of the potential risks posed by advanced AI as well as potential solutions and mitigations.We are actively working with AISI to build more robust evaluations for AI models, and our teams have collaborated on safety research to move the field forward, including recent work on Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety. Building on this success, today we are broadening our partnership from testing to include wider, more foundational, research in a variety of areas.What the partnership involvesUnder this new research partnership, we’re broadening our collaboration to include:Sharing access to our proprietary models, data and ideas to accelerate research progressJoint reports and publications sharing findings with the research communityMore collaborative security and safety research combining our teams’ expertiseTechnical discussions to tackle complex safety challengesKey research areasOur joint research with AISI focuses on critical areas where Google DeepMind’s expertise, interdisciplinary teams, and years of pioneering responsible research can help make AI systems more safe and secure:Monitoring AI reasoning processesWe will work on techniques to monitor an AI system’s “thinking”, also commonly referred to as its chain-of-thought (CoT). This work builds on previous Google DeepMind research as well, and our recent collaboration on this topic with AISI, OpenAI, Anthropic and other partners. CoT monitoring helps us understand how an AI system produces its answers, complementing interpretability research.Understanding social and emotional impactsWe will work together to investigate the ethical implications of socioaffective misalignment; that is, the potential for AI models to behave in ways which do not align with human wellbeing, even when they’re technically following instructions correctly. This research will build on existing Google DeepMind work that has helped define this critical area of AI safety.Evaluating economic systemsWe will explore the potential impact of AI on economic systems by simulating real-world tasks across different environments. Experts will score and validate these tasks, after which they will be categorised along dimensions like complexity or representativeness, to help predict factors like long-term labour market impact.Working together to realise the benefits of AIOur partnership with AISI is one element of how we aim to realise the benefits of AI for humanity while mitigating potential risks. Our wider strategy includes foresight research, extensive safety training that goes hand-in-hand with capability development, rigorous testing of our models, and the development of better tools and frameworks to understand and mitigate risk.Strong internal governance processes are also essential for safe and responsible AI development, as is collaborating with independent external experts who bring fresh perspectives and diverse expertise to our work. Google DeepMind’s Responsibility and Safety Council works across teams to monitor emerging risk, review ethics and safety assessments and implement relevant technical and policy mitigations. We also partner with other external experts like Apollo Research, Vaultis, Dreadnode and more, to conduct extensive testing and evaluation of our models, including Gemini 3, our most intelligent and secure model to date.Additionally, Google DeepMind is a proud founding member of the Frontier Model Forum, as well as the Partnership on AI, where we focus on ensuring safe and responsible development of frontier AI models and increasing collaboration on important safety issues.We hope our expanded partnership with AISI will allow us to build more robust approaches to AI safety for the benefit not just of our own organisations, but also the wider industry and everyone who interacts with AI systems.

The research partnership with AISI is an important part of our broader collaboration with the UK government on accelerating safe and beneficial AI progress.

Building on a foundation of collaboration

AI holds immense potential to benefit humanity by helping treat disease, accelerate scientific discovery, create economic prosperity and tackle climate change. For these benefits to be realised, we must put safety and responsibility at the heart of development. Evaluating our models against a broad spectrum of potential risks remains a critical part of our safety strategy, and external partnerships are an important element of this work.

This is why we have partnered with the UK AISI since its inception in November 2023 to test our most capable models. We are deeply committed to the UK AISI’s goal to equip governments, industry and wider society with a scientific understanding of the potential risks posed by advanced AI as well as potential solutions and mitigations.

We are actively working with AISI to build more robust evaluations for AI models, and our teams have collaborated on safety research to move the field forward, including recent work on Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety. Building on this success, today we are broadening our partnership from testing to include wider, more foundational, research in a variety of areas.

What the partnership involves

Under this new research partnership, we’re broadening our collaboration to include:

Sharing access to our proprietary models, data and ideas to accelerate research progress
Joint reports and publications sharing findings with the research community
More collaborative security and safety research combining our teams’ expertise
Technical discussions to tackle complex safety challenges

Key research areas

Our joint research with AISI focuses on critical areas where Google DeepMind’s expertise, interdisciplinary teams, and years of pioneering responsible research can help make AI systems more safe and secure:

Monitoring AI reasoning processes

We will work on techniques to monitor an AI system’s “thinking”, also commonly referred to as its chain-of-thought (CoT). This work builds on previous Google DeepMind research as well, and our recent collaboration on this topic with AISI, OpenAI, Anthropic and other partners. CoT monitoring helps us understand how an AI system produces its answers, complementing interpretability research.

Understanding social and emotional impacts

We will work together to investigate the ethical implications of socioaffective misalignment; that is, the potential for AI models to behave in ways which do not align with human wellbeing, even when they’re technically following instructions correctly. This research will build on existing Google DeepMind work that has helped define this critical area of AI safety.

Evaluating economic systems

We will explore the potential impact of AI on economic systems by simulating real-world tasks across different environments. Experts will score and validate these tasks, after which they will be categorised along dimensions like complexity or representativeness, to help predict factors like long-term labour market impact.

Working together to realise the benefits of AI

Our partnership with AISI is one element of how we aim to realise the benefits of AI for humanity while mitigating potential risks. Our wider strategy includes foresight research, extensive safety training that goes hand-in-hand with capability development, rigorous testing of our models, and the development of better tools and frameworks to understand and mitigate risk.

Strong internal governance processes are also essential for safe and responsible AI development, as is collaborating with independent external experts who bring fresh perspectives and diverse expertise to our work. Google DeepMind’s Responsibility and Safety Council works across teams to monitor emerging risk, review ethics and safety assessments and implement relevant technical and policy mitigations. We also partner with other external experts like Apollo Research, Vaultis, Dreadnode and more, to conduct extensive testing and evaluation of our models, including Gemini 3, our most intelligent and secure model to date.

Additionally, Google DeepMind is a proud founding member of the Frontier Model Forum, as well as the Partnership on AI, where we focus on ensuring safe and responsible development of frontier AI models and increasing collaboration on important safety issues.

We hope our expanded partnership with AISI will allow us to build more robust approaches to AI safety for the benefit not just of our own organisations, but also the wider industry and everyone who interacts with AI systems.

Stay Ahead

Explore More Insights

Stay ahead with more perspectives on cutting-edge power, infrastructure, energy, bitcoin and AI solutions. Explore these articles to uncover strategies and insights shaping the future of industries.

Cybersecurity skills matter more than headcount in an AI era: ISC2 study

Organizations have experienced oversights in cybersecurity processes and procedures (26%), been forced to put underqualified or inexperienced people into roles to cover them (25%), are lacking the time or resources to train cybersecurity staff (25%), and are dealing with misconfigured systems (24%), according to this year’s study. The report also

TotalEnergies farms out 40% participating interest in certain licenses offshore Nigeria to Chevron

@import url(‘https://fonts.googleapis.com/css2?family=Inter:[email protected]&display=swap’); a { color: var(–color-primary-main); } .ebm-page__main h1, .ebm-page__main h2, .ebm-page__main h3, .ebm-page__main h4, .ebm-page__main h5, .ebm-page__main h6 { font-family: Inter; } body { line-height: 150%; letter-spacing: 0.025em; font-family: Inter; } button, .ebm-button-wrapper { font-family: Inter; } .label-style { text-transform: uppercase; color: var(–color-grey); font-weight: 600; font-size: 0.75rem; } .caption-style

AI-driven network management gains enterprise trust

The way the full process works is that the raw data feed comes in, and machine learning is used to identify an anomaly that could be a possible incident. That’s where the generative AI agents step up. In addition to the history of similar issues, the agents also look for

Short memory supply forces Micron to abandon consumer market, prioritize enterprise

Along with that, they take a good hard look at how they are using their scarce resources, checking to see that they are selling into the most profitable markets and asking if they should be redirecting their output to more profitable businesses, Handy said. That’s what happened to Crucial. If

Crude rises after US seizes Venezuelan tanker

Oil futures erased earlier declines after US forces intercepted and seized a sanctioned oil tanker off the coast of Venezuela, a move that marks a major escalation of tensions between the two countries. West Texas Intermediate traded higher to settle above $58 after earlier dropping as much as 1%. Brent crude settled above $62. The seizure may make it much more difficult for Venezuela to send its oil overseas, as other shippers are now likely to be more reluctant to load its cargoes. Most Venezuelan oil heads to China, usually through intermediaries, at steep discounts due to sanctions risk. US President Donald Trump has suggested numerous times that the US could strike on land in Venezuela and that the country’s President Nicolas Maduro’s “days are numbered.” “Tensions are continuing to move up the escalation ladder and introduce some short-term supply risk,” said Rebecca Babin, a senior energy trader at CIBC Private Wealth Group. “That said, given the administration’s clear desire to keep oil and gasoline prices contained, the market is only assigning a small risk premium. Any potential disruption is still being viewed as short-lived.” Still, oversupply concerns continue to weigh on sentiment. The US said domestic crude production would hit a record 13.6 million barrels a day this year, adding to a flood of supply hitting the global market, while several of India’s largest refiners are buying sanctioned Russian oil, easing the worst fears of a supply threat. Ukraine carried out yet another attack on a Russian shadow-fleet oil tanker as it continues to target Moscow’s vital seaborne petroleum trade. Meantime, data from the US Energy Information Administration on Wednesday showed US inventories declined 1.8 million barrels, the first draw on stocks in around three weeks. Inventories at the Cushing, Oklahoma, storage hub rose. Data also showed a surge

South Sudan Oil Exports at Risk

South Sudan’s oil exports faced a new threat after rebels in war-torn Sudan seized facilities key to transporting crude to the Red Sea. Workers fled and operations were halted at Heglig, an oil hub in southern Sudan, as the Rapid Support Forces paramilitary group approached the area, according to people familiar with the events. The RSF, which has been battling Sudan’s army since April 2023, said on Telegram on Monday it had taken control of the “strategic Heglig” area, and was committed to securing the oil facilities. The development raises the prospect of another halt in exports of South Sudan’s Dar Blend after a disruption in mid-November. While Sudan ships little crude of its own, it’s the sole conduit for oil from landlocked South Sudan. Heglig — which lies near their border — plays a crucial role in the pipeline network. Sudan exported an average of 165,000 barrels a day of its neighbor’s crude in the past three months, according to tanker-tracking data compiled by Bloomberg. The army-backed government in Sudan didn’t respond to requests for comment. Nor did South Sudanese authorities, who rely on oil exports for the vast majority of state revenue. The RSF’s seizure of Heglig caps a string of recent territorial gains in southern Sudan for the group that’s been accused by the US of genocide in a conflict in which hundreds of thousands of people are thought to have died. The World Health Organization on Monday said drone strikes on a kindergarten and a nearby hospital in South Kordofan on Dec. 4 had killed 114 people, including 63 children. 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.

Exxon CFO to Retire

Kathy Mikells, the first outsider to join Exxon Mobil Corp.’s inner circle of top executives, will retire next year as she battles a serious but non-life threatening health condition. Mikells, 60, joined Exxon in 2021 when the Texas oil giant was under pressure from shareholders to improve financial performance, diversify its leadership and build a low-carbon business. She will retire on Feb. 1 to focus on her health, Chief Executive Officer Darren Woods said in a presentation to investors Tuesday. She will be replaced by Neil Hansen, a 25-year Exxon veteran who leads the company’s global business solutions division. “In recent months Kathy has undergone a series of procedures and surgeries to address a debilitating but thankfully non-life threatening health issue,” Woods said. “While her condition has improved, it has become clear to her, and I think the rest of us, that she needs to focus fully on her recovery.” Mikells came to Exxon from beverage titan Diageo Plc and became the first female senior vice president on the company’s management committee, which oversees day-to-day operations and sets strategy. She was also the first executive to hold such a high position at Exxon without a background in oil, natural gas or chemicals. “Things are absolutely getting better, but it has been slow going, and I still have a lot of work to do with my doctors to one day get back to my usual self,” Mikells said. “I know my colleagues on the call today will recognize the sincerity of my disappointment in needing to leave this great company.” Mikells modernized Exxon’s finance function and was the first manager to hold the formal title of chief financial officer. She overhauled investor communications and provided more granular, forward-looking information to analysts and the market in general. Hansen has been prepared for

Eni Announces ‘Significant’ Find Offshore Indonesia

Eni announced, in a statement sent to Rigzone recently, a “significant gas discovery” in the Konta-1 exploration well off the coast of East Kalimantan in Indonesia. “Estimates indicate 600 billion cubic feet of gas initially in place (GIIP) with a potential upside beyond one trillion cubic feet,” Eni said in the statement. The Konta-1 discovery is situated in the Muara Bakau PSC, Eni highlighted in the statement, pointing out that this is operated by the company with an 88.334 percent participating interest. Saka Energi holds the remaining 11.666 percent stake. “Konta-1 was drilled to a depth of 4,575 meters [15,009 feet] in 570 meters [1,870 feet] water depth, encountering gas in four separate sandstone reservoirs of Miocene age with good petrophysical properties that have been subject to an extensive data acquisition campaign,” Eni said in the statement. “A well production test (DST) has been successfully performed in one of the reservoirs and it flowed up to 31 million standard cubic feet per day of gas and approximately 700 barrels per day of condensate,” Eni added. “Based on the DST results the well has an estimated potential for a multi-pool gas rate of up to 80 million standard cubic feet per day of gas and about 1,600 barrels per day of condensate,” it continued. Eni noted in the statement that preliminary estimates indicate a discovered volume of 600 billion cubic feet of gas in place in the four reservoirs hit by the well trajectory. “Additional reservoir segments in the Konta Prospect area, not penetrated by the well, but with similar gas signature, may bring the overall volumes beyond one trillion cubic feet GIIP,” it added. Eni highlighted in the statement that the Konta discovery is sitting nearby existing facilities and adjacent to existing discoveries, “providing significant synergies for the development”. The

Phase 1 of Varco’s Sizing John BESS in Liverpool Reaches Full Operation

Varco Energy and Fluence Energy Inc said the first phase of their Sizing John Battery Energy Storage System (BESS) in the United Kingdom is now in full commercial operation and has entered phase 2. “The 57 MW/137.5 MWh project is located within the Mersey Ring east of Liverpool, a region known for its acute grid constraints”, a joint statement said. Sizing John Phase 1 has “one of the longest durations [2.4 hours] of any operational battery project in the UK”, the companies said. “Its longer duration will help lower overall energy costs by addressing growing congestion in the region and reducing price volatility created by rising renewable generation”. Phase 2, which will continue to involve intelligent energy storage and optimization software provider Fluence, will add 85.5 MW/201 MWh. The partners expect to start up phase 2 next year. “On energization of phase 2, the Sizing John project will rank among the largest battery energy storage systems in the UK”, the companies said. “Phase 2 will incorporate the Fluence-supplied next-generation Gridstack Pro 5000 with advanced grid-forming capabilities, providing critical support to the UK’s grid by actively regulating voltage and frequency, providing essential regional grid stability”, they said. Varco director Richard Whitmore said, “The addition of grid-forming capabilities will set a new standard for regional grid support, especially in the wake of recent Iberian Peninsula blackout”. Brian Perusse, Fluence managing director for the UK and Ireland, said, “Sizing John is a key step in bringing longer-duration storage and additional grid-forming capabilities to the UK, technologies that play a vital role in improving system resilience, unlocking greater renewable integration and reducing costs to consumers”. Sizing John is the second project by Varco, a BESS asset owner and operator backed by the Adaptogen Capital Battery Storage Fund, to start operation, according to the statement. Native

Kinder Morgan Expects to Ride on LNG, Power Demand Growth

Kinder Morgan Inc has announced adjusted earnings per share (EPS) guidance of $1.37 for 2026, with the North American pipeline operator encouraged by growth in the liquefied natural gas (LNG) and power sectors. That is an increase of eight percent versus its adjusted EPS forecast for 2025. For 2026 adjusted earnings before interest, taxes, depreciation and amortization (EBITDA), Kinder Morgan expects $8.7 billion, up four percent compared to its guidance for 2025. The outlook reflects “continued execution on expansion projects in our natural gas pipelines business segment”, chief executive Kim Dang said in an online statement. “We are projecting an annualized dividend of $1.19 for 2026, marking the ninth consecutive year of dividend increases”, Dang added. “Our year-end 2026 net debt-to-adjusted EBITDA ratio is forecast at 3.8 times, remaining at the low end of our 3.5x-4.5x target range and preserving flexibility for opportunistic investments”. The Houston, Texas-based owner of oil and gas pipelines and terminals, which also produces oil and renewable natural gas, plans nearly $3.4 billion in discretionary capital next year, “substantially funded from internally generated cash flow”. Kinder Morgan president Tom Martin said, “We expect to continue benefiting from strong natural gas market fundamentals, supporting growth on our existing transportation and storage assets and creating expansion opportunities”. For the first nine months of 2025, Kinder Morgan recorded $0.91 in EPS adjusted for nonrecurring items. That was up 10 percent from the same period in 2024, according to its third-quarter report October 22. Adjusted EBITDA for January-September 2025 totaled $6.12 billion, up four percent year-on-year. Volumes transported via its gas and liquid pipelines rose year-over-year. Gas transport volumes exceeded 46 trillion British thermal units a day, while it delivered 2.12 million barrels per day of liquids (crude oil, condensate and refined products). Revenue totaled $12.43 billion, up from $11.11 billion for the

Arista goes big with campus wireless tech

In a white paper describing how VESPA works, Arista wrote: The first component of VESPA involves Arista access points creating VXLAN tunnels to Arista switches serving as WLAN Gateways…. Second, as device packets arrive via the AP, it dynamically creates an Ethernet Segment Identifier (Type 6 ESI) based on the AP’s VTEP IP address. These dynamically created tunnels can scale to 30K ESI’s spread across paired switches in the cluster which provide active/active load sharing (performance+HA) to the APs. Third, the gateway switches use Type 2 EVPN NLRI (Network Layer Reachability Information) to learn and exchange end point MAC addresses across the cluster. … With this architecture, adding more EVPN WLAN gateways scales both AP and user connections, to tens of thousands of end points. To manage the forwarding information for hundreds of thousands of clients (e.g: FIB next hop and rewrite) would prove very complex and expensive if using conventional networking solutions. Arista’s innovation is to distribute this function across the WiFi access points with a unique MAC Rewrite Offload feature (MRO). With MRO, the access point is responsible for servicing mobile client ARP requests (using its own mac address), building a localized MAC-IP binding table, and forwarding client IP addresses to the WLAN gateways with the APs MAC address. The WLAN Gateways therefore only learns one (MAC) address for all the clients associated with the AP. This improves the gateway’s scaling from 10X to 100X, allowing these cost effective gateways to support hundreds of thousands of clients attached to the APs. AVA system gets a boost In addition to the new wireless technology, Arista is also bolstering the capabilities of its natural-language, generative AI-based Autonomous Virtual Assist (AVA) system for delivering network insights and AIOps. AVA is aimed at providing an intelligent assistant that’s not there to replace

Most significant networking acquisitions of 2025

Cisco makes two AI deals: EzDubs and NeuralFabric Last month Cisco completed its acquisition of EzDubs, a privately held AI software company with speech-to-speech translation technology. EzDubs translates conversations across 31 languages and will accelerate Cisco’s delivery of next-generation features, such as live voice translation that preserves the characteristics of speech, the vendor stated. Cisco plans to incorporate EzDubs’ technology in its Cisco Collaboration portfolio. Also in November, Cisco bought AI platform company NeuralFabric, which offers a generative AI platform that lets organizations develop domain-specific small language models using their own proprietary data. Coreweave buys Core Scientific Nvidia-backed AI cloud provider CoreWeave acquired crypto miner Core Scientific for about $9 billion, giving it access to 1.3 gigawatts of contracted power to support growing demand for AI and high-performance computing workloads. CoreWeave said the deal augments its vertical integration by expanding its owned and operated data center footprint, allowing it to scale GPU-powered services for enterprise and research customers. F5 picks up three: CalypsoAI, Fletch and MantisNet F5 acquired Dublin, Ireland-based CalypsoAI for $180 million. CalypsoAI’s platform creates what the company calls an Inference Perimeter that protects across models, vendors, and environments. F5 says it will integrate CalypsoAI’s adaptive AI security capabilities into its F5 Application Delivery and Security Platform (ADSP). F5’s ADSP also stands to gain from F5’s acquisition of agentic AI and threat management startup Fletch. Fletch’s technology turns external threat intelligence and internal logs into real-time, prioritized insights; its agentic AI capabilities will be integrated into ADSP, according to F5. Lastly, F5 grabbed startup MantisNet to enhance cloud-native observability in F5’s ADSP. MantisNet leverages extended Berkeley Packet Filer (eBPF)-powered, kernel-level telemetry to provide real-time insights into encrypted protocol activity and allow organizations “to gain visibility into even the most elusive traffic, all without performance overhead,” according to an F5 blog

Aviz Networks launches enterprise-grade community SONiC distribution

First, the company enabled FRR (Free Range Routing) features that exist in the community code but aren’t consistently implemented across different ASICs. VRRP (Virtual Router Redudancy Protocol) provides router redundancy for high availability. Spanning tree variants prevent network loops in layer 2 topologies. MLAG allows two switches to act as a single logical device for link aggregation. EVPN enhancements support layer 2 and layer 3 VPN services over VXLAN overlays. These protocols work differently depending on the underlying silicon, so Aviz normalized their implementation across Broadcom, Nvidia, Cisco and Marvell chips. Second, Aviz fixed bugs discovered in production deployments. One customer deployed community SONiC with OpenStack and started migrating virtual machines between hosts. The network fabric couldn’t handle the workload and broke. Aviz identified the failure modes and patched them. Third, Aviz built a software component that normalizes monitoring data across vendors. Broadcom’s Tomahawk ASIC generates different telemetry formats than Nvidia’s Spectrum or Cisco’s Silicon One. Network operators need consistent data for troubleshooting and capacity planning. The software collects ASIC-specific logs and network operating system telemetry, then translates them into a standardized format that works the same way regardless of which silicon vendor’s chips are running in the switches. Validated for enterprise deployment scenarios The distribution supports common enterprise network architectures. IP CLOS provides the leaf-spine topology used in modern data centers for predictable latency and scalability. EVPN/VXLAN creates layer 2 and layer 3 overlay networks that span physical network boundaries. MLAG configurations provide link redundancy without spanning tree limitations. Aviz provides validated runbooks for these deployments across data center, edge and AI fabric use cases.

US approves Nvidia H200 exports to China, raising questions about enterprise GPU supply

Shifting demand scenarios What remains unclear is how much demand Chinese firms will actually generate, given Beijing’s recent efforts to steer its tech companies away from US chips. Charlie Dai, VP and principal analyst at Forrester, said renewed H200 access is likely to have only a modest impact on global supply, as China is prioritizing domestic AI chips and the H200 remains below Nvidia’s latest Blackwell-class systems in performance and appeal. “While some allocation pressure may emerge, most enterprise customers outside China will see minimal disruption in pricing or lead times over the next few quarters,” Dai added. Neil Shah, VP for research and partner at Counterpoint Research, agreed that demand may not surge, citing structural shifts in China’s AI ecosystem. “The Chinese ecosystem is catching up fast, from semi to stack, with models optimized on the silicon and software,” Shah said. Chinese enterprises might think twice before adopting a US AI server stack, he said. Others caution that even selective demand from China could tighten global allocation at a time when supply of high-end accelerators remains stretched, and data center deployments continue to rise.

What does Arm need to do to gain enterprise acceptance?

But in 2017, AMD released the Zen architecture, which was equal if not superior to the Intel architecture. Zen made AMD competitive, and it fueled an explosive rebirth for a company that was near death a few years prior. AMD now has about 30% market share, while Intel suffers from a loss of technology as well as corporate leadership. Now, customers have a choice of Intel or AMD, and they don’t have to worry about porting their applications to a new platform like they would have to do if they switched to Arm. Analysts weigh in on Arm Tim Crawford sees no demand for Arm in the data center. Crawford is president of AVOA, a CIO consultancy. In his role, he talks to IT professionals all the time, but he’s not hearing much interest in Arm. “I don’t see Arm really making a dent, ever, into the general-purpose processor space,” Crawford said. “I think the opportunity for Arm is special applications and special silicon. If you look at the major cloud providers, their custom silicon is specifically built to do training or optimized to do inference. Arm is kind of in the same situation in the sense that it has to be optimized.” “The problem [for Arm] is that there’s not necessarily a need to fulfill at this point in time,” said Rob Enderle, principal analyst with The Enderle Group. “Obviously, there’s always room for other solutions, but Arm is still going to face the challenge of software compatibility.” And therein lies what may be Arm’s greatest challenge: software compatibility. Software doesn’t care (usually) if it’s on Intel or AMD, because both use the x86 architecture, with some differences in extensions. But Arm is a whole new platform, and that requires porting and testing. Enterprises generally don’t like disruption —

Intel decides to keep networking business after all

That doesn’t explain why Intel made the decision to pursue spin-off in the first place. In July, NEX chief Sachin Katti issued a memo that outlined plans to establish key elements of the Networking and Communications business as a stand-alone company. It looked like a done deal, experts said. Jim Hines, research director for enabling technologies and semiconductors at IDC, declined to speculate on whether Intel could get a decent offer but noted NEX is losing ground. IDC estimates Intel’s market share in overall semiconductors at 6.8% in Q3 2025, which is down from 7.4% for the full year 2024 and 9.2% for the full year 2023. Intel’s course reversal “is a positive for Intel in the long term, and recent improvements in its financial situation may have contributed to the decision to keep NEX in house,” he said. When Tan took over as CEO earlier this year, prioritized strengthening the balance sheet and bringing a greater focus on execution. Divest NEX was aligned with these priorities, but since then, Intel has secured investments from the US Government, Nvidia and SoftBank that have reduced the need to raise cash through other means, Hines notes. “The NEX business will prove to be a strategic asset for Intel as it looks to protect and expand its position in the AI datacenter market. Success in this market now requires processor suppliers to offer a full-stack solution, not just silicon. Scale-up and scale-out networking solutions are a key piece of the package, and Intel will be able to leverage its NEX technologies and software, including silicon photonics, to develop differentiated product offerings in this space,” Hines said.

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.

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

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

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

Stay Ahead, Stay ONMINE