‘Nomads at the Summit’ Podcasts – Recorded Live at DCF Trends Summit 2025

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‘Nomads at the Summit’ Podcasts – Recorded Live at DCF Trends Summit 2025

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Welcome to Nomads at the Summit, a new podcast series from Data Center Frontier in partnership with the Nomad Futurist Foundation. Recorded live at the 2025 Data Center Frontier Trends Summit (Aug. 26-28), here we sit down with industry leaders, innovators, and change-makers shaping the future of digital infrastructure.

Join hosts Nabeel Mahmood and Phillip Koblence of Nomad Futurist, alongside DCF editorial leadership including Editor at Large Melissa Farney and Senior Editor David Chernicoff, for these candid conversations that highlight the ideas, talent, and technologies driving the next chapter of the data center industry.

Whether you attended the DCF Trends Summit in person or are just now tuning in from afar, Nomads at the Summit gives you a behind-the-scenes look at the people and innovations defining what’s next in digital infrastructure.

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EPISODE LIST

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Waste Heat to Water – The Path Towards Water Positive Data Centers

In this DCF Trends-Nomads at the Summit Podcast episode, Matt Grandbois, Vice President at AirJoule, introduces a game-changing approach to one of the data center industry’s most pressing challenges: water sustainability. As power-hungry, high-density environments collide with growing water scarcity concerns, Grandbois lays out a compelling vision for water-positive data centers—facilities that produce more water than they consume. Leveraging AirJoule’s advanced atmospheric water harvesting technology, he explains how waste heat, typically seen as a problem to mitigate, can become a valuable resource for onsite water generation. From adiabatic cooling and humidification to local water replenishment, this conversation opens up new possibilities for sustainable design, reduced PUE, and location flexibility—redefining what it means for data centers to be responsible community partners.

AI Models and their Corresponding Infrastructure Needs

In this DCF Trends-Nomads at the Summit Podcast episode, Chris James, CEO of NoesisAI, delivers a sweeping, insight-rich overview of how different classes of AI models—from LLMs and RAG to vision AI and scientific workloads—are driving a new wave of infrastructure decisions across the data center landscape. With a sharp focus on the diverging needs of training vs. inference, James breaks down what it takes to support today’s AI—from GPU-intensive clusters with high-speed interconnects and liquid cooling to inference-optimized, edge-deployed accelerators. He also explores the rapidly shifting hardware ecosystem, including the rise of custom silicon, heterogeneous computing, and where the battle between NVIDIA, AMD, Intel, and hyperscaler-designed chips is headed. Whether you’re designing for scalability, sustainability, or the bleeding edge, this conversation offers a field guide to the infrastructure behind intelligent computing.

Technology Infrastructure Considerations for Hyperscale, MTDC, Wholesale: A Consultant Engineer’s Perspective

Speakers:
Joseph Ford, Senior Associate – Technology, Bala Consulting Engineers
Eric Klaiber, Data Center Design Manager, Bala Consulting Engineers

In this DCF Trends-Nomads at the Summit Podcast episode, Joseph Ford and Eric Klaiber of Bala Consulting Engineers offer a consultant engineer’s hard-won perspective on the complex realities of designing infrastructure for hyperscale, MTDC, and wholesale data centers. Drawing on years of field experience, they dig into the nuanced choreography required to align incoming duct banks, meet-me room layouts, and overlapping network systems—all while staying within the spatial constraints driven by power and cooling demands. This candid conversation highlights what it really takes to create design harmony across client expectations, design teams, and contractors, with insights into space planning, coordination strategy, and the delicate balance of infrastructure coexistence that underpins modern high-performance facilities.

How Medium Voltage UPS Architectures are Redefining Data Center Design to Meet the Demands of AI Densification

Speakers:
Mike Klassen, Director of Business Development, ZincFive
Sugam Patel, VP of Product Management, DG Matrix

In this DCF Trends-Nomads at the Summit Podcast episode, experts from ZincFive and DG Matrix unpack how medium voltage (MV) UPS architectures are redefining the way data centers power up for AI. As AI densification pushes traditional infrastructure to its limits, MV UPS solutions offer a path forward—boosting efficiency, reducing heat and losses, and reclaiming floor space for compute. The conversation delves into how higher voltage translates into smarter, more scalable designs that not only meet the demands of today’s high-performance AI workloads but also future-proof facilities for what’s coming next. From design frameworks to deployment strategies, Smith and Inam provide a grounded, technical look at the UPS shift already underway.

Infrastructure Masons CEO Santiago Suinaga Talks Digital Infrastructure Frontiers

In this DCF Trends-Nomads at the Summit Podcast episode, the ever-curious, future-focused podcast hosts from Data Center Frontier and Nomad Futurist reunite with Infrastructure Masons CEO Santiago Suinaga for a timely, in-depth follow-up to his impactful debut on the DCF Show. With AI infrastructure growth hitting warp speed, the conversation will dig deeper into Suinaga’s vision for how the digital infrastructure community can scale responsibly—without losing sight of net zero goals, workforce development, or supply chain accountability. Expect a candid, high-level exchange on emerging regulatory pressures, the embodied carbon challenge, and why flexible cooling and modular design must be table stakes for the AI-powered data center of the future. Suinaga will also share the latest on iMasons’ Climate Accord, job-matching platform, and new cross-sector partnerships—all aimed at fostering sustainability, equity, and innovation in an industry racing to keep pace with exponential demand.

Africa’s Digital Future: A Conversation with UVA Darden’s Tosin Fashola & Albert Odum

In this DCF Trends-Nomads at the Summit Podcast episode, the hosts of Data Center Frontier and Nomad Futurist sit down with UVA Darden MBA candidates Tosin Fashola and Albert Odum for an energizing conversation about next-generation data infrastructure—and why they believe Africa is poised to be its future epicenter. With professional backgrounds spanning data center strategy at KPMG and government-led implementations in Ghana, Tosin and Albert bring fresh, globally-minded perspectives on AI infrastructure, regional power strategy, and the role of connectivity in economic transformation. Expect a wide-ranging dialogue on the untapped potential of African markets, the roadmap to building sovereign cloud capacity and IXPs, and how a new generation of leaders is preparing to close the global digital divide—one hyperscale project at a time.

Renewable and Sovereign Energy Opportunities for Data Center Applications

In this DCF Trends-Nomads at the Summit Podcast episode, the hosts from Data Center Frontier and Nomad Futurist sit down with Adrienne Pierce, CEO of New Sun Road, to explore the emerging frontier of sovereign and renewable energy solutions for modular data center deployment. With over 1,500 microgrids under management via the company’s Stellar platform, Pierce brings a field-tested perspective on how flexible, AI-driven energy controls can empower edge and sub-10 MW data center systems—especially in regions where traditional grid infrastructure can’t keep up with AI-era demands. This discussion dives into the real-world opportunities for modular, microgrid-powered data centers to unlock new markets, reduce energy costs, and create more resilient and autonomous compute infrastructure at the edge and beyond. Expect sharp insights into what it means to decouple data center growth from utility bottlenecks—and how the right energy intelligence can accelerate both sustainability and scalability.

Mission-Critical and Data Center Challenges + 7×24 National Update

In this DCF Trends-Nomads at the Summit Podcast episode, Data Center Frontier and Nomad Futurist hosts sit down with Bob Cassiliano, Chairman & CEO of 7×24 Exchange International, for a wide-ranging conversation on the state of mission-critical infrastructure and the evolving challenges facing the data center industry. As the leader of one of the most influential organizations in the space, Cassiliano offers a national perspective on power constraints, workforce development, sustainability pressures, and the cultural shifts reshaping operations and leadership across the digital infrastructure landscape. The discussion also highlights how 7×24 Exchange continues to serve as a vital convening force for collaboration, education, and resilience in an industry tasked with powering the AI era. With decades of insight and a pulse on what’s next, Cassiliano shares where the data center sector must go to meet the moment.

Telling the Right Data Center Stories

In this DCF Trends-Nomads at the Summit Podcast episode, the Data Center Frontier and Nomad Futurist hosts engage in a dynamic, behind-the-scenes conversation with two of the most influential voices shaping digital infrastructure communications: Illisa Miller, founder of iMiller PR, and Adam Waitkunas, founder of Milldam PR. With decades of experience guiding some of the industry’s most prominent brands through launches, crises, and rebranding efforts, Miller and Waitkunas offer an unfiltered look at what it really takes to cut through the noise in a crowded, technically complex market. From telling the right story about AI and sustainability, to building trust across hyperscalers, investors, and public stakeholders, this episode explores the evolving narrative demands of the data center space—and why strategic communications is now mission-critical to business success. Expect honest reflections, practical PR wisdom, and a few war stories from the front lines of digital infrastructure storytelling.

From Liquid Cooling to Hyperscale Frontiers: A Conversation with Vertiv’s Greg Stover

In this DCF Trends-Nomads at the Summit Podcast episode, Data Center Frontier editors and Nomad Futurist hosts sit down with Greg Stover, Vertiv’s Global Director, Hi-Tech Development. The discussion delves into Stover’s work at the intersection of advanced cooling technologies, hyperscale growth, and AI-driven infrastructure design. Drawing on his experience guiding Vertiv’s strategy for high-density deployments, liquid cooling adoption, and close collaboration with hyperscalers and chipmakers, Stover offers a forward-looking perspective on how evolving compute architectures, thermal management innovations, and market forces are redefining the competitive edge in the data center industry.

Doug Recker on Edge AI, Data Centers, and Building Resilient Infrastructure

In this DCF Trends-Nomads at the Summit Podcast episode, the editors of Data Center Frontier and the hosts of Nomad Futurist sit down with Doug Recker, a telecommunications veteran and edge data center pioneer with more than 30 years of industry leadership. Today, Recker leads Duos Edge AI, driving initiatives to bring multi-access edge data centers (EDCs) to underserved communities, including schools and health facilities across the U.S. From founding Edge Presence (acquired by Ubiquity in 2023) and Colo5 Data Centers (later acquired by Cologix in 2014), to deploying more than 40 TM2500 units worldwide, Recker has consistently been at the forefront of building scalable, resilient infrastructure. His career is marked by multiple honors, including Northeast Florida’s Ultimate CEO Award and recognition among Inc. 500’s fastest-growing companies. In this conversation, Recker shares insights on the evolution of edge computing, lessons learned from decades in telecom and data centers, and how his time in the U.S. Marine Corps shaped his leadership philosophy. Tune in for a wide-ranging discussion on innovation, resilience, and the future of edge AI.

Schneider Electric’s Lovisa Tedestedt on Global Sales, Growth, and the Human Side of Data Centers

In this DCF Trends-Nomads at the Summit Podcast episode, the editors of Data Center Frontier and the hosts of Nomad Futurist sit down with Lovisa Tedestedt, Sales Executive at Schneider Electric, where she focuses on colo acquisition accounts. With more than 25 years of experience in international sales management, business development, and leadership, Lovisa has built a career defined by strong client relationships, bold growth strategies, and a passion for delivering excellence. From Sweden to China, Europe to the U.S., Lovisa brings a truly global perspective to the data center industry. In this conversation, she shares insights on strategic planning, high-stakes negotiations, and the importance of adaptability in today’s fast-changing market. Beyond her career, Lovisa talks about life outside of work as an avid hockey mom, now based in Des Moines, Iowa with her husband and two teenage children. Join us for a conversation that blends global business lessons, sales leadership, and the personal side of a career in the digital infrastructure world.

Melissa Farney & Bill Kleyman on the Future of AI and Digital Infrastructure

In this episode of the DCF Trends–Nomads at the Summit podcast, we bring together two dynamic voices shaping the future of digital infrastructure: Melissa Farney, Editor at Large for Data Center Frontier, Marketing Director for TECfusions, and an ambassador of the Nomad Futurist Foundation, and Bill Kleyman, Contributing Editor for Data Center Frontier and CEO of Apolo, who also serves as a member of the Nomad Futurist Foundation. Melissa and Bill join up for a candid discussion on the biggest trends transforming the data center and digital ecosystem. From AI-driven growth and sustainability challenges to the human capital needed to sustain the industry’s rapid expansion, they share a unique blend of editorial perspective and executive experience. This episode also dives into the mission of the Nomad Futurist Foundation: inspiring and equipping the next generation of leaders in the digital infrastructure space. Listeners will gain insights not just into market shifts, but also into the values and vision shaping the future of the field. Tune in for an engaging conversation at the intersection of thought leadership, industry transformation, and the mission to build a more resilient, inclusive digital future.

Keep pace with the fast-moving world of data centers and cloud computing by connecting with Data Center Frontier on LinkedIn, following us on X/Twitter and Facebook, as well as on BlueSky, and signing up for our weekly newsletters using the form below.

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New Supermicro BMC vulnerabilities open servers to malicious attacks on firmware

During this research, Binarly discovered a second vulnerability, CVE-2025-6198, relating to Supermicro’s X13SEM-F motherboard firmware, also rated as high severity with a CVSS score of 7.2. While CVE-2025-7937 or CVE-2025-6198 would pose major security risks in the event attackers were able to exploit them, the caveat is that to do

Cisco admins urged to patch IOS, IOS XE devices

“It requires an authenticated user, so at least it’s not an unauthenticated RCE (remote code execution),” said Shipley. The vulnerability has a high CVSS score of 7.7, “but [it’s] not the worst we’ve seen of late.” Ed Dubrovsky, chief operating officer of US-based incident response firm Cypfer, also noted that a

Pure Storage targets AI complexity with a unified data cloud, Azure integration, and embedded security

Pure Storage also expanded its AI Copilot with new features, including Portworx Pure1 AI Copilot for Kubernetes environments. The company said users can now “query Portworx clusters in the same way they interact with FlashArray systems” using natural language. The vendor also announced integration with Model Context Protocol servers, scheduled

Amazon and SAP partner on European data sovereignty platforms to offer better oversight

Other vendors also see the appeal. Adobe, Snowflake, Cisco, and MongoDB have already signed up to support the AWS Sovereign Cloud on a global basis. Two clouds better than one But what does deploying a SAP sovereign cloud inside a separate AWS sovereign cloud mean in practice? The official answer

Oil Swings as NATO and Russian Tensions Escalate

Oil fluctuated in choppy trading as tensions between Russia and NATO intensified, with European leaders warning the Kremlin that Western military alliance is ready to respond with force to violations of its airspace. West Texas Intermediate swung between gains and losses to settle near $65, after earlier falling as much as 1.4%, as European diplomats concluded that a recent Russian incursion into Estonia was a deliberate tactic ordered by Russian commanders. Those comments echo earlier remarks by US President Donald Trump, who on Wednesday said that NATO should shoot down Russian aircrafts that cross into their airspace. Russian flows have been in the spotlight over the past few weeks amid global efforts to pressure Moscow to make peace in Ukraine by targeting its energy assets. Crude received a bump earlier Thursday after Trump told Turkey’s Recep Tayyip Erdogan to “stop buying any oil from Russia,” just a day after urging Europe to stop purchasing energy from the OPEC+ member, leading oil investors to cover bearish positions. Elsewhere, US Defense Secretary Pete Hegseth ordered an urgent meeting of top military commanders for an unusual meeting early next week, fueling concerns over wider unrest that could imperil global crude flows. Still, the confluence of bearish inputs didn’t succeed in breaking out of a narrow range since early August as traders balance a bearish outlook against escalating global tensions. Market watchers led by the International Energy Agency are forecasting excess supply later in the year due to increased output from the Organization of the Petroleum Exporting Countries and its partners, as well as from outside the group. The commodity was down earlier as traders assessed future flows from Iraq’s Kurdistan to global supply chains. A landmark agreement to resume exports could return 500,000 barrels a day to the market, Foreign Minister Fuad Hussein

Trump, Orban Talk Energy

Donald Trump and Viktor Orban held a phone conversation a day after the US president said he would press the Hungarian premier to stop purchasing Russian oil. The two leaders discussed energy security, in addition to Russia’s war on Ukraine, the global economy and tariffs, Hungarian Foreign Minister Peter Szijjarto said on the sidelines of the United Nations General Assembly in New York late Wednesday. Their call came as pressure mounts on Hungary to at least reduce purchases as Western allies seek to dent Russia’s oil revenues, a major source of financing for its continuing invasion of Hungary’s eastern neighbor. On Tuesday, at a briefing with Ukrainian President Volodymyr Zelenskiy at the UN, Trump floated calling Orban to ask him to cut Hungary’s Russian oil procurements. Szijjarto publicly gave no indication that Hungary was ready to do that. Hungary, a European Union and NATO member, can’t scrap its Russian oil purchases due to “geographic and physical” reasons and Russia has been a “reliable partner,” Szijjarto told reporters after meeting his Russian counterpart Sergei Lavrov, with whom he’s maintained close contact even after Russia’s 2022 invasion. Slovakia, another landlocked EU nation neighboring Hungary, holds a similar position. Slovak Prime Minister Robert Fico said on Thursday he would send a government emissary to the US, to explain why it’s also not ready to phase out Russian energy. Facing pressure from Trump, the European Commission, the EU’s executive arm, is reviewing trade measures targeting imports of Russian oil via the Druzhba pipeline that feeds Hungary and Slovakia, Bloomberg reported on Sept. 20. EU foreign policy chief Kaja Kallas also told Bloomberg on Wednesday that the bloc should wean itself off Russian energy more quickly. Some member states which continued to buy from Moscow were “good friends of Trump,” she said, asking the US president to talk

Is nuclear fusion power for real this time? Some utilities think so.

Listen to the article 14 min This audio is auto-generated. Please let us know if you have feedback. Several utilities are exploring partnerships with nuclear fusion startups that promise to deploy the cutting edge technology at commercial scale – a feat that has eluded scientists for decades. Recent technical breakthroughs at government labs around the world have moved this milestone closer, but industry and experts are divided over how close. “We’re seeing these companies get a little more serious about their siting and deployment plans, no longer just making vague promises about getting fusion onto the grid ‘in a few years,’” said Patrick White, group lead for fusion safety and regulation with Clean Air Task Force. Inside a nuclear fusion reactor, lightweight atoms smash together under incredible heat. The energy they release drives a power conversion system similar to those found in existing thermal power plants’ generator rooms. Electricity comes out the other side. The process is energy-dense: A ton of the hydrogen isotope deuterium, one possible fusion fuel, contains the energy equivalent of 29 billion tons of coal. Commercial fusion power still exists only in theory because sustaining an earthbound atom-smashing reaction at temperatures hotter than the sun’s core is a formidable technical challenge. For years, scientists warned that commercial fusion power was always 50 years off. Utilities strike fusion partnerships following breakthroughs Now, they’re not so sure. In late 2022, the U.S. Department of Energy’s Lawrence Livermore National Laboratory said it had achieved a vital breakthrough. For the first time, scientists there had created and briefly sustained a fusion reaction that generated more energy than it consumed – a threshold called “net energy gain” or “Q>1.” Researchers and technicians in the National Ignition Facility control room at the Lawrence Livermore National Laboratory react to Energy Secretary Jennifer Granholm’s

India Pleads to Replace Russian Oil with Iranian Flows

Indian officials have again told the Trump administration that a significant reduction in Russian oil imports by the South Asian nation’s refiners would require Washington to instead allow crude purchases from sanctioned suppliers Iran and Venezuela. A delegation visiting the US this week reiterated the request in meetings with American officials, a person with knowledge of the discussions said, asking not to be identified as the talks are private. Indian representatives have emphasized that simultaneously cutting off Indian refiners’ supply from Russia, Iran and Venezuela – all major oil producers – could lead to a spike in global prices, people familiar with the negotiations added. Spokespeople for the Commerce and Oil Ministries, and the US embassy in New Delhi, didn’t immediately respond to requests seeking comment. New Delhi’s representatives traveled to the US for talks after Washington imposed crushing tariffs on the country in punishment for its oil trade with Russia. Despite the levies, the South Asian nation has maintained its crude imports from the OPEC+ producer, albeit at a lower rate. Indian Commerce Minister Piyush Goyal said this week that the country wanted to increase its purchases of American oil and gas, adding that “our energy security goals will have a very high element of US involvement.” He made the remarks in New York. Russia was forced to discount its crude after many others shunned trade with Moscow due to the war in Ukraine. Almost 90 percent of India’s oil needs are met by imports, and cheaper Russian barrels have helped to reduce the burden on its import bill. Iranian and Venezuelan oil would also be similarly discounted. India stopped buying Iranian oil in 2019, and the nation’s largest private refiner – Reliance Industries Ltd. – halted purchases of Venezuelan crude this year as the US tightened sanctions. Processors can shift to buying more Middle Eastern

Seatrium Sells AmFELS Yard to Karpower Valley

Seatrium Limited has agreed to sell its AmFELS Yard in Brownsville, Texas, for $50.4 million to Karpower Valley LLC, a Karpowership-related party. Seatrium said in a media release that this sale will allow it to improve its capital and operational efficiencies while unlocking value from one of its surplus facilities. “We have a strong and long-standing relationship with Karpowership, and are pleased to entrust the yard to a partner with whom we will continue to deepen our collaboration. Notwithstanding the divestment, the U.S. market remains important to us”, Chris Ong, Chief Executive Officer of Seatrium, said. “We will continue to leverage our global footprint and integrated One Seatrium Delivery Model to deliver world-class solutions to our U.S.-based and global customers in the offshore and energy sectors”. Seatrium said it will shift its focus in the U.S. toward engineering innovation and technological capabilities through its technology centers and offices based in Houston, Texas, as well as a service center in Vicksburg, Mississippi, to meet the changing needs of its clients. The price will be paid in cash, with $38.8 million being deferred to be paid one year following closing. The finalization of the divestment is subject to standard closing conditions, including the Port of Brownsville transferring the lease to the new owner. Seatrium said it is dedicated to finishing all current projects at AmFELS Yard by the end of 2025. To contact the author, email [email protected] 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. MORE FROM THIS AUTHOR

Sempra Infrastructure Partners Makes FID on Port Arthur LNG Phase 2

Sempra Infrastructure Partners has reached a final investment decision to advance the development, construction, and operation of phase 2 of the Port Arthur LNG project in Jefferson County, Texas. The new phase will include two natural gas liquefaction trains, one liquefied natural gas (LNG) storage tank and associated facilities with a nameplate capacity of approximately 13 million metric tons per annum (mtpa) of U.S.-produced LNG, Sempra said in a news release. Incremental project capital expenditures for the new phase are estimated at $12 billion, plus an approximate $2 billion payment for shared common facilities, the company said. Commercial operations are expected in 2030 and 2031 for Trains 3 and 4, respectively. Funding for the new phase is supported by a $7 billion equity investment led by Blackstone Credit & Insurance, together with an investor consortium including KKR, Apollo-managed funds, and Private Credit at Goldman Sachs Alternatives, for a total of 49.9 percent minority equity interest, with Sempra Infrastructure Partners retaining a 50.1 percent majority stake in the project, according to the release. Sempra Infrastructure Partners has entered into a contract with global engineering, construction and project management firm Bechtel Energy Inc., which has received full notice to proceed for the project. Bechtel’s continued involvement from the first phase is expected to “drive favorable economics and help mitigate execution risk by leveraging efficiencies and learnings across phases,” the release said. Phase 2 is subscribed with long-term offtake under 20-year sales and purchase agreements with strategic partner ConocoPhillips as anchor, and counterparties EQT, JERA Co. Inc. and Sempra Infrastructure Partners, which said it expects to enter into additional offtake agreements from time to time to enhance the overall economic value of the project. KKR Acquires Majority Interest in Sempra Infrastructure Partners Meanwhile, Sempra said it has agreed to sell a 45 percent

‘Nomads at the Summit’ Podcasts – Recorded Live at DCF Trends Summit 2025

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Equinix unveils distributed AI infrastructure targeting inferencing, cloud connectivity

Data center provider Equinix has launched its Distributed AI infrastructure, which includes a new AI-ready backbone to support high performance distributed AI deployments spanning multiple data center facilities, a global AI Proving Ground to test new solutions, and Fabric Intelligence to better support next generation enterprise workloads. Equinix designed Distributed AI from the ground up to support the scale, speed, and complexity of modern intelligent systems, such as autonomous, agentic AI capable of reasoning, acting, and learning independently. AI is inherently distributed, drawing on multiple data sources in different locations. To effectively train a model, data must be drawn from multiple locations and processed where it lies, not moved around. This requires a new kind of infrastructure that is globally distributed, deeply interconnected, and fully programmable. Distributed AI links more than 270 data centers in over 60 markets, effectively including almost all Equinix’s facilities, according to the vendor.

Cisco expands its quantum networking portfolio with new software prototypes

The software stack supports three other prototype applications to help enable quantum networking and the data center. The first is what Pandey describes as a network-aware distributed quantum compiler that lets quantum algorithms run across multiple networked processors. “The compiler is the piece of technology you need to enable practical, pragmatic, distributed quantum computing. It takes a quantum workload, a quantum circuit, and it partitions it so that it runs in a distributed environment, in a connected set of qubits or quantum compute nodes,” Pandey said. Significantly, it’s multivendor; the quantum compute nodes can be from the same vendor or from other vendors, such as IBM: “It could be as messy a brownfield, heterogeneous environment as you want. It doesn’t matter to the compiler, which will take an algorithm, partition it across any heterogeneous, brownfield environment,” Pandey said. “What makes it unique, and an industry-first, is that it accounts for quantum interconnect requirements between processors and supports distributed quantum error correction. Existing compilers target circuits for only single computers,” Pandey stated. “Ours compiles circuits for network-connected computers potentially made of heterogeneous quantum compute technologies and can distribute that partitioned circuit across an entire data center of processors, all connected through a quantum network.” The distributed quantum error correction is a key feature of the software. Error correction ensures the accuracy and reliability of quantum computations and is a challenge for any distributed or standalone network. The Cisco software in this case understands the error correction intricacies of each of the quantum computing modalities in the network, and “we can ensure that those are carried over from node to node, giving us a distributed or a holistic view of the entire distributed environment and result,” Pandey said. In addition, “we are developing our own algorithms [to determine] the best way, using our network, to do a

NVIDIA and OpenAI Forge $100B Alliance to Power the Next AI Revolution

The new strategic partnership between OpenAI and NVIDIA, formalized via a letter of intent in September 2025, is designed to both power and finance the next generation of OpenAI’s compute infrastructure, with initial deployments expected in the second half of 2026. According to the joint press release, both parties position this as “the biggest AI infrastructure deployment in history,” explicitly aimed at training and running OpenAI’s next-generation models. At a high level: The target scale is 10 gigawatts (GW) or more of deployed compute capacity, realized via NVIDIA systems (comprising millions of GPUs). The first phase (1 GW) is slated for the second half of 2026, built on the forthcoming Vera Rubin platform. NVIDIA will progressively invest up to $100 billion into OpenAI, contingent on deployment of capacity in stages. An initial $10 billion investment from NVIDIA is tied to the execution of a definitive purchase agreement for the first gigawatt of systems. The equity stake NVIDIA will acquire is described as non-voting / non-controlling, meaning it gives financial skin in the game without governance control. From a strategic standpoint, tying investment to capacity deployment helps OpenAI lock in capital and hardware over a long horizon, mitigating supply-chain and financing risk. With compute frequently cited as a binding constraint on advancing models, this kind of staged, anchored commitment gives OpenAI a more predictable growth path (at least in theory; that said, the precise economic terms and risk-sharing remain to be fully disclosed.) Press statements emphasize that millions of GPUs will ultimately be involved, and that co-optimization of NVIDIA’s hardware with OpenAI’s software/stack will be a key feature of the collaboration. Importantly, this deal also fits into OpenAI’s broader strategy of diversifying infrastructure partnerships beyond any single cloud provider. Microsoft remains a central backer and collaborator, but this NVIDIA tie-up further

Balancing AI’s opportunities and challenges to serve enterprises

AI has taken the technology industry by storm, with enterprises deploying emerging applications to create business value. Amid this shift, operators are leveraging network automation, optical innovation and more to support enterprise AI use cases. Still, the technology ecosystem must balance AI’s opportunities with its challenges. While AI can improve operations, it can also leave companies more vulnerable to cyberattacks. As organizations deploy more AI tools and employees increasingly use them, the overall attack surface expands and opens more security gaps. This article explores how internet carriers are building their networks to support enterprises, while also discussing how operators are establishing trust with customers. Table stakes: reliability, diversity and reach AI’s requirements are similar to content distribution, cloud networking and previous industry shifts, but place even greater pressure on carrier-delivered enterprise network services. In these services, network diversity is integral, allowing carriers to eliminate single points of failure in the event of an outage, then quickly reroute traffic through the next best available path. This improved reliability is vital for enabling real-time enterprise AI operations amid increased instances of network disruption due to geopolitical sabotage or accidental damage. As more hyperscalers build sprawling AI data center campuses, network reach will also prove even more crucial. By continuously expanding their network footprints, carriers can help enterprises access these sites no matter where they’re located, with operators’ high-capacity connectivity infrastructure facilitating the transfer of massive data volumes between these campuses. Similar to how content distribution networks rely on a robust network underlay, backbone connectivity provides the high-capacity, long-haul transport underpinning the delivery of AI inferencing responses. While the backbone itself does not cache or deliver these responses, its densely interconnected networks ensure that this AI traffic reaches regional and access networks, which then distribute responses to end users. Lightspeed: optical innovation With

Microsoft’s new cooling tech targets AI’s thermal bottleneck as hyperscalers hit power ceilings

Rising thermal pressure on AI hardware AI workloads and high-performance computing have placed unprecedented strain on data center infrastructure. Thermal dissipation has emerged as one of the toughest bottlenecks, with traditional methods such as airflow and cold plates increasingly unable to keep pace with new generations of silicon. “Modern accelerators are throwing out thermal loads that air systems simply cannot contain, and even advanced water loops are straining. The immediate issues are not only the soaring TDP of GPUs, but also grid delays, water scarcity, and the inability of legacy air-cooled halls to absorb racks running at 80 or 100 kilowatts,” said Sanchit Vir Gogia, CEO and chief analyst at Greyhound Research. “Cold plates and immersion tanks have extended the runway, but only marginally. They still suffer from the resistance of thermal interfaces that smother heat at the die. The friction lies in the last metre of the thermal path, between junction and package, and that is where performance is being squandered.” Cooling costs: the next data center budget crisis Cooling isn’t just a technical challenge but also an economic one. Data centers spend heavily to manage the immense heat generated by servers, networking gear, and GPUs. Hence, the cost of cooling a data center is also a significant expense. “As per 2025 AI infra buildouts TCO analysis, over 45%-47% of data center power budget typically goes into cooling, which could further expand to 65%-70% without advancement in cooling method efficiency,” said Danish Faruqui, CEO at Fab Economics. “In 2024, Nvidia Hopper H100 had 700 watts of power requirements per GPU, which scaled in 2025 to double with Blackwell B200 and Blackwell Ultra B300 to 1000 W and 1400 watts per GPU. Going forward in 2026, it will again more than double by Rubin and Rubin Ultra GPU to 1800W

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