The aim, said Gogia, “is continuity, not cost efficiency. These deals are forward leaning, relying on revenue forecasts that remain speculative. In that context, OpenAI must continue to draw heavily on outside capital, whether through venture rounds, debt, or a future public offering.” He pointed out, “the company’s recent legal and corporate restructuring was designed to open the doors to that capital. Removing Microsoft’s exclusivity makes room for more vendors but also signals that no one provider can meet OpenAI’s demands. In several cases, suppliers are stepping in with financing arrangements that link product sales to future performance. While these strategies help close funding gaps, they introduce fragility. What looks like revenue is often pre-paid consumption, not realized margin.” Execution risks, he said, add to the concern. “Building and energizing enough data centers to meet OpenAI’s projected needs is not a function of ambition alone. It requires grid access, cooling capacity, and regional stability. Microsoft has acknowledged that it lacks the power infrastructure to fully deploy the GPUs it owns. Without physical readiness, all of these agreements sit on shaky ground.” Lots of equity swapping going on Scott Bickley, advisory fellow at Info-Tech Research Group, said he has not only been astounded by the funding announcements over the last few months, but is also appalled, primarily, he said, “because of the disconnect to what this does to the underlying technology stocks and their market prices versus where the technology is at from a development and ROI perspective … and from a boots on the ground perspective.” He added that while the financial pledges involve “huge, staggering numbers, most of them are tied up in ways that are not necessarily going to require all the cash to come from OpenAI. In a lot of cases, there is equity swapping. You have

“AI will be essential to the future of business and society, driving innovation that demands a network to match,” Scott Lawrence, senior vice president and chief product officer at Verizon Business said in a statement. “This deal with Amazon demonstrates our continued commitment to meet the growing demands of AI workloads for the businesses and developers building our future.” This is not the first time that two companies have partnered. Verizon has previously adopted AWS as a preferred public cloud provider for its digital transformation efforts. The collaboration also extends to joint development of private mobile edge computing solutions, delivering secure, dedicated connectivity for enterprise customers. These efforts have been targeted at industries such as manufacturing, healthcare, retail, and entertainment.

Supermicro has introduced a new business line, Data Center Building Block Solutions (DCBBS), expanding its modular approach to data center development. The offering packages servers, storage, liquid-cooling infrastructure, networking, power shelves and battery backup units (BBUs), DCIM and automation software, and on-site services into pre-validated, factory-tested bundles designed to accelerate time-to-online (TTO) and improve long-term serviceability. This move represents a significant step beyond traditional rack integration; a shift toward a one-stop, data-center-scale platform aimed squarely at the hyperscale and AI factory market. By providing a single point of accountability across IT, power, and thermal domains, Supermicro’s model enables faster deployments and reduces integration risk—the modern equivalent of a “single throat to choke” for data center operators racing to bring GB200/NVL72-class racks online. What’s New in DCBBS DCBBS extends Supermicro’s modular design philosophy to an integrated catalog of facility-adjacent building blocks, not just IT nodes. By including critical supporting infrastructure—cooling, power, networking, and lifecycle software—the platform helps operators bring new capacity online more quickly and predictably. According to Supermicro, DCBBS encompasses: Multi-vendor AI system support: Compatibility with NVIDIA, AMD, and Intel architectures, featuring Supermicro-designed cold plates that dissipate up to 98% of component-level heat. In-rack liquid-cooling designs: Coolant distribution manifolds (CDMs) and CDUs rated up to 250 kW, supporting 45 °C liquids, alongside rear-door heat exchangers, 800 GbE switches (51.2 Tb/s), 33 kW power shelves, and 48 V battery backup units. Liquid-to-Air (L2A) sidecars: Each row can reject up to 200 kW of heat without modifying existing building hydronics—an especially practical design for air-to-liquid retrofits. Automation and management software: SuperCloud Composer for rack-scale and liquid-cooling lifecycle management SuperCloud Automation Center for firmware, OS, Kubernetes, and AI pipeline enablement Developer Experience Console for self-service workflows and orchestration End-to-end services: Design, validation, and on-site deployment options—including four-hour response service levels—for both greenfield builds

New Acquisitions and Partner Awards Vertiv’s third-quarter financial performance was underscored by a series of strategic acquisitions and ecosystem recognitions that expand the company’s technological capabilities and market reach amid AI-driven demand. Acquisition of Waylay NV: AI and Hyperautomation for Infrastructure Intelligence On August 26, Vertiv announced its acquisition of Waylay NV, a Belgium-based developer of generative AI and hyperautomation software. The move bolsters Vertiv’s portfolio with AI-driven monitoring, predictive services, and performance optimization for digital infrastructure. Waylay’s automation platform integrates real-time analytics, orchestration, and workflow automation across diverse connected assets and cloud services—enabling predictive maintenance, uptime optimization, and energy management across power and cooling systems. “With the addition of Waylay’s technology and software-focused team, Vertiv will accelerate its vision of intelligent infrastructure—data-driven, proactive, and optimized for the world’s most demanding environments,” said CEO Giordano Albertazzi. Completion of Great Lakes Acquisition: Expanding White Space Integration Just days earlier, as alluded to above, Vertiv finalized its $200 million acquisition of Great Lakes Data Racks & Cabinets, a U.S.-based manufacturer of enclosures and integrated rack systems. The addition expands Vertiv’s capabilities in high-density, factory-integrated white space solutions; bridging power, cooling, and IT enclosures for hyperscale and edge data centers alike. Great Lakes’ U.S. and European manufacturing footprint complements Vertiv’s global reach, supporting faster deployment cycles and expanded configuration flexibility.  Albertazzi noted that the acquisition “enhances our ability to deliver comprehensive infrastructure solutions, furthering Vertiv’s capabilities to customize at scale and configure at speed for AI and high-density computing environments.” 2024 Partner Awards: Recognizing the Ecosystem Behind Growth Vertiv also spotlighted its partner ecosystem in August with its 2024 North America Partner Awards. The company recognized 11 partners for 2024 performance, growth, and AI execution across segments: Partner of the Year – SHI for launching a customer-facing high-density AI & Cyber Labs featuring

The race to make quantum computing practical – and commercially consequential – took a major step forward this fall, as Boston-based QuEra Computing announced new research milestones, expanded strategic funding, and an accelerating roadmap for hybrid quantum-classical supercomputing. QuEra’s Chief Commercial Officer Yuval Boger joined the Data Center Frontier Show to discuss how neutral-atom quantum systems are moving from research labs into high-performance computing centers and cloud environments worldwide. NVIDIA Joins Google in Backing QuEra’s $230 Million Round In early September, QuEra disclosed that NVentures, NVIDIA’s venture arm, has joined Google and others in expanding its $230 million Series B round. The investment deepens what has already been one of the most active collaborations between quantum and accelerated-computing companies. “We already work with NVIDIA, pairing our scalable neutral-atom architecture with its accelerated-computing stack to speed the arrival of useful, fault-tolerant quantum machines,” said QuEra CEO Andy Ory. “The decision to invest in us underscores our shared belief that hybrid quantum-classical systems will unlock meaningful value for customers sooner than many expect.” The partnership spans hardware, software, and go-to-market initiatives. QuEra’s neutral-atom machines are being integrated into NVIDIA’s CUDA-Q software platform for hybrid workloads, while the two companies collaborate at the NVIDIA Accelerated Quantum Center (NVAQC) in Boston, linking QuEra hardware with NVIDIA’s GB200 NVL72 GPU clusters for simulation and quantum-error-decoder research. Meanwhile, at Japan’s AIST ABCI-Q supercomputing center, QuEra’s Gemini-class quantum computer now operates beside more than 2,000 H100 GPUs, serving as a national testbed for hybrid workflows. A jointly developed transformer-based decoder running on NVIDIA’s GPUs has already outperformed classical maximum-likelihood error-correction models, marking a concrete step toward practical fault-tolerant quantum computing. For NVIDIA, the move signals conviction that quantum processing units (QPUs) will one day complement GPUs inside large-scale data centers. For QuEra, it widens access to the

In the evolving landscape of artificial-intelligence infrastructure, a singular truth is emerging: access to cutting-edge silicon and massive GPU clusters is no longer enough by itself. For companies chasing the frontier of multi-trillion-parameter model training and agentic AI deployment, the bottleneck increasingly lies not just in compute, but in the seamless integration of compute + power + data center scale. The latest chapter in this story is the collaboration between CoreWeave and Poolside, culminating in the launch of Project Horizon, a 2-gigawatt AI-campus build in West Texas. Setting the Stage: Who’s Involved, and Why It Matters CoreWeave (NASDAQ: CRWV) has positioned itself as “The Essential Cloud for AI™” — a company founded in 2017, publicly listed in March 2025, and aggressively building out its footprint of ultra-high-performance infrastructure.  One of its strategic moves: in July 2025 CoreWeave struck a definitive agreement to acquire Core Scientific (NASDAQ: CORZ) in an all-stock transaction. Through that deal, CoreWeave gains grip over approximately 1.3 GW of gross power across Core Scientific’s nationwide data center footprint, plus more than 1 GW of expansion potential.  That acquisition underlines a broader trend: AI-specialist clouds are no longer renting space and power; they’re working to own or tightly control it. Poolside, founded in 2023, is a foundation-model company with an ambitious mission: building artificial general intelligence (AGI) and deploying enterprise-scale agents.  According to Poolside’s blog: “When people ask what it takes to build frontier AI … the focus is usually on the model … but that’s only half the story. The other half is infrastructure. If you don’t control your infrastructure, you don’t control your destiny—and you don’t have a shot at the frontier.”  Simply put: if you’re chasing multi-trillion-parameter models, you need both the compute horsepower and the power infrastructure; and ideally, tight vertical integration. Together, the