AMD is escalating its challenge to Nvidia with Helios, a rack-scale AI system that puts the company squarely into the race to define how the next generation of AI factories are built. Unveiled in production form at AMD’s Advancing AI 2026 event in San Francisco, Helios combines 72 Instinct MI455X GPUs with sixth-generation EPYC “Venice” CPUs, Pensando networking and AMD’s ROCm software stack. The significance goes beyond another generation of faster accelerators. Like Nvidia’s Vera Rubin platform, Helios treats the rack as an integrated compute system in which GPUs, CPUs, memory, networking, power delivery and cooling increasingly have to be engineered together. For data center operators, that means the competitive battle between the two chip companies is moving directly into infrastructure design. AMD said Helios is now in production, with deployments beginning during the second half of 2026. The Rack Becomes the System Helios is built around AMD’s Instinct MI455X, a liquid-cooled accelerator based on the company’s CDNA 5 architecture and equipped with HBM4 memory. A complete Helios rack delivers 72 GPUs along with EPYC host CPUs and Pensando networking for front-end, scale-up and scale-out traffic. AMD is positioning the platform for both large-scale training and increasingly important inference workloads. AMD says Helios can deliver up to 30% more inference tokens per dollar than a competing system. The company also claims the MI455X provides more peak AI compute and substantially greater memory capacity than Nvidia’s Rubin GPU. Those numbers are AMD benchmarks rather than independent comparisons. But the larger architecture may matter more than the percentages. AI infrastructure is rapidly moving beyond the model of servers being installed as largely independent pieces of IT equipment. Accelerators have to exchange enormous volumes of data with each other while CPUs orchestrate workloads and networking connects increasingly large clusters across rows, halls and

Moses Lake and the Quincy Effect Moses Lake should not be understood as an isolated rural data center project. It sits within the larger Grant County infrastructure ecosystem that helped make nearby Quincy one of the defining hyperscale markets of the cloud era. Keel has called Moses Lake “adjacent to one of the most proven data center markets in the United States,” noting that hyperscale infrastructure has operated around Quincy for nearly two decades. In its Q1 remarks, management argued that increasingly constrained regional power leaves operators seeking incremental Pacific Northwest capacity with fewer options. The Grant County Economic Development Council’s data center inventory includes Microsoft, NTT Data, Sabey, Vantage, Intuit and other operators. The organization counts more than 1.5 million square feet of data center operations in the county and points to a diverse fiber network and Grant County PUD’s Columbia River hydroelectric resources as core advantages. That existing cluster changes the equation for an 18-MW project. The headline AI developments of 2026 are increasingly measured in hundreds of megawatts or gigawatts. But another market exists underneath those megacampus announcements: operators that need tens of megawatts in the right geography on a timeline measured in quarters rather than many years. An 18-MW facility with power, fiber, equipment and construction underway can therefore be strategically more relevant than its relatively modest capacity suggests. Keel had previously secured an option for another 10 MW near Moses Lake, but management said during its second-quarter call that it has relinquished that option and is now focused exclusively on the existing 18 MW. The decision further distinguishes Moses Lake from the industry’s race to advertise ever-larger pipelines. This project is about getting capacity online. A Second Life for Crypto Power That may ultimately be the larger Moses Lake story. Bitcoin miners assembled portfolios around

AI Infrastructure’s New Calculus: Speed, Quality and the Race to Revenue NASHVILLE — The defining question in data center development has become brutally simple: How quickly can a site get to revenue? Power availability sits at the center of that calculation. But as AI pushes development into new geographies and compresses construction schedules, an increasingly complicated set of infrastructure dependencies sits behind the megawatts — equipment, suppliers, construction capacity, fiber, optical connectivity, workforce and the quality systems needed to make all of it work reliably. That tension framed a Data Center Frontier-led fireside discussion at EndeavorB2B’s ISE Expo 2026 between Sean Farney, Vice President of Data Center Strategy at JLL, and Dave Stehlin, CEO of the Telecommunications Industry Association (TIA). The conversation began with a new data center quality initiative. It quickly expanded into something larger: an examination of what happens when time to revenue becomes the organizing principle for an entire infrastructure industry. “There is absolutely, positively no room for pause right now,” Farney said. DCE 9000 Meets the AI Buildout For TIA, the answer begins with a problem Google brought to the association last year. According to Stehlin, Google was seeing recurring quality and delivery problems among operational technology suppliers — the companies providing equipment such as generators, cooling systems and other physical infrastructure required to make a data center operate. TIA responded by developing DCE 9000, or Data Center Excellence 9000, a third-party-certifiable quality management standard for the data center infrastructure supply chain. Stehlin said more than 70 companies are now participating in the effort, ranging from hyperscalers and data center operators to major infrastructure manufacturers. The first draft is expected in September. That is an unusually compressed development cycle for an industry standard. “Typically standards take five years to get implemented,” Stehlin said. “In nine months, we’re

Moving Beyond Speculation The answer is not simply earlier marketing campaigns or more aggressive public relations programs. Effective engagement requires understanding local concerns, motivations and political dynamics—and recognizing when community opposition reflects a durable constraint rather than a communications problem. We need to realize when no means no, and not interpret it as “try harder.” Phantom perception also can’t be handled by any one operator in any one market; this must be a collective, such as a crowd-sourced data platform, market by market. What our industry needs are clearer frameworks for evaluating digital infrastructure against these additional community-readiness criteria, because speculation is increasingly filling information gaps before formal projects reach the public process. Organizations such as OIX have begun working toward that objective. Its Digital Infrastructure Framework is modeled on traditional master planning and is intended to help communities evaluate what infrastructure they have, what they need and what they want as they plan for future technology requirements. The framework includes assessment criteria spanning investment readiness, policy, risk, sustainability and resilience. Greater transparency can narrow the gap between perception and reality. But greater transparency will not eliminate speculation, and unfortunately, it also won’t eliminate fear. Large infrastructure projects have always attracted public interest and scrutiny, and data centers are unlikely to become invisible again as AI demand accelerates. The question is how the industry responds to that visibility. The Next Stage of Data Center Development Community reaction to perceived data center development represents another potential source of site-selection intelligence. If communities begin reacting to a project before a developer has formally advanced one, that response can offer an early indication of whether a market is receptive to large-scale digital infrastructure or already approaching its political limit. This gives operators and investors another axis to measure: not just megawatts, fiber routes,

The customer agreement expanded an earlier commitment and includes dedicated high-speed storage and CPUs in addition to GPUs. Corvex initially delivered capacity during the first quarter and continued deployment through the second and third quarters. By its Aug. 14 earnings update, the company said the multi-year Blackwell agreement had been fully delivered. Corvex reported approximately $22 million in contracted annualized recurring revenue from compute that was live and accepted by customers. The expansion was financed through debt, customer prepayments and cash on hand rather than additional equity issuance. But the most noteworthy aspect of the project may be the deployment itself. Corvex installed high-density, liquid-cooled NVIDIA HGX B200 systems inside an existing air-cooled data center and says it commissioned the capacity approximately two weeks after the equipment arrived. Instead of rebuilding the facility around a central liquid-cooling system, Corvex worked with Lenovo to use Lenovo Neptune liquid-to-air cooling technology. Liquid removes heat from the servers and transfers it to the existing air-cooled facility infrastructure. The cluster uses Lenovo ThinkSystem systems equipped with NVIDIA HGX B200 GPUs, NVIDIA Quantum-2 QM9700 InfiniBand for GPU traffic, NVIDIA Spectrum SN5600 switches for storage networking and SN2201 switches for management traffic. Corvex says the design allowed it to place high-density Blackwell infrastructure into the existing facility without a conventional facility-wide liquid-cooling conversion. Lenovo, in a case study of the deployment, contrasts the approximately two-week commissioning period with what it describes as typical data center upgrade timelines of seven to 12 months or more. That has significance beyond a single cluster. Power availability and suitable data center capacity increasingly constrain GPU deployment. If the approach proves repeatable, liquid-to-air cooling could allow some existing air-cooled facilities with sufficient power and other supporting infrastructure to accommodate higher-density AI systems without first undergoing a full central liquid-cooling conversion. For

The North American data center industry built at record scale during the first half of 2026. It still wasn’t enough to loosen the market. Primary-market supply increased 33.7% year over year to a record 10,903 MW, according to CBRE’s newly released North America Data Center Trends H1 2026. Yet vacancy moved in the opposite direction, falling from 1.6% a year earlier to another record low of 1.4%. Net absorption reached 1,456.2 MW, up 11.7%, as hyperscale cloud and AI infrastructure operators continued competing for increasingly scarce blocks of contiguous power and capacity. Construction climbed 24.8% to a record 7,481.1 MW, surpassing the previous peak of 6,350.1 MW set in the second half of 2024. Perhaps the most telling number in the report is 80.4%. That is the share of primary-market capacity under construction that has already been preleased, up from 74.3% a year ago. CBRE estimates that less than 1,500 MW of all capacity currently under construction remains available—roughly six months of demand at the current absorption rate. The resulting picture is less one of a construction shortage than a race between infrastructure delivery and an AI demand curve that keeps absorbing capacity before it reaches the market. And increasingly, CBRE argues, securing the megawatts is only part of that race. Power, Permitting and Local Approval Converge Power availability and infrastructure delivery timelines remain the primary determinants of where data centers can be built. But CBRE’s H1 report places another constraint alongside them: community acceptance. “Local opposition has also become a serious obstacle,” the report states, with community resistance, zoning disputes and entitlement delays increasingly capable of stopping projects even after developers identify viable power and fiber. CBRE goes further in its outlook, describing community engagement as a development constraint now “on par with power procurement.” In practical site-selection terms,