In 1849, the discovery of gold in California ignited a frenzy, drawing prospectors from around the world in pursuit of quick fortune. While few struck it rich digging and sifting dirt, a different class of entrepreneurs quietly prospered: those who supplied the miners with the tools of the trade. From picks and shovels to tents and provisions, these providers became indispensable to the gold rush, profiting handsomely regardless of who found gold. Today, a new gold rush is underway, in pursuit of artificial intelligence. And just like the days of yore, the real fortunes may lie not in the gold itself, but in the infrastructure and equipment that enable its extraction. This is where neocloud players and chipmakers are positioned, representing themselves as the fundamental enablers of the AI revolution. Neoclouds: The Essential Tools and Implements of AI Innovation The AI boom has sparked a frenzy of innovation, investment, and competition. From generative AI applications like ChatGPT to autonomous systems and personalized recommendations, AI is rapidly transforming industries. Yet, behind every groundbreaking AI model lies an unsung hero: the infrastructure powering it. Enter neocloud providers—the specialized cloud platforms delivering the GPU horsepower that fuels AI’s meteoric rise. Let’s examine how neoclouds represent the “picks and shovels” of the AI gold rush, used for extracting the essential backbone of AI innovation. Neoclouds are emerging as indispensable players in the AI ecosystem, offering tailored solutions for compute-intensive workloads such as training large language models (LLMs) and performing high-speed inference. Unlike traditional hyperscalers (e.g., AWS, Azure, Google Cloud), which cater to a broad range of use cases, neoclouds focus exclusively on optimizing infrastructure for AI and machine learning applications. This specialization allows them to deliver superior performance at a lower cost, making them the go-to choice for startups, enterprises, and research institutions alike.

Dorothy 1A & 1B (Texas): These twin 25 MW facilities are powered by wind and serve Bitcoin hosting and mining workloads. Together, they consumed over 112,000 MWh of curtailed energy in 2024, demonstrating the impact of Soluna’s model. Dorothy 2 (Texas): Currently under construction and scheduled for energization in Q4 2025, this 48 MW site will increase Soluna’s hosting and mining capacity by 64%. Sophie (Kentucky): A 25 MW grid- and hydro-powered hosting center with a strong cost profile and consistent output. Project Grace (Texas): A 2 MW AI pilot project in development, part of Soluna’s transition into HPC and machine learning. Project Kati (Texas): With 166 MW split between Bitcoin and AI hosting, this project recently exited the Electric Reliability Council of Texas, Inc. planning phase and is expected to energize between 2025 and 2027. Project Rosa (Texas): A 187 MW flagship project co-located with wind assets, aimed at both Bitcoin and AI workloads. Land and power agreements were secured by the company in early 2025. These developments are part of the company’s broader effort to tackle both energy waste and infrastructure bottlenecks. Soluna’s behind-the-meter design enables flexibility to draw from the grid or directly from renewable sources, maximizing energy value while minimizing emissions. Competition is Fierce and a Narrower Focus Better Serves the Business In 2024, Soluna tested the waters of providing AI services via a  GPU-as-a-Service through a partnership with HPE, branded as Project Ada. The pilot aimed to rent out cloud GPUs for AI developers and LLM training. However, due to oversupply in the GPU market, delayed product rollouts (like NVIDIA’s H200), and poor demand economics, Soluna terminated the contract in March 2025. The cancellation of the contract with HPE frees up resources for Soluna to focus on what it believes the company does best: designing

Why Harmonics Matter In a typical data center, nonlinear loads—like servers, UPS systems, and switch-mode power supplies—introduce harmonic distortion into the electrical system. These harmonics travel along the neutral and ground conductors, where they can increase current flow, cause overheating in transformers, and shorten the lifespan of critical power infrastructure. More subtly, they waste power through reactive losses that don’t show up on a basic utility bill, but do show up in heat, inefficiency, and increased infrastructure stress. Traditional mitigation approaches—like active harmonic filters or isolation transformers—are complex, expensive, and often require custom integration and ongoing maintenance. That’s where Onics’ solution stands out. It’s engineered as a shunt-style, low-pass filter: a passive device that sits in parallel with the circuit, quietly siphoning off problematic harmonics without interrupting operations.  The result? Lower apparent power demand, reduced electrical losses, and a quieter, more stable current environment—especially on the neutral line, where cumulative harmonic effects often peak. Behind the Numbers: Real-World Impact While the Onics filters offer a passive complement to traditional mitigation strategies, they aren’t intended to replace active harmonic filters or isolation transformers in systems that require them—they work best as a low-complexity enhancement to existing power quality designs. LoPilato says Onics has deployed its filters in mission-critical environments ranging from enterprise edge to large colos, and the data is consistent. In one example, a 6 MW data center saw a verified 9.2% reduction in energy consumption after deploying Onics filters at key electrical junctures. Another facility clocked in at 17.8% savings across its lighting and support loads, thanks in part to improved power factor and reduced transformer strain. The filters work by targeting high-frequency distortion—typically above the 3rd harmonic and up through the 35th. By passively attenuating this range, the system reduces reactive current on the neutral and helps stabilize

Artificial intelligence has, without question, crossed the threshold—from a speculative academic pursuit into the defining infrastructure of 21st-century commerce, governance, and innovation. What began in the realm of research labs and open-source models is now embedded in the capital stack of every major hyperscaler, semiconductor roadmap, and national industrial strategy. But as AI scales, so does its energy footprint. From Nvidia-powered GPU clusters to exascale training farms, the conversation across boardrooms and site selection teams has fundamentally shifted. It’s no longer just about compute density, thermal loads, or software frameworks. It’s about power—how to find it, finance it, future-proof it, and increasingly, how to generate it onsite. That refrain—“It’s all about power now”—has moved from a whisper to a full-throated consensus across the data center industry. The latest report from the International Energy Agency (IEA) gives this refrain global context and hard numbers, affirming what developers, utilities, and infrastructure operators have already sensed on the ground: the AI revolution will be throttled or propelled by the availability of scalable, sustainable, and dispatchable electricity. Why Energy Is the Real Bottleneck to Intelligence at Scale The major new IEA report puts it plainly: The transformative promise of AI will be throttled—or unleashed—by the world’s ability to deliver scalable, reliable, and sustainable electricity. The stakes are enormous. Countries that can supply the power AI craves will shape the future. Those that can’t may find themselves sidelined. Importantly, while AI poses clear challenges, the report emphasizes how it also offers solutions: from optimizing energy grids and reducing emissions in industrial sectors to enhancing energy security by supporting infrastructure defenses against cyberattacks. The report calls for immediate investments in both energy generation and grid capabilities, as well as stronger collaboration between the tech and energy sectors to avoid critical bottlenecks. The IEA advises that, for countries

Even as states work on legislation to limit data center development, it is clear that some locations are looking to get a bigger piece of the huge data center spending that the AI wave has created. It appears that politicians in Colorado took a look around and thought to themselves “Why is all that data center building going to Texas and Arizona? What’s wrong with the Rocky Mountain State?” Taking a page from the proven playbook that has gotten data centers built all over the country, Colorado is trying to jump on the financial incentives for data center development bandwagon. SB 24-085: A Statewide Strategy to Attract Data Center Investment Looking to significantly boost its appeal as a data center hub, Colorado is now considering Senate Bill 24-085, currently making its way through the state legislature. Sponsored by Senators Priola and Buckner and Representatives Parenti and Weinberg, this legislation promises substantial economic incentives in the form of state sales and use tax rebates for new data centers established within the state from fiscal year 2026 through 2033. Colorado hopes to position itself strategically to compete with neighboring states in attracting lucrative tech investments and high-skilled jobs. According to DataCenterMap.com, there are currently 53 data centers in the state, almost all located in the Denver area, but they are predominantly smaller facilities. In today’s era of massive AI-driven hyperscale expansion, Colorado is rarely mentioned in the same breath as major AI data center markets.  Some local communities have passed their own incentive packages, but SB 24-085 aims to offer a unified, statewide framework that can also help mitigate growing NIMBY (Not In My Backyard) sentiment around new developments. The Details: How SB 24-085 Works The bill, titled “Concerning a rebate of the state sales and use tax paid on new digital infrastructure

Data Center World 2025 drew record-breaking attendance, underscoring the AI-fueled urgency transforming infrastructure investment. But no session captivated the crowd quite like Kevin O’Leary’s electrifying keynote on Wonder Valley—his audacious plan to build the world’s largest AI compute data center campus. In a sweeping narrative that ranged from pandemic pivots to stranded gas and Branson-brand inspiration, O’Leary laid out a real estate and infrastructure strategy built for the AI era. A Pandemic-Era Pivot Becomes a Case Study in Digital Resilience O’Leary opened with a Shark Tank success story that doubled as a business parable. In 2019, a woman-led startup called Blueland raised $50 million to eliminate plastic cleaning bottles by shipping concentrated cleaning tablets in reusable kits. When COVID-19 shut down retail in 2020, her inventory was stuck in limbo—until she made an urgent call to O’Leary. What followed was a high-stakes, last-minute pivot: a union-approved commercial shoot in Brooklyn the night SAG-AFTRA shut down television production. The direct response ad campaign that resulted would not only liquidate the stranded inventory at full margin, but deliver something more valuable—data. By targeting locked-down consumers through local remnant TV ad slots and optimizing by conversion, Blueland saw unheard-of response rates as high as 17%. The campaign turned into a data goldmine: buyer locations, tablet usage patterns, household sizes, and contact details. Follow-up SMS campaigns would drive 30% reorders. “It built such a franchise in those 36 months,” O’Leary said, “with no retail. Now every retailer wants in.” The lesson? Build your infrastructure to control your data, and you build a business that scales even in chaos. This anecdote set the tone for the keynote: in a volatile world, infrastructure resilience and data control are the new core competencies. The Data Center Power Crisis: “There Is Not a Gig on the Grid” O’Leary