All Posts

Why this cycle is different, why white-collar work is exposed, and where real opportunity still exists There is a tendency in every major technology shift to assume the noise is exaggerated. People say the headlines are overheated, the fear is temporary, and the market will eventually settle back into something familiar. That is not what this moment feels like. What is happening in AI looks much more like a structural reset—one that is changing how work is performed, how comp

For decades, growth was defined by distribution. Companies manufactured products, sold them externally, reinvested profits, and repeated the cycle. Capital leaked outward at every step—through suppliers, vendors, energy providers, and infrastructure operators. That model is quietly being replaced. Today’s most dominant technology players are building something far more powerful: Closed-loop ecosystems that internally consume the very infrastructure they produce. From Vertical

Innovation in capital markets rarely comes from novelty alone. More often, it comes from reassessment — from asking sharper questions about assets that already exist. Not what was this built to do , but what else can this support ? A recent infrastructure project in Switzerland offers a useful illustration. At a decommissioned satellite teleport in the Alps, massive satellite dishes — once critical to global communications — are being repurposed as solar-tracking energy syste

The idea of data centers in space has officially escaped the realm of speculation. At the World Economic Forum in Davos, global leaders framed orbital computing not as science fiction, but as a structural response to the most pressing constraint facing artificial intelligence today: Earth itself. Power shortages, cooling limits, land scarcity, permitting delays, and carbon pressure are colliding just as AI demand is accelerating beyond anything existing infrastructure was des

At the recent World Economic Forum  in Davos, a reality long understood by infrastructure operators was stated plainly on the global stage. As articulated by Elon Musk , the limiting factor for artificial intelligence is no longer compute availability. It is power. That observation marks an inflection point—not because it is new, but because it has now entered the mainstream narrative. For those building at scale, this constraint has been visible for years. The Shift from Com

Eliakim Capital is proud to be instrumental in the transformation of The Freedom Center , a landmark infrastructure project redefining South Florida’s role in global connectivity, artificial intelligence, and enterprise compute. Located in Sunrise, the Freedom Center occupies a rare position at the intersection of broadcast-grade resilience, hemispheric connectivity, and AI-era compute readiness. Formerly home to HBO Latin America, the facility is now being reimagined as a ne

South Florida’s emergence as a serious data center market is no longer theoretical. It is operational, powered, and ready. The Freedom Center  stands as a clear signal that the region has entered a new phase—one defined by execution rather than ambition, and by infrastructure that meets the real demands of AI-driven workloads. Over the last two days, Rich Washburn , Managing Partner & Chief AI Officer of Eliakim Capital , spent extensive time onsite at the Freedom Center. The

Artificial intelligence is often described as a software revolution, but at scale it becomes an infrastructure problem. Every serious AI system eventually resolves into racks, chips, cooling, steel, and electricity. As AI and high-performance computing infrastructure expands, the industry is discovering a hard truth: intelligence scales physically. Compute is not virtual — it is industrial. From Algorithms to Infrastructure AI / HPC infrastructure has moved beyond experimenta

When markets talk about “$3 trillion flowing into AI,” the assumption is usually software, models, and abstract innovation. In reality, the bulk of the capital is being deployed into physical systems: data centers, high-density compute, networking, cooling, and the power infrastructure required to run them continuously. This is not a digital spending cycle—it is an industrial one. What’s unfolding is closer to the buildout of railroads, telecom, or electrification than a typi

After nearly two decades of relatively flat electricity consumption, the United States is entering a new era of power demand growth. This shift is not being driven by population growth, household consumption, or traditional heavy industry. Instead, it is being propelled by data centers—specifically those supporting cloud computing, artificial intelligence, and high-performance workloads. Federal energy forecasts now show that U.S. electricity usage is set to rise more over th

The reported agreement by SoftBank Group Corp.  to acquire DigitalBridge Group, Inc.  for approximately $4.0 billion is not simply another large-cap infrastructure transaction. It is a strategic signal to global markets that the next phase of artificial intelligence leadership will be determined less by software breakthroughs and more by ownership of the physical systems that make AI possible. The immediate market reaction underscored this reality. Shares of DigitalBridge sur

The AI infrastructure market is entering its most revealing phase. Demand is real, but delivery is being separated from promotion at an accelerating pace. In the last 18 months, “AI data center” has become a label applied to everything from entitled land to partially designed shells—often with bold megawatt claims and thin execution behind them. That’s the backdrop for what Groq CEO Jonathan Ross has called “fake data centers”: projects that look investable in a deck, but c

The global race to build AI infrastructure has triggered what looks, on the surface, like a data-center supercycle. New projects are announced weekly. Capacity targets grow larger by the month. Megawatts are promised freely and confidently. Yet beneath the headlines, a more uncomfortable reality is emerging: many of these facilities are not real data centers at all. As Jonathan Ross, CEO of Groq, who was recently acquired by NVIDA for $20BIL, bluntly put it in a recent inter

Executive Summary 2025 marked a historic acceleration  in AI-driven data center investment, with hyperscalers committing unprecedented capital to compute, land, and power. AI compute demand reshaped capital markets , supply chains, and semiconductor economics, concentrating value in GPUs, advanced nodes, and energy infrastructure. Power availability—not chips—emerged as the primary constraint , redefining site selection and project timelines. 2026 will remain a growth year ,

Every major technology cycle has a moment where value migrates silently—long before it becomes consensus. In AI, that moment is now. NVIDIA’s reported ~$20B strategic integration with Groq is not a conventional acquisition. It is a structural repositioning around what has quietly become the most constrained variable in AI economics: inference latency. This move does not signal a retreat from training dominance. It signals recognition that the next phase of AI value creation w

Eliakim Capital is pleased to announce that Rich Washburn  has joined the firm as Managing Partner and Chief AI Officer . Rich’s addition marks an important step forward for Eliakim Capital as the firm continues to scale its work at the intersection of artificial intelligence, high-performance computing, power infrastructure, and capital formation. His role reflects the firm’s conviction that AI and systems architecture must be represented at the highest level of leadership.

Why Microreactors Are Back — and Why NANO Nuclear Is First in Focus Artificial intelligence is no longer constrained by algorithms or silicon alone. It is increasingly constrained by power—and more specifically, by the kind of power that can operate continuously, predictably, and at scale. As AI systems grow in complexity and ambition, they are placing unprecedented demands on physical infrastructure. Training and operating frontier models requires electricity that behaves le

Executive Summary POWER’s inaugural Data Center POWER eXchange (DPX)  Summit convened utilities, hyperscalers, regulators, financiers, and developers to address the accelerating collision between data center demand growth and grid capacity. AI-driven load expansion is materially outpacing grid planning, permitting, and build-out timelines—raising reliability, cost, and political risks. Former federal energy regulators and utility CEOs highlighted a dual challenge: maintaining

When a power system fails during a natural disaster, there is no luxury of long planning cycles, regulatory indecision, or theoretical optimization. Hospitals need electricity. Communications must come back online. Water systems, logistics hubs, and emergency command centers cannot wait for utility upgrades or multiyear grid studies. In those moments, power is deployed the only way that matters: fast, reliable, and sufficient to meet real demand. What is becoming increasingly

For the better part of the last decade, the story of artificial intelligence infrastructure has been a story about silicon. Who could secure the most advanced GPUs. Who had priority access to next-generation accelerators. Who could outspend competitors on hardware, packaging, and interconnects. That narrative is no longer sufficient. Today, the defining constraint on AI scale is not compute—it is power. Reliable, dispatchable, near-term power. And increasingly, the market is