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Three Hidden Bottlenecks the AI Buildout Has Already Moved Past GPUs Bloom Energy reported Q1 2026 revenue of $751 million. That number was 130 percent higher than the prior year, 42 percent above consensus, and triggered a full-year guidance raise to $3.6 billion 1. Most of the post-earnings coverage read the print as a fuel cell company finally turning operationally profitable. The print is not a fuel cell story. It is the canonical evidence that the AI infrastructure bottleneck has migrated past compute. For two years the consensus model for AI capex has anchored on GPU shipments. NVIDIA, AMD, the hyperscaler capex disclosures, the analyst models all priced compute as the load-bearing constraint. The reasoning was straightforward: training runs scaled, GPU clusters grew from 5,000 units to 50,000 to 100,000, and the company that supplied the silicon owned the bottleneck. The reasoning was correct in 2023. It became incomplete in 2024. By 2026 it has become a rear-view mirror. The analyst models that price AI on GPU shipments are not wrong about GPUs being important. They are wrong about GPUs being scarce. The supply-side data has been telling a different story for three quarters now, and Bloom Energy’s print is the most recent confirmation. The bottleneck moved. It always does. The binding constraint never disappears. It only migrates to the next layer. The question that matters now is which layer the binding constraint has migrated to. Three layers have evidence pointing at them, none of which are GPUs, and the layers compose into a single observation about where AI capex goes once the compute layer has been solved. The first layer: power, and the 128-week wait Behind every large GPU cluster sits a power-delivery infrastructure that takes longer to build than the cluster itself. Power transformers, the equipment that steps utility-scale voltage down to data-centre-usable voltage, have 80 to 128 week lead times right now 2. Cleveland-Cliffs is the only domestic U

On July 27, 2026, the Caribbean Development Bank announced that it had approved a US$100,000 grant to the CARICOM Private Sector Organization to support the first phase of a study examining the feasibility and possible design of a regional stock exchange for participating states of the CARICOM Single Market and Economy. Together, the Caribbean Development Bank and the Inter-American Development Bank are contributing US$324,700 towards Phase I. [1] The proposed study will examine market demand, legal and regulatory requirements, international exchange models and the needs of public- and private-sector stakeholders. It will also consider how regional capital markets could become more connected, improve liquidity, lower financing costs and expand access to capital for Caribbean businesses. [1] These are important economic goals. However, achieving them would depend heavily on the technology supporting the exchange. More Than a Trading Website When people hear the term “stock exchange”, many may picture a website displaying company names, share prices and complex charts. This mental image is, by no means, incorrect, but it admittable fails to grasp the complex financial infrastructure that must be put in place to support a proper exchange. Behind the website with the complex charts, lies systems which process orders, match buyers to sellers, record and broadcasts trades, protect investor information and maintain an accurate history of every market. The birth of a regional exchange would require a great deal of thought, since it would need to operate across multiple Caribbean jurisdictions. Investors in Guyana, Jamaica, Barbados, Trinidad and Tobago and other participating states should be able to interact with the same market without the barrier of geography. This would require several closely connected systems, including: A high-performance order-matching engine Secure investor and broker portals Real-time market-data services Trade clearing and settlement infrastructu