Nvidia has become the world’s first $5 trillion company, a milestone driven by its strategic position in the burgeoning Artificial Intelligence (AI) landscape. The company serves as the de facto arms dealer for AI infrastructure, powering every data center and model that drives this transformative industry. This article analyzes whether Nvidia can sustain this growth trajectory or if it marks the precipice of an impending bubble burst. 2024 saw Nvidia’s AI ambitions solidify with increased public-private partnerships, fueled by unprecedented capital flows into energy and data centers. This consolidation has positioned Nvidia as the frontrunner in this new era of AI. But, will this growth continue or meet its end? 0.1% GDP growth, according to Harvard economist Jason Furman, would result from cutting AI investments during the first half of 2025. Meanwhile, corporate AI spending shot up to $252.3 billion in 2024, an eightfold increase from 2022. Gartner predicts a staggering $1.5 trillion in global AI spending in 2025. Despite its impressive rise, concerns linger regarding the sustainability of Nvidia’s valuation and potential overinvestment. OpenAI’s data center investments, totaling billions of dollars, are raising alarm bells about self-reinforcing loop within the industry. Wall Street analysts compare this to the dot-com bubble in the late 1990s. Microsoft co-founder Bill Gates acknowledges that some AI-related ventures may not yield substantial returns, highlighting a crucial distinction between hype and actual innovation. However, Nvidia CEO Jensen Huang expressed optimism about a half trillion dollar worth of AI GPU sales in the coming years. This ambitious vision highlights Nvidia’s commitment to addressing the growing demand for computational power. As Amazon continues its cost-cutting initiatives, fueled by layoffs and automation in key areas like retail and cloud computing, it further underscores the impact of AI on efficiency, profitability, and infrastructure limitations. In short, Nvidia’s success hinges on overcoming physical energy grid constraints and securing access to critical AI chip supplies.