While high capex is often seen as a negative, for giants like Alphabet and Microsoft, it functions as a powerful moat in the AI race. The sheer scale of spending—tens of billions annually—is something most companies cannot afford, effectively limiting the field of viable competitors.

The strongest evidence that corporate AI spending is generating real ROI is that major tech companies are not just re-ordering NVIDIA's chips, but accelerating those orders quarter over quarter. This sustained, growing demand from repeat customers validates the AI trend as a durable boom.

The current AI spending spree by tech giants is historically reminiscent of the railroad and fiber-optic bubbles. These eras saw massive, redundant capital investment based on technological promise, which ultimately led to a crash when it became clear customers weren't willing to pay for the resulting products.

Tech giants are shifting from asset-light models to massive capital expenditures, resembling utility companies. This is a red flag, as historical data shows that heavy investment in physical assets—unlike intangible assets—tends to predict future stock underperformance.

Eclipse Ventures founder Lior Susan shares a quote from Sam Altman that flips a long-held venture assumption on its head. The massive compute and talent costs for foundational AI models mean that software—specifically AI—has become more capital-intensive than traditional hardware businesses, altering investment theses.

Sam Altman dismisses concerns about OpenAI's massive compute commitments relative to current revenue. He frames it as a deliberate "forward bet" that revenue will continue its steep trajectory, fueled by new AI products. This is a high-risk, high-reward strategy banking on future monetization and market creation.

Major tech companies view the AI race as a life-or-death struggle. This 'existential crisis' mindset explains their willingness to spend astronomical sums on infrastructure, prioritizing survival over short-term profitability. Their spending is a defensive moat-building exercise, not just a rational pursuit of new revenue.

Merco's explosive growth and $10B valuation are less about its standalone business and more a direct proxy for the AI CapEx boom. With massive customer concentration among foundation models, its success is a high-leverage bet that AI giants will continue their massive spending on training for the next 3-5 years.

Massive AI capital expenditures by firms like Google and Meta are driven by a game-theoretic need to not fall behind. While rational for any single company to protect its turf, this dynamic forces all to invest, eroding collective profitability for shareholders across the sector.