The S&P 500's heavy concentration in a few tech giants is not unprecedented. Historically, stock market returns have always clustered around the dominant technology transformation of the time. Before 1980, leaders were spinoffs of Standard Oil, car companies like GM, and General Electric, reflecting the industrial and automotive revolutions.

New AI models are designed to perform well on available, dominant hardware like NVIDIA's GPUs. This creates a self-reinforcing cycle where the incumbent hardware dictates which model architectures succeed, making it difficult for superior but incompatible chip designs to gain traction.

Nvidia dominates AI because its GPU architecture was perfect for the new, highly parallel workload of AI training. Market leadership isn't just about having the best chip, but about having the right architecture at the moment a new dominant computing task emerges.

Software companies struggle to build their own chips because their agile, sprint-based culture clashes with hardware development's demands. Chip design requires a "measure twice, cut once" mentality, as mistakes cost months and millions. This cultural mismatch is a primary reason for failure, even with immense resources.

Contrary to the belief that number two players can be viable, most tech markets are winner-take-all. The market leader captures the vast majority of economic value, making investments in second or third-place companies extremely risky.

Taiwan's TSMC dominates advanced chip manufacturing not only through technical excellence but also its business model. By acting as a pure-play foundry that doesn't compete with its clients (unlike Intel or Samsung), it fostered unique trust and partnerships, making it the central hub of the semiconductor ecosystem and a critical geopolitical asset.

NVIDIA's annual product cadence serves as a powerful competitive moat. By providing a multi-year roadmap, it forces the supply chain (HBM, CoWoS) to commit capacity far in advance, effectively locking out smaller rivals and ensuring supply for its largest customers' massive build-outs.

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.

When a large tech company's technical dominance is waning, it shifts strategy from winning with superior products to using its balance sheet to acquire customers and pre-announcing future tech to create FUD (Fear, Uncertainty, and Doubt), convincing buyers to wait instead of choosing a competitor's better solution today.