The Algorithm’s Appetite

The pronouncements regarding an impending effervescence – a ‘bubble,’ as they term it – in the realm of artificial intelligence seem, at best, a misdirection. The true expansion isn’t in the intelligence itself, but in the relentless, almost involuntary, accumulation of the means to sustain it. The hyperscalers, these entities dedicated to the processing of the intangible, are not merely spending; they are compelled to spend, as if driven by an internal directive beyond the scope of conventional accounting. The logic, if one can apply such a term, is not of return on investment, but of continued existence. Whether this expenditure will ultimately yield something of demonstrable value is, of course, irrelevant. The process itself is the justification.

One observes, with a certain detached curiosity, that the beneficiaries of this peculiar compulsion are, predictably, those who provide the physical substrate. It is in these purveyors of silicon and electricity that one finds, not necessarily opportunity, but a temporary respite from the unsettling feeling of being utterly superfluous. Three entities, in particular, seem poised to navigate this labyrinthine expansion, though not, one suspects, without incurring their own share of existential dread.

Taiwan Semiconductor

Every path, however circuitous, leads back to Taiwan Semiconductor Manufacturing. The largest foundry, it is the silent architect of nearly every computational device that fuels this artificial awakening. One might imagine a complex network of dependencies, a delicate balance of supply and demand. But the reality is far simpler: they possess the means of production, and the others, despite their pronouncements of innovation, are reliant upon it. Alternatives exist, naturally, but they are pale imitations, insufficient to satisfy the insatiable hunger of the hyperscalers. It is a relationship not of choice, but of necessity, a quiet coercion enforced by the sheer scale of the undertaking.

Management anticipates a demand for these chips that borders on the fantastical, and has committed between $52 and $56 billion to expand production capacity. The CEO, C.C. Wei, admitted to a certain ‘nervousness’ regarding this expenditure – a fleeting moment of human recognition in the face of the overwhelming – but expressed confidence after consultations with clients. One can only assume these consultations involved a tacit understanding of mutual dependency, a shared recognition of the absurdity of the situation. They project a compound annual growth rate of nearly 60% between 2024 and 2029. Such growth is not merely optimistic; it is a preordained consequence of the system itself.

Nvidia

Nvidia, the name has become almost synonymous with the very concept of artificial intelligence. Their graphics processing units, these intricate arrangements of silicon and electricity, fill the data centers, processing the endless stream of data. It is a curious phenomenon, this elevation of a particular technology to the status of a symbol. Perhaps it is simply a convenient way to externalize the anxieties surrounding this new form of intelligence, to attribute agency to a machine rather than confront the implications of its existence.

Analysts anticipate further growth, projecting a 52% revenue increase in fiscal year 2027. They believe that global data center capital expenditures will rise to $3 to $4 trillion annually by 2030 – a figure that, in 2025, was a mere $600 billion. It is a staggering escalation, a relentless march towards an unknown destination. The party, as they say, is just beginning. One wonders, however, who will be left to enjoy it.

Broadcom

Broadcom takes a different approach, a deviation from the broad-purpose architecture of Nvidia. They are partnering directly with the hyperscalers to design application-specific integrated circuits – ASICs. These chips are purpose-built, optimized for specific workloads. The logic is sound, of course: efficiency, reduced cost. But it also introduces a new level of dependence, a tightening of the already intricate web of relationships. If the workload changes, the chip becomes obsolete. It is a precarious balance, a constant negotiation between flexibility and control.

Revenue from AI semiconductors is expected to double in the first quarter. Momentum is building, accelerating. More hyperscalers are beginning to purchase these alternative computing units. Broadcom is poised to take ground from Nvidia, but all three – Taiwan Semiconductor, Nvidia, and Broadcom – represent, at this moment, the most… stable points in a rapidly shifting landscape. One hesitates to call them investments. They are, perhaps, simply the least undesirable options in a system spiraling out of control.

2026-02-02 07:32

Taiwan Semiconductor

Nvidia

Broadcom

Read More