In a recent LinkedIn post, Jean Ng 🟢 highlights the escalating importance of computing power, framing it not merely as a technological component but as a fundamental driver of national progress and competitive advantage. The post, which references data from the Global Computing Consortium (GCC) and Harvard, argues that neglecting the strategic allocation of computing resources is a critical misstep for nations and businesses alike.
Computing Power: The New National Imperative
Jean Ng 🟢 asserts that computing power has transcended its traditional role, becoming the primary engine for civilisational advancement. The scale of investment underscores this shift, with major tech firms reportedly dedicating substantial sums to AI infrastructure. According to the post, this is not just an IT budget concern but a matter of national power.
“Countries treating this as an IT budget decision are losing before they realise the game has started.”
This perspective challenges conventional thinking, suggesting that organizations and governments viewing computing power as a mere operational expense risk falling behind. As Jean Ng 🟢 points out, the rapid annual growth in AI computing scale, projected to increase a thousandfold by 2030, necessitates a strategic, top-down approach.
The Jevons Paradox and Universal Dependence on AI
The exponential growth in AI computing capability is linked to the Jevons Paradox, a phenomenon where increased efficiency and reduced costs lead to a surge in overall consumption. Jean Ng 🟢 explains this trend is pushing industries towards a state of ‘universal dependence’ on AI, moving beyond selective applications.
“We’re shifting from ‘selective AI application’ to ‘universal dependence.’ Industries won’t just use AI—they’ll be unable to function without it.”
This profound shift implies that AI will become as essential as traditional operating systems, but with a critical difference. Jean Ng 🟢 elaborates on the evolving nature of AI systems:
From Deterministic Engines to Uncertainty Handlers
Jean Ng 🟢 distinguishes between traditional operating systems, which are deterministic, and the new paradigm required for AI. The latter must function as ‘uncertainty engines’ capable of handling natural language, multimodal interactions, and complex human intent.
“AI requires something different: an uncertainty engine that handles natural language, multimodal interaction, and human intent.”
In this evolving ecosystem, the post highlights a fundamental change in how value is structured and delivered. Jean Ng 🟢 argues that ‘Agents have replaced Apps as the primary unit of value,’ capable of independent planning and converting intentions into actions, marking a move from managing hardware to mediating intelligent tasks.
The Frontier of Embodied Intelligence and Commercial Value
Looking ahead, Jean Ng 🟢 identifies the next frontier as ’embodied intelligence’—AI with a physical presence. This is enabled by breakthroughs in ‘World Models’ that master ‘spatiotemporal consistency,’ allowing AI to understand and simulate physical environments more accurately than ever before.
However, Jean Ng 🟢 also addresses the current challenges enterprises face in translating technical AI advancements into commercial success. The post emphasizes that early metrics focused on token consumption and user scale are becoming obsolete. The true measure of success, according to Jean Ng 🟢, will be the achievement of a ‘commercial closed-loop’ where AI delivers tangible ROI that significantly outweighs computing costs.
Ultimately, Jean Ng 🟢 concludes that the future belongs to organizations that recognize computing power as the bedrock of competitive advantage, rather than merely an infrastructure upgrade. The critical question posed is how strategic budgets are being allocated to this foundational element.
📝 About This Content
This article is based on insights shared by Jean Ng 🟢 on LinkedIn.
📅 Originally posted on March 9, 2026 | View original post on LinkedIn →