1.4 Why Should We
Prioritize UCTR Over AI?

Footnote

Jensen Huang, NVIDIA’s CEO, often explains AI as a layered system, like a cake. At the very bottom is energy—the raw electricity that powers everything. Without abundant, affordable energy, none of the higher layers can exist.

On top of that sits chips and hardware. These are the GPUs, networking systems, and memory technologies that transform energy into computation. They’re the engines that make AI possible.

The third layer is infrastructure. Think of vast data centers—what Huang calls “AI factories.” They orchestrate thousands of processors, cooling systems, and networking pipelines into a single industrial‑scale intelligence machine.

Above infrastructure comes AI models. These are the brains: large language models, protein‑folding models, robotics simulations. Huang emphasizes the shift from generative AI (which creates text or images) to agentic AI (which reasons, plans, and acts).

Finally, at the top is applications. This is where AI touches everyday life—healthcare diagnostics, retail search, voice assistants, financial services. It’s the layer where economic value and social impact are realized.

So the picture is: energy → chips → infrastructure → models → applications. Each layer depends on the one below it, and together they form the complete AI ecosystem. Huang’s point is that to lead in AI, nations and companies must master all five layers, not just one.

Author's Reflection

UCTR can help to meet all the requirement as outlined y Jensen Huang.