A positive perspective: War is indirectly accelerating Pi’s DePIN AI

While the world is concerned about geopolitical instability, there is a lesser-noticed angle: these disruptions are actually creating a competitive advantage for the decentralized AI infrastructure model (DePIN) that Pi Network is building.

1. Helium shortage → Rising AI chip production costs
Helium is essential in many stages of chip manufacturing: wafer cooling, creating inert environments for plasma etching, and vacuum leak testing. When geopolitical conflicts disrupt industrial gas supply chains, especially from major extraction regions, helium becomes scarcer. No gas can fully replace it in fabs. The direct result: AI chip production costs rise significantly, impacting the entire centralized AI hardware supply chain.

2. Memory chip shortage — The centralized AI race becomes increasingly expensive
Conventional DRAM prices have surged by 90–95%, while HBM (high-bandwidth memory used for AI GPUs) is even scarcer as Samsung, SK Hynix, and Micron allocate most production capacity to large data centers. Paradoxically, the faster the AI race accelerates, the more exponentially the cost of centralized AI hardware increases.

3. Attacks on Amazon’s AI cloud → Trust in centralized AI weakens
When cyber and even physical attacks target AI cloud infrastructure of major players like Amazon, concerns about security and resilience grow. A single point of failure—one data center going down—can paralyze the entire dependent ecosystem. Trust in centralized AI is gradually eroding.

4. Global energy crisis → A critical weakness of centralized AI
The energy crisis is squeezing centralized AI infrastructure from multiple angles. Gas prices are high and supply is disrupted. Renewable energy is not stable enough for 24/7 data centers. Many countries are returning to nuclear energy, which is costly and slow to deploy. AI data centers consume enormous electricity—an H100 GPU cluster can use as much power as a residential area.
Meanwhile, Pi’s DePIN AI distributes computation across millions of small devices, each consuming minimal energy, resulting in significantly better overall energy efficiency.

When energy constraints tighten, chips become more expensive, cloud infrastructure becomes more vulnerable, and hardware supply chains grow fragile, Pi’s DePIN AI becomes increasingly attractive. Millions of distributed devices, no central point of attack, no dependence on a single hardware provider, and no need for expensive cloud services.

This may explain why PCT spoke at Consensus 2026—it is no coincidence. As global conditions drive up the cost and reduce the reliability of centralized AI, this is a golden moment for the market to seriously reconsider decentralized models.

“Success or failure depends on who can deliver AI infrastructure that is cheaper, more stable, and more sustainable in the long term.”
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