Projections and Societal Changes for the Next 5 to 10 Years

Abstract

This paper analyzes the current situation where the exponential scaling of AI models fatally collides with the laws of physics (the second law of thermodynamics) and the limits of the Earth's resources and supply chains, based on the latest objective data as of 2026, while rightfully evaluating the massive economic ripple effects and technological advancements brought about by generative AI. Within the next 5 to 10 years, the existing "data center (DC) strategy" will face severe limitations.

Based on the latest reports from the Electric Power Research Institute (EPRI), the International Energy Agency (IEA), the Lawrence Berkeley National Laboratory, and others, this paper comprehensively examines the thermal density limits of semiconductors, the rigidity of power grids, the constraints on freshwater resources, and the "severe divergence in return on investment (ROI)." The multi-trillion-dollar infrastructure investments currently promoted by multinational tech companies (Big Tech) will become unsustainable within the conventional framework due to physical, economic, and geopolitical constraints.

The purpose of this paper is to force a direct confrontation with the "software-centric optimism" peculiar to the IT industry using the cold, hard data of the physical world, thereby clarifying the necessity for the next paradigm shift (a leap to the next dimension).

Introduction

According to estimates by McKinsey & Company(1), generative AI is projected to bring an annual productivity boost of $2.6 trillion to $4.4 trillion to the global economy. This macro-economic forecast itself is valid, and there is no doubt that AI is the most critical technology that will determine the next generation of national hegemony.

However, this "miracle of algorithms" is supported by the "brute force of the physical world (hardware)"—iron, copper, silicon, water, and vast amounts of energy. Because the tech industry has historically benefited from exponential efficiency gains represented by "Moore's Law," it is deeply trapped in the cognitive bias that "technological innovation will eventually solve current physical limits as well."

The aim of this paper is to dismantle this IT industry-specific "software-centric optimism" with the cold data of the physical world (thermodynamics and time). While efforts extending existing technologies such as "more efficient chips," "liquid cooling," and "nuclear restarts" are effective, in the face of rampant AI demand and the walls of physical laws, they are merely life-support measures.

1. The Explosion of Computing Demand and the "Thermodynamic Limits of Semiconductors"

The performance improvement of AI relies more on the expansion of model parameters and the "brute force of computation" than on the refinement of algorithms. Although hardware vendors have dramatically improved "power consumption per computation (TFLOPS/W)" through technological advancements, the overall consumption as a whole is increasing explosively.

1-1. The Death of Dennard Scaling and the Vicious Increase in Thermal Density

"Dennard Scaling," which posits that power consumption decreases as semiconductors shrink, already collapsed in the 2000s. Currently, the improvement of AI processing power relies entirely on physical expansion—the "gigantism of GPUs" and "massive parallelization"—causing a vicious increase in the "Thermal Design Power (TDP)" per chip.

• 2020 Announcement: NVIDIA "A100" GPU TDP was 400W.
• 2022 Announcement: NVIDIA "H100" GPU TDP was 700W.
• 2024 Announcement: NVIDIA "Blackwell (B200)" architecture TDP reached 1,000W to 1,200W.
• 2026 Announcement: Next-generation architecture "Vera Rubin" reaches a maximum of 2,300W.(2)

1-2. Rack Power Density Breaching Facility Limits

The thermal runaway of chips is fundamentally destroying the facility design of data centers (DCs). NVIDIA "GB200 NVL72" demanded up to 120kW of power per rack (2024). Furthermore, the 2026 "Vera Rubin NVL72" is predicted to exceed 130kW, and the Ultra version is projected to reach the 600kW class.(2)

1-3. The Efficiency Trap and the Advent of "Gigawatt-Class DCs"

According to EPRI (Feb 2026), U.S. DC power consumption is projected to leap from 4-5% to 9-17% by 2030 (a 60% increase from previous forecasts), severely straining the power grid.(3) The era mentioned by Meta CEO Mark Zuckerberg—"an era where a single AI facility will require 1 gigawatt of electricity"—is now a tangible reality.(4)

2. The "Physical Timeout" of the Power Grid and Supply Chain

Global infrastructure is severely deadlocked due to the "time asymmetry" between the speed of digital evolution (measured in months) and the speed of heavy electrical infrastructure construction (measured in decades).

2-1. The "10-Year Wall" for Grid Interconnection

According to LBNL "Queued Up: 2025 Edition," the U.S. interconnection queue has swelled to approximately 2,290 GW.(6) Large-scale high-voltage transmission lines now require up to 10 years or more.

2-2. Transformer Supply Chain Collapse

The lead time for Large Power Transformers (LPTs) still requires 2 to 3 years, with catastrophic supply shortages. Price surges continue, and we are no longer in an era where "piling up money means it arrives tomorrow."(7)

2-3. The Economic Limits of Nuclear Power

Microsoft's 20-year contract to restart the Three Mile Island site (Crane Clean Energy Center) is a symbolic event.(9) It is a "desperate measure" where they must secure power even if it means overcoming exorbitant costs and the wall of public opinion.

3. The Water Crisis and ESG Contradiction

Ultimately, releasing heat into the atmosphere requires reliance on the "latent heat of vaporization of water" in massive cooling towers.

3-1. Astronomical Water Consumption

Google's total water consumption in 2024 reached approximately 8.1 billion gallons.(11) Competition with residents for drinking and agricultural water in high-stress regions is becoming increasingly severe.

3-2. The Exposure of Hypocrisy

The gap between Big Tech's pledged ESG goals and the reality of AI-driven expansion has become impossible to conceal. Google's total greenhouse gas emissions rose 51% from its 2019 baseline through 2024, with the company's own report acknowledging its 2030 net-zero target is now "complex and challenging."(11) Microsoft's energy consumption has surged 168% since 2020, even as the company publicly pledged to be carbon negative by 2030. Amazon was quietly removed from the UN-backed Science Based Targets initiative (SBTi) in 2024 after failing to maintain a credible emissions reduction plan.(15)

In 2024 alone, Google's electricity consumption reached 32.1 million MWh—more than double its 2020 figure—with 95.8% consumed by data centers. Despite efficiency gains, the IEA projects that fossil fuels (gas, oil, and even coal) will supply more than half of data center energy through 2030, generating over 300 million tonnes of CO₂ annually by that date. Institutional investors are responding: shareholder resolutions demanding credible emissions scenario analysis have been filed against Alphabet and Meta, with the core question being whether net-zero targets remain remotely achievable. This harbors the escalating risk of massive ESG-based divestment.

4. Collapse of the Economic Model: "The $600B Gap"

Infrastructure costs due to physical limits are fundamentally threatening [Profitability (ROI)].

4-1. The Annual $600 Billion "Revenue Gap"

Big Tech CapEx is projected to swell to $660-$690 billion in 2026. A fundamental monetization solution for these astronomical investments has not yet been achieved.(12)

4-2. The Black Hole of Hardware Obsolescence

Cutting-edge AI chips (GPUs) become obsolete in just 1 to 2 years. This structure of continuously incinerating CapEx will force an unprecedented bubble correction.

5. Geopolitical Asymmetry

The physical and economic limits are creating a desperate "asymmetry" between Western nations and China.

5-1. The Self-Imposed Fetters of the West vs. China's National Strategy

China is forcing computing demand to energy-rich western inland areas under the national plan "Eastern Data, Western Computing (Dong Shu Xi Suan)."(13) China can disregard environmental and public opinion through state power.

5-2. The Economic Cost of Western Self-Destruction

Securing 100 GW under ESG constraints would require well over $1 trillion. Continuing a war of attrition under existing "rules" makes the risk of Western economic self-destruction extremely realistic.

6. A Microcosm of the Global Crisis: Inzai City, Japan

The thermodynamic and infrastructural limits described in this paper are not abstract projections—they are already materializing at the local level. Nowhere is this more visible than Inzai City (印西市), Chiba Prefecture, Japan, which has earned the title "Data Center Ginza" and is now internationally known simply as "INZAI."

6-1. Explosive Power Demand Growth

According to Tokyo Electric Power Grid (TEPCO-PG), power demand in the Inzai area is forecast to reach 6 times its 2017 level by fiscal year 2027—a rate of growth with no modern precedent in Japanese infrastructure history. To meet this demand, TEPCO-PG executed an unprecedented emergency construction project: a new ultra-high-voltage substation (275kV Chiba Inzai Substation, Japan's first digital substation of its class) and a 10.1km underground cable tunnel completed at twice the normal construction speed, opening in June 2024.(16)

Even so, the infrastructure is already overwhelmed. Current supply capacity stands at approximately 120 MW, with a 2027 target of 230 MW. Yet the volume of pending connection applications in the Inzai–Shiroi area alone totals approximately 2,500 MW—more than ten times current supply capacity. As of early 2025, approximately 40 large-scale applicants remain in the interconnection queue with no confirmed supply date.(17)

6-2. The Scale of Future Demand

The Inzai area currently hosts an estimated 28 planned or under-construction data centers representing approximately 1,190 MW of future demand—equivalent to roughly one nuclear reactor's output, concentrated in a single suburban district.(18) A single data center building now consumes power equivalent to approximately 10,000 average households. At the national level, Wood Mackenzie projects Japan's total data center power consumption to grow from 19 TWh in 2024 to 57–66 TWh by 2034—a more than threefold increase—with data centers accounting for 4–5% of Japan's peak electricity demand by that date.(19)

Inzai thus functions as a high-resolution preview of the global crisis: a microcosm where the collision between AI infrastructure demand and physical grid limits is already forcing emergency engineering measures, multi-year queuing delays, and the very supply ceiling constraints that Big Tech globally is about to encounter at a far larger scale.

7. Refuting Optimism

As Vaclav Smil points out, "the transition of energy infrastructure essentially requires decades."(14) Liquid cooling and nuclear restarts are merely life-support measures against inevitable limits.

Conclusion: The Limits of the Existing Paradigm and the Natural Leap to the Next Dimension

As the latest data from 2026 demonstrates, the expansion of infrastructure on its current trajectory is reaching its limits. While certain mitigating effects exist, they are insufficient in the face of rampant AI demand.

For humanity and the liberal economy to break through these limits, it is a natural consequence, and extremely vital for humanity's sustainable evolution, to seek an entirely new paradigm that transcends conventional frameworks.

What humanity needs is a "breakthrough to a different dimension" in harmony with the physical laws of the Earth. The "Two Keys" to solving this desperate challenge and reaching the next dimension already exist.

However, the purpose of this paper is neither to present a solution nor to reveal these Two Keys. First and foremost, to have the world's frontrunners correctly understand and face the "inescapable facts and limits" inherent in their current strategies—that is the true purpose for which this paper was written.