Title: The AI ​​Era, Computational Efficiency Determines Earth's Temperature:

The 75% Solution Presented by 'Sky Butterfly'

With the advent of the Artificial Intelligence (AI) era, we are living in a period of computational expansion unprecedented in history.

While massive data centers for AI learning have become the brain of modern civilization, behind this lies a 'thermodynamic limit' that we must inevitably face.

1. Computational Density and the Thermodynamic Dilemma

Modern computer architectures have increased transistor density and clock speeds to enhance computational power. However, according to the laws of physics, 'Joule heat' inevitably occurs during the movement of data and computation.

 

2. Algorithms: A Fundamental Solution Beyond Hardware

Until now, we have relied solely on larger GPUs and more memory to increase hardware performance. However, inefficient algorithms cause even the most powerful hardware to unnecessarily occupy CPU and memory resources.

The 'Sieve of Eratosthenes,' which we have used for over 2,000 years, reveals its limitations in the face of modern, massive data scales. In billion-scale calculations, the new 'Sky Butterfly' algorithm demonstrated a 75% reduction in computation time compared to the existing method. Furthermore, we secured data where computation time continues to decrease as the numbers grow larger. It is also a fact that at certain points, it surpasses even supercomputers, and at extreme numbers, it exceeds quantum computers. This is because, while the 'Sieve of Eratosthenes' expands, the Sky Butterfly computation converges to a single point, resembling a triangle. Please refer to the figure.

Prime numbers are not just simple numbers. They are atoms that make up the universe.

3. Why does '4x speed' reduce the carbon footprint?

Reducing computation time by a quarter means more than simply finishing tasks faster; it means reducing the 'time occupancy' during which the system consumes energy by 75%.

Direct reduction in energy consumption: Leads to an immediate reduction in power consumption by cutting computation and memory access cycles, which account for the largest share of power consumption in data centers, by 75%.

• Physical mitigation of cooling load: The energy used for cooling accounts for a massive portion of a data center's total power. If the heat sources within servers are reduced due to algorithmic efficiency, the additional energy consumed to cool them and carbon emissions also decrease in a chain reaction.

4. Conclusion: Beyond Digital Transformation (DX) to 'Digital Ecosystem Transformation'

Building a sustainable AI center is not enough with just the introduction of high-efficiency GPUs. 'Sky Butterfly' aims to eliminate computing inefficiencies at the software level.

• Law of Conservation of Energy: "Data is not created but moves, and that movement inevitably generates heat."