Core Insights - The rapid growth of computing power is essential for the digital economy, with Huawei predicting a 100,000-fold increase in total computing power by 2035, enabling real-time high-definition video calls from Earth to Mars [1][4] - The demand for computing power is experiencing non-linear growth, particularly in AI training and inference, with a potential 100-fold increase in computing needs when the token volume processed by AI increases tenfold [3][4] Computing Power Revolution - The exponential evolution of AI models, such as GPT-5 and Claude 3, requires significant computational resources, consuming 25,000 H100 GPUs for three months for a single training session [3] - The future of computing will involve a "computing revolution," driven by advancements in architecture, materials, and engineering processes, including photon computing and quantum bits [9] Connectivity and Data Processing - By 2035, the number of connected devices is expected to rise from 9 billion to 900 billion, necessitating advanced edge computing capabilities to handle massive data streams, such as 1TB of sensor data per second from a single L4 autonomous vehicle [4] - Traditional computing architectures face challenges, such as the "memory wall," where data transfer times consume over 70% of processing time, hindering performance improvements [7] Energy and Efficiency Challenges - Global data centers currently consume 3% of total electricity, with a single AI server's power consumption equivalent to that of 30 household air conditioners, highlighting the need for energy-efficient solutions [8] - The International Energy Agency (IEA) predicts that global data center electricity consumption will reach 945 TWh by 2030, necessitating innovations to reduce carbon intensity by 80% [21] Innovations in Healthcare and Industry - AI is projected to assist in preventing 80% of chronic diseases by 2035 through real-time monitoring and predictive modeling, enabling early warnings for conditions like cancer and diabetes [11] - In industrial manufacturing, predictive maintenance driven by computing power can reduce equipment downtime by 70% and improve product quality significantly [14] National Strategies and Technological Breakthroughs - The "East Data West Computing" initiative aims to deploy 1 million standard racks across eight hubs, optimizing the match between high real-time computing demands in the east and green energy resources in the west [16] - Huawei's Ascend 910B chip, with a computing density of 320 TFLOPS, represents a significant advancement in AI chip technology, doubling performance compared to previous generations [17]