2024-11-13-亿欧智库-2024中国大模型发展要素洞察报告_语料_算力_电力研究_30页_12mb

报告摘要

2024 AI Industry Development Report

AI Development Driving Factors and Production Constraints
The AI industry growth is driven by advancements in technology and increased demand for data and computational power. However, challenges include high costs for training, limited data availability, and growing energy consumption.
Computational Power (Hardware) Analysis
GPUs remain dominant in AI computing, with companies like NVIDIA (e.g., H100) leading the market. Emerging chips like ASICs andChiplet technology aim to improve efficiency. In 2028, AI-specific chips could reduce costs by 40-50%.
Data Requirements and Shortages
AI models require massive datasets, with AIGC (AI-Generated Content) consuming significant data resources. Over 20% of global data traffic is attributed to AI, but data acquisition faces ethical and privacy issues, leading to shortages in certain domains.
Energy Consumption
AI training, especially large language models (e.g., GPT series), consumes massive energy. In 2023, AI-related energy use was 14.05 EFLOPS, with projections indicating 2.3x growth by 2026. SMES (Superconducting Magnetic Energy Storage) and other technologies may offset environmental impacts.
Market and Future Outlook
The global AI market reached $40.9 billion in 2024, with CAGR of 38% through 2026. Key drivers include government policies, rising R&D spending, and increasing enterprise adoption.