Core Viewpoint - Google recently released a research report on the energy consumption of its AI model, Gemini, highlighting its environmental impact and efficiency improvements in resource usage [1][4]. Summary by Sections Energy Consumption and Emissions - Processing a median Gemini text prompt consumes approximately 0.26 mL of water, 0.24 Wh of electricity, and produces 0.03 grams of CO2 emissions [4]. - Google claims to have reduced energy consumption per text prompt by 33 times and carbon footprint by 44 times from May 2024 to May 2025 [5]. Measurement Methodology - Google emphasizes that its measurement approach is more comprehensive than traditional methods, accounting for energy consumption during active states, standby, auxiliary hardware, and data center cooling and power distribution [6]. Efficiency Optimization - The lower resource consumption figures are attributed to Google's "full-stack" efficiency optimization, which includes improvements in model architecture, algorithms, and hardware [7]. - Gemini is based on the Transformer architecture, achieving efficiency improvements of 10 to 100 times compared to previous models [7]. - Google employs techniques like Accurate Quantized Training (AQT) to maximize efficiency without compromising response quality [9]. Hardware and Software Innovations - Google has designed its TPU from scratch over the past decade to maximize performance per watt, with the latest TPU generation, Ironwood, achieving a 30-fold increase in efficiency compared to the earliest TPUs [9]. - The XLA machine learning compiler and other systems ensure efficient execution of models on TPU inference hardware [9]. Data Center Efficiency - Google's data centers are among the most efficient in the industry, with an average Power Usage Effectiveness (PUE) of 1.09 [10]. Expert Criticism - Experts have raised concerns about the methodology and completeness of Google's study, particularly regarding the omission of indirect water consumption and the carbon emissions accounting method [12][13]. - Critics argue that the reported water consumption only includes direct usage, neglecting the significant water used in power generation for data centers [13]. - The carbon emissions measurement is based on market-based methods, which may not accurately reflect the actual impact on local grids [15]. Overall Resource Consumption Concerns - Despite improvements in efficiency for individual AI prompts, experts warn of the "Jevons Paradox," where increased efficiency may lead to higher overall resource consumption and pollution [17]. - Google's own sustainability report indicates a 51% increase in carbon emissions since 2019, raising concerns about the broader implications of AI development [17].
谷歌Gemini一次提示能耗≈看9秒电视,专家:别太信,有误导性