Intelligent chatbots powered by large language models(LLMs)have recently been sweeping the world,with potential for a wide variety of industrial applications.Global frontier technology companies are feverishly partici...Intelligent chatbots powered by large language models(LLMs)have recently been sweeping the world,with potential for a wide variety of industrial applications.Global frontier technology companies are feverishly participating in LLM-powered chatbot design and development,providing several alternatives beyond the famous ChatGPT.However,training,fine-tuning,and updating such intelligent chatbots consume substantial amounts of electricity,resulting in significant carbon emissions.The research and development of all intelligent LLMs and software,hardware manufacturing(e.g.,graphics processing units and supercomputers),related data/operations management,and material recycling supporting chatbot services are associated with carbon emissions to varying extents.Attention should therefore be paid to the entire life-cycle energy and carbon footprints of LLM-powered intelligent chatbots in both the present and future in order to mitigate their climate change impact.In this work,we clarify and highlight the energy consumption and carbon emission implications of eight main phases throughout the life cycle of the development of such intelligent chatbots.Based on a life-cycle and interaction analysis of these phases,we propose a system-level solution with three strategic pathways to optimize the management of this industry and mitigate the related footprints.While anticipating the enormous potential of this advanced technology and its products,we make an appeal for a rethinking of the mitigation pathways and strategies of the life-cycle energy usage and carbon emissions of the LLM-powered intelligent chatbot industry and a reshaping of their energy and environmental implications at this early stage of development.展开更多
Whereas current building related life cycle energy and carbon assessment in China has typically focused on either the national building stock or the single building level,this paper attempts to evaluate life cycle ene...Whereas current building related life cycle energy and carbon assessment in China has typically focused on either the national building stock or the single building level,this paper attempts to evaluate life cycle energy consumption and carbon emissions at the level of Chinese residential small district(RSD).This paper discusses a case study of RSD in order to illustrate the way of measuring material,energy and water flows at this spatial level with transparent assessment boundary.Results indicate that evaluating the RSD as a whole,rather than building by building,can provide extra decision-making information for various stakeholders such as housing buyers and RSD designers.展开更多
基金supported by the National Natural Science Foundation of China(72061127004 and 72104164)the System Science and Enterprise Development Research Center(Xq22B04)+1 种基金financial support from the Engineering and Physical Sciences Research Council(EPSRC)Programme(EP/V030515/1)financial support from the Science and Technology Support Project of Guizhou Province([2019]2839).
文摘Intelligent chatbots powered by large language models(LLMs)have recently been sweeping the world,with potential for a wide variety of industrial applications.Global frontier technology companies are feverishly participating in LLM-powered chatbot design and development,providing several alternatives beyond the famous ChatGPT.However,training,fine-tuning,and updating such intelligent chatbots consume substantial amounts of electricity,resulting in significant carbon emissions.The research and development of all intelligent LLMs and software,hardware manufacturing(e.g.,graphics processing units and supercomputers),related data/operations management,and material recycling supporting chatbot services are associated with carbon emissions to varying extents.Attention should therefore be paid to the entire life-cycle energy and carbon footprints of LLM-powered intelligent chatbots in both the present and future in order to mitigate their climate change impact.In this work,we clarify and highlight the energy consumption and carbon emission implications of eight main phases throughout the life cycle of the development of such intelligent chatbots.Based on a life-cycle and interaction analysis of these phases,we propose a system-level solution with three strategic pathways to optimize the management of this industry and mitigate the related footprints.While anticipating the enormous potential of this advanced technology and its products,we make an appeal for a rethinking of the mitigation pathways and strategies of the life-cycle energy usage and carbon emissions of the LLM-powered intelligent chatbot industry and a reshaping of their energy and environmental implications at this early stage of development.
文摘Whereas current building related life cycle energy and carbon assessment in China has typically focused on either the national building stock or the single building level,this paper attempts to evaluate life cycle energy consumption and carbon emissions at the level of Chinese residential small district(RSD).This paper discusses a case study of RSD in order to illustrate the way of measuring material,energy and water flows at this spatial level with transparent assessment boundary.Results indicate that evaluating the RSD as a whole,rather than building by building,can provide extra decision-making information for various stakeholders such as housing buyers and RSD designers.
