{"title":"鞋盒中的数据中心:IMEC 利用超导体缩小计算机的计划","authors":"Anna Herr;Quentin Herr","doi":"10.1109/MSPEC.2024.10551792","DOIUrl":null,"url":null,"abstract":"What's more, this projection was made before the sudden explosion of generative AI. The amount of computing resources used to train the largest AI models has been doubling roughly every 6 months for more than the past decade. At this rate, by 2030 training a single artificial-intelligence model would take one hundred times as much computing resources as the combined annual resources of the current top 10 super-computers. Simply put, computing will require colossal amounts of power, soon exceeding what our planet can provide.","PeriodicalId":13249,"journal":{"name":"IEEE Spectrum","volume":"61 6","pages":"37-41"},"PeriodicalIF":2.6000,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Data Center in a Shoebox: IMEC's Plan to use Superconductors to Shrink Computers\",\"authors\":\"Anna Herr;Quentin Herr\",\"doi\":\"10.1109/MSPEC.2024.10551792\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"What's more, this projection was made before the sudden explosion of generative AI. The amount of computing resources used to train the largest AI models has been doubling roughly every 6 months for more than the past decade. At this rate, by 2030 training a single artificial-intelligence model would take one hundred times as much computing resources as the combined annual resources of the current top 10 super-computers. Simply put, computing will require colossal amounts of power, soon exceeding what our planet can provide.\",\"PeriodicalId\":13249,\"journal\":{\"name\":\"IEEE Spectrum\",\"volume\":\"61 6\",\"pages\":\"37-41\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Spectrum\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10551792/\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Spectrum","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10551792/","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
A Data Center in a Shoebox: IMEC's Plan to use Superconductors to Shrink Computers
What's more, this projection was made before the sudden explosion of generative AI. The amount of computing resources used to train the largest AI models has been doubling roughly every 6 months for more than the past decade. At this rate, by 2030 training a single artificial-intelligence model would take one hundred times as much computing resources as the combined annual resources of the current top 10 super-computers. Simply put, computing will require colossal amounts of power, soon exceeding what our planet can provide.
期刊介绍:
IEEE Spectrum Magazine, the flagship publication of the IEEE, explores the development, applications and implications of new technologies. It anticipates trends in engineering, science, and technology, and provides a forum for understanding, discussion and leadership in these areas.
IEEE Spectrum is the world''s leading engineering and scientific magazine. Read by over 300,000 engineers worldwide, Spectrum provides international coverage of all technical issues and advances in computers, communications, and electronics. Written in clear, concise language for the non-specialist, Spectrum''s high editorial standards and worldwide resources ensure technical accuracy and state-of-the-art relevance.