{"title":"Memristors enabling probabilistic AI at the edge","authors":"Damien Querlioz","doi":"10.1038/s43588-024-00761-x","DOIUrl":null,"url":null,"abstract":"By combining several probabilistic AI algorithms, a recent study demonstrates experimentally that the inherent noise and variation in memristor nanodevices can be exploited as features for energy-efficient on-chip learning.","PeriodicalId":74246,"journal":{"name":"Nature computational science","volume":"5 1","pages":"7-8"},"PeriodicalIF":18.3000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature computational science","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s43588-024-00761-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
By combining several probabilistic AI algorithms, a recent study demonstrates experimentally that the inherent noise and variation in memristor nanodevices can be exploited as features for energy-efficient on-chip learning.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
