{"title":"对《中程》的狭隘评价","authors":"Ultan Byrne","doi":"10.1177/14780771231170271","DOIUrl":null,"url":null,"abstract":"This paper recommends that critical attention towards machine learning should be focused on the ordering procedures at work in these models. More precisely, it draws attention to the central role of ‘latent spaces.’ The paper first explores ‘latent space’ through a series of analogies, and then briefly situates the concept in relation to a genealogy reaching back to developments in mathematical statistics at the turn to the 20th century.","PeriodicalId":45139,"journal":{"name":"International Journal of Architectural Computing","volume":"21 1","pages":"374 - 379"},"PeriodicalIF":1.6000,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Parochial Comment on Midjourney\",\"authors\":\"Ultan Byrne\",\"doi\":\"10.1177/14780771231170271\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper recommends that critical attention towards machine learning should be focused on the ordering procedures at work in these models. More precisely, it draws attention to the central role of ‘latent spaces.’ The paper first explores ‘latent space’ through a series of analogies, and then briefly situates the concept in relation to a genealogy reaching back to developments in mathematical statistics at the turn to the 20th century.\",\"PeriodicalId\":45139,\"journal\":{\"name\":\"International Journal of Architectural Computing\",\"volume\":\"21 1\",\"pages\":\"374 - 379\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2023-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Architectural Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/14780771231170271\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Architectural Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/14780771231170271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"ARCHITECTURE","Score":null,"Total":0}
This paper recommends that critical attention towards machine learning should be focused on the ordering procedures at work in these models. More precisely, it draws attention to the central role of ‘latent spaces.’ The paper first explores ‘latent space’ through a series of analogies, and then briefly situates the concept in relation to a genealogy reaching back to developments in mathematical statistics at the turn to the 20th century.