{"title":"为什么学习和机器学习不同","authors":"J. Végh, Ádám-József Berki","doi":"10.54364/aaiml.2021.1109","DOIUrl":null,"url":null,"abstract":"Machine learning intends to be a biology-mimicking learningmethod, implemented bymeans of technical computing. Their technology and methods, however, differ very much; mainly because technological computing is based on the time-unaware classic computing paradigm. Based on the time-aware computing paradigm, the paper discovers the mechanism of biological information storing and learning; furthermore, it explains, why biological and technological information handling and learning are entirely different. The consequences of the huge difference in transmission speed in those computing systems may remain hidden in “toy”-level technological systems but comes to the light in systems having large size and/or mimicking neuronal operations. The biology-mimicking technological operations are in resemblance to the biological operations only when using time-unaware computing paradigm. The difference leads also to the need of introducing “training” mode (with desperately low efficiency) in technological learning, while biological systems have the ability of life-long learning. It is at least misleading to use technological learning methods to complement biological learning studies. The examples show evidence for the effect of transmission time in published experiments.","PeriodicalId":373878,"journal":{"name":"Adv. Artif. Intell. Mach. Learn.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Why Learning and Machine Learning Are Different\",\"authors\":\"J. Végh, Ádám-József Berki\",\"doi\":\"10.54364/aaiml.2021.1109\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Machine learning intends to be a biology-mimicking learningmethod, implemented bymeans of technical computing. Their technology and methods, however, differ very much; mainly because technological computing is based on the time-unaware classic computing paradigm. Based on the time-aware computing paradigm, the paper discovers the mechanism of biological information storing and learning; furthermore, it explains, why biological and technological information handling and learning are entirely different. The consequences of the huge difference in transmission speed in those computing systems may remain hidden in “toy”-level technological systems but comes to the light in systems having large size and/or mimicking neuronal operations. The biology-mimicking technological operations are in resemblance to the biological operations only when using time-unaware computing paradigm. The difference leads also to the need of introducing “training” mode (with desperately low efficiency) in technological learning, while biological systems have the ability of life-long learning. It is at least misleading to use technological learning methods to complement biological learning studies. The examples show evidence for the effect of transmission time in published experiments.\",\"PeriodicalId\":373878,\"journal\":{\"name\":\"Adv. Artif. Intell. Mach. Learn.\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Adv. Artif. Intell. Mach. Learn.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54364/aaiml.2021.1109\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Adv. Artif. Intell. Mach. Learn.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54364/aaiml.2021.1109","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Machine learning intends to be a biology-mimicking learningmethod, implemented bymeans of technical computing. Their technology and methods, however, differ very much; mainly because technological computing is based on the time-unaware classic computing paradigm. Based on the time-aware computing paradigm, the paper discovers the mechanism of biological information storing and learning; furthermore, it explains, why biological and technological information handling and learning are entirely different. The consequences of the huge difference in transmission speed in those computing systems may remain hidden in “toy”-level technological systems but comes to the light in systems having large size and/or mimicking neuronal operations. The biology-mimicking technological operations are in resemblance to the biological operations only when using time-unaware computing paradigm. The difference leads also to the need of introducing “training” mode (with desperately low efficiency) in technological learning, while biological systems have the ability of life-long learning. It is at least misleading to use technological learning methods to complement biological learning studies. The examples show evidence for the effect of transmission time in published experiments.