本頁只刊出中文翻譯與中文說明；英文原文請見下方原文連結。
原文連結
論文資訊
- 類型：已發表論文
- 日期：2022-05-09
摘要
When computers started to become a dominant part of technology around the 1950s, fundamental questions about reliable designs and robustness were of great relevance. Their development gave rise to the exploration of new questions, such as what made 大腦s reliable (since neurons can die) and how computers could get inspiration from 神經 systems. In parallel, the first artificial 神經 網絡s came to life. Since then, the comparative view between 大腦s and computers has been developed in new, sometimes unexpected directions. With the rise of 深度學習 and the development of connectomics, an 演化ary look at how both hardware and 神經 complexity have evolved or designed is required. In this paper, we argue that important similarities have resulted both from convergent 演化 (the inevitable outcome of architectural co
※ 此為已發表論文，全文需透過期刊付費取得