深度學習時代，“計算鴻溝”正在集中權力，加劇不平等

{"type":"doc","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"來自弗吉尼亞理工學院暨州立大學（Virginia Tech）和西方大學（Western University）的人工智能研究人員得出結論稱，學術界算力的不平等分配正在加劇深度學習時代的不平等。他們還指出了那些離開名牌大學去從事高薪行業工作的人對學術界產生的影響。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"通過分析來自近 60 個著名計算機科學會議的 171394 篇論文，得出結論認爲算力集中在精英大學，擠掉了中低層研究機構。該團隊審查了"},{"type":"link","attrs":{"href":"https:\/\/venturebeat.com\/2020\/07\/09\/ai-researchers-create-testing-tool-to-find-bugs-in-nlp-from-amazon-google-and-microsoft\/","title":"","type":null},"content":[{"type":"text","text":"ACL"}]},{"type":"text","text":"、"},{"type":"link","attrs":{"href":"https:\/\/venturebeat.com\/2019\/06\/14\/ai-weekly-icml-2019-top-papers-and-highlights\/","title":"","type":null},"content":[{"type":"text","text":"ICML"}]},{"type":"text","text":"和"},{"type":"link","attrs":{"href":"https:\/\/venturebeat.com\/2019\/12\/13\/ai-weekly-neurips-proves-machine-learning-at-scale-is-hard\/","title":"","type":null},"content":[{"type":"text","text":"NeurIPS"}]},{"type":"text","text":"等大型人工智能會議上接受發表的論文，這些論文涉及計算機視覺、數據挖掘、機器學習和自然語言處理等類別。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"他們在論文中寫道：“深度學習自 2012 年以來由於 GPU 的意外使用而迅速崛起，我們發現人工智能正越來越多地被少數參與者所塑造，而這些參與者大多隸屬於大型科技公司或精英大學。要想真正實現人工智能的‘民主化’，需要政策制定者、學術機構和企業層面的行動者共同努力，以解決計算鴻溝問題。”"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}}]}