深度学习时代，“计算鸿沟”正在集中权力，加剧不平等

{"type":"doc","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"来自弗吉尼亚理工学院暨州立大学（Virginia Tech）和西方大学（Western University）的人工智能研究人员得出结论称，学术界算力的不平等分配正在加剧深度学习时代的不平等。他们还指出了那些离开名牌大学去从事高薪行业工作的人对学术界产生的影响。"}]},{"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":"通过分析来自近 60 个著名计算机科学会议的 171394 篇论文，得出结论认为算力集中在精英大学，挤掉了中低层研究机构。该团队审查了"},{"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":"等大型人工智能会议上接受发表的论文，这些论文涉及计算机视觉、数据挖掘、机器学习和自然语言处理等类别。"}]},{"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":"他们在论文中写道：“深度学习自 2012 年以来由于 GPU 的意外使用而迅速崛起，我们发现人工智能正越来越多地被少数参与者所塑造，而这些参与者大多隶属于大型科技公司或精英大学。要想真正实现人工智能的‘民主化’，需要政策制定者、学术机构和企业层面的行动者共同努力，以解决计算鸿沟问题。”"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}}]}