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于尔根·施密德胡伯

编辑
于尔根·施密德胡伯

Jürgen Schmidhuber（生于1963年1月17日）[1]是一位计算机科学家，以其在人工智能、深度学习和人工神经网络领域的工作而闻名。他是位于瑞士南部提契诺卢加诺区的曼诺的Dalle Molle人工智能研究所的联合主任。有时他被称为“现代人工智能之父”[2][3][4][5][6]或者“深度学习之父”。[7]

Schmidhuber在德国慕尼黑工业大学完成了他的本科学业。[1]自2004年到2009年，他在瑞士卢加诺的意大利大学担任人工智能教授。

1 工作编辑

Schmidhuber和他的学生Sepp Hochreiter，Felix Gers，Fred Cummins，Alex Graves以及其他人一起，出版了一种叫做长期短期记忆（LSTM）的循环神经网络的日益复杂的版本。Hochreiter的毕业论文(1991)中已经报告了第一批成果，其中分析并克服了著名的消失梯度问题。[8]“LSTM”这个名字是在一份技术报告（1995年）中提出的，该报告是被引用最多的LSTM出版物（1997）。[9]几乎所有当前应用中使用的标准LSTM体系结构于2000年推出。[10]现在的使用通过时间的反向传播技术的“vanilla LSTM”于2005年出版，[11][12]连接时序分类训练算法[13]于2006年出版。连接时序分类支持与LSTM的端到端语音识别。

2015年，由连接时序分类训练的LSTM被用于谷歌智能手机软件中新开发的语音识别。[14]谷歌也用LSTM作为智能助手Allo[14] 和谷歌翻译。[15][16]苹果在苹果手机上使用了LSTM技术的“快速输入”功能[17][18]和Siri。[19]亚马逊将LSTM用于亚马逊Alexa。[20]2017年，Facebook每天使用LSTM网络进行约45亿次自动翻译。[21]彭博商业周刊写道:“这些能力使LSTM成为最商业化的人工智能成就，用于预测疾病到作曲的各个领域。”[22]

2011年，Schmidhuber在IDSIA的团队和他的博士后研究生Dan Ciresan在称为GPU的快速并行计算设备上实现了卷积神经网络（CNN）的显著加速。Chellapilla等人（2006）在GPU上实现的早期CNN比在CPU上的同等实现快4倍。[23]Dan Ciresan等人2011年时在IDSIA中提出的深度循环神经网络已经快了60倍[24]，并在2011年8月的计算机视觉竞赛中取得了第一次惊人表现。[25]在2011年5月15日至2012年9月10日期间，他们的快速深度循环神经网络赢得了不下四场图像比赛。[26][27]他们还显著提高了多个图像数据库在文献检索中的最佳性能。[28]这种方法已经成为计算机视觉。[27]该方法基于Yann LeCun等人早期（1989年）引入的循环神经网络的设计[29]，他们将反向传播算法应用于福岛核电站原始循环神经网络架构的一个变种，被称为神经认知机，[30]后来被翁氏方法修改为最大池化。[31][27]

2014年，Schmidhuber成立了一家名为Nnaisense的公司，致力于人工智能在金融、重工业和自动驾驶汽车等领域的商业应用。Sepp Hochreiter、Jaan Tallinn和Marcus Hutter是该公司的顾问。[14]2016年销售额在1100万美元以下；然而，Schmidhuber指出，目前的重点是研究，而非盈利。纳尼森在2017年1月进行了第一轮融资。Schmidhuber的总体目标是通过在各种单方面的任务中依次训练单个人工智能来创建一个通用的人工智能；然而，一些怀疑者指出，像Arago股份有限公司和IBM这样的公司多年来已经将人工智能应用于各种不同的项目，但没有任何通用人工智能的迹象。[32]

2 争议编辑

据《卫报》报道，[33]Schmidhuber在一篇“2015尖刻文章”中抱怨说，深度学习研究员同事Geoffrey Hinton, Yann LeCun and Yoshua Bengio“大量引用彼此的成果”，但“不相信该领域的先驱”，据称他们低估了Schmidhuber和其他早期机器学习先驱的贡献，包括早在1965年发布第一个深度学习网络的Alexey Grigorevich Ivakhnenko。LeCun否认了这一指控，并表示Schmidhuber“一直宣称自己不应得的功劳”。[34][33]

3 荣誉编辑

Schmidhuber在2013年获得了 International Neural Network Society颁发的亥姆霍兹奖[34]和2016年IEEE计算智能学会神经网络先锋奖。[35]他是欧洲科学院的一员。[36][37]

参考文献

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    ^Recipients: Neural Networks Pioneer Award. Piscataway, NJ: IEEE Computational Intelligence Society. Accessed January 2019.].

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