[3][4] He is best known for his foundational and highly-cited[5] work on long short-term memory (LSTM), a type of neural network architecture which was the dominant technique for various natural language processing tasks in research and commercial applications in the 2010s.

[1] He has served as the director of Dalle Molle Institute for Artificial Intelligence Research (IDSIA), a Swiss AI lab, since 1995.

[1] In 2014, Schmidhuber formed a company, Nnaisense, to work on commercial applications of artificial intelligence in fields such as finance, heavy industry and self-driving cars.

[13] In the 1980s, backpropagation did not work well for deep learning with long credit assignment paths in artificial neural networks.

To overcome this problem, Schmidhuber (1991) proposed a hierarchy of recurrent neural networks (RNNs) pre-trained one level at a time by self-supervised learning.

Schmidhuber supervised the 1991 diploma thesis of his student Sepp Hochreiter[18] which he considered "one of the most important documents in the history of machine learning".

[20] Today's "vanilla LSTM" using backpropagation through time was published with his student Alex Graves in 2005,[21][22] and its connectionist temporal classification (CTC) training algorithm[23] in 2006.

By the 2010s, the LSTM became the dominant technique for a variety of natural language processing tasks including speech recognition and machine translation, and was widely implemented in commercial technologies such as Google Neural Machine Translation,[24] have also been used in Google Voice for transcription[25] and search,[26] and Siri.

[36] In 2011, Schmidhuber's team at IDSIA with his postdoc Dan Ciresan also achieved dramatic speedups of convolutional neural networks (CNNs) on fast parallel computers called GPUs.

[37] The deep CNN of Dan Ciresan et al. (2011) at IDSIA was already 60 times faster[38] and achieved the first superhuman performance in a computer vision contest in August 2011.

[2][44][45] He wrote a "scathing" 2015 article arguing that Hinton, Bengio and Lecun "heavily cite each other" but "fail to credit the pioneers of the field".

[45] In a statement to the New York Times, Yann LeCun wrote that "Jürgen is manically obsessed with recognition and keeps claiming credit he doesn't deserve for many, many things...

"[62][55] Schmidhuber himself, however, has called Alexey Grigorevich Ivakhnenko the "father of deep learning,"[63][64] and gives credit to many even earlier AI pioneers.