Deep Learning has emerged as one of the most successful fields of artificial intelligence with overwhelming success in industrial speech, language and vision benchmarks. Consequently it evolved into the central field of research for IT giants like Google, facebook, Microsoft, Baidu, and Amazon. Deep Learning is founded on novel neural network techniques, the recent availability of very fast computers, and massive data sets.
At the JKU Linz, we apply Deep Learning to advance autonomous driving in the AUDI Deep Learning Center and with NVIDIA, ZF and Bosch. Using Deep Learning we won the NIH Tox21 challenge and deploy it to toxicity and target prediction in collaboration with pharma companies like Janssen, UCB, Merck, AstraZeneca, and Bayer. With local companies (e.g. FILL and DCS) we apply Deep Learning to task in the field of plant and machine engineering. Together with Zalando we use Deep Learning for analyzing fashion images and fashion blogs.
Long Short-Term Memory (LSTM, invented by me) has been used to compose new music pieces and to write story-books of theater pieces. Deep learning with style-transfer has be used to transfer music of one style to another, has been used to transfer images from one painting style to another, has been used for supporting design in fashion. Recently, exhibitions dedicated to art made purely by deep learning were made in some galleries, e.g. in New York’s Chelsea gallery. See examples under http://nips4creativity.com/ and https://aiartists.org/ .
Sepp Hochreiter is heading the Institute for Machine Learning, the LIT AI Lab and the AUDI.JKU deep learning center at the Johannes Kepler University of Linz and is director of the Institute of Advanced Research in Artificial Intelligence (IARAI). He is regarded as a pioneer of Deep Learning as he discovered the fundamental deep learning problem: deep neural networks are hard to train, because they suffer from the now famous problem of vanishing or exploding gradients. He is best known for inventing the long short-term memory (LSTM) in his diploma thesis 1991 which was later published in 1997. LSTMs have emerged into the best-performing techniques in speech and language processing and are used in Google’s Android, in Apple’s iOS, Google’s translate, Amazon’s Alexa, and Facebook’s translation. Currently, Sepp Hochreiter is advancing the theoretical foundation of Deep Learning, investigates new algorithms for deep learning, and reinforcement learning. His current research projects include Deep Learning for climate change, smart cities, drug design, for text and language analysis, for vision, and in particular for autonomous driving.