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/ .
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