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Neukart, Florian
Volkswagen Group of America, University of Leiden
San Francisco, California
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| | Florian Neukart holds a PhD in Quantum Computing and Artificial Intelligence from the Transilvania University of Brasov, as well as a Master’s degree in Information Technology from the CAMPUS02 University of Applied Sciences in Graz, and a Master’s degree in Computer Science from the Joanneum University of Applied Sciences in Kapfenberg. He works as a principal scientist in the fields of artificial intelligence and quantum computing at Volkswagen Group of America, where he is conducting research in the fields of self-driving vehicles, quantum machine learning, self-optimizing robots, and artificial intelligence in general. Neukart, born in Bruck an der Mur, Austria, is also a lecturer at Leiden University, where he works on quantum computing and artificial intelligence. He is the author of the book Reverse Engineering the Mind - Consciously Acting Machines and Accelerated Evolution. Here, he is concerned with establishing a symbiotic relationship between a biological brain, sensors, AI, and quantum hardware and software, resulting in solutions for the continuous consciousness-problem as well as other state-of-the-art problems. He was one of the first researchers to propose and implement quantum neural networks, and among the first ones to solve real-world problems of society and environment by means of quantum computing/annealing. In 2014, Neukart was awarded for his work in biologically inspired artificial intelligence software by the Science Park Austria. |
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Date Reviewed |
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1 - 5 of 5
reviews
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 Universal quantum computing: supervening decoherence -- surmounting uncertainty
Amoroso R., World Scientific Publishing Co, Inc., Hackensack, NJ, 2017. 632 pp. Type: Book
Quantum computing is one of the hottest research fields right now, although the theory behind it had its start in the early 1980s, when Richard Feynman asked in a lecture why simulating quantum effects with classical (non-quantum) comp...
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May 22 2019 |
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Introduction to morphogenetic computing
Resconi G., Xu X., Xu G., Springer International Publishing, New York, NY, 2017. 172 pp. Type: Book (978-3-319576-14-5)
Morphogenetic computing is a fundamentally new approach to computing that attempts to add consistency and stability in uncertain situations. Valued logic or machine learning may be applied to reason in uncertain situations. However, th...
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Mar 30 2018 |
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Optimization and approximation
Pedregal P., Springer International Publishing, New York, NY, 2017. 254 pp. Type: Book (978-3-319648-42-2)
Optimization problems are ubiquitous, and the term alone indicates that it is important. Mathematically, optimization refers to finding the largest or the smallest value that a function can take. For our everyday lives, this can range ...
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Feb 28 2018 |
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Perturbations, optimization, and statistics
Hazan T., Papandreou G., Tarlow D., The MIT Press, Cambridge, MA, 2016. 412 pp. Type: Book (978-0-262035-64-4)
The latest research in machine learning shows that the injection of perturbations into both learning and inference procedures may result in increased predictive accuracy. In almost every machine learning problem, decisions are made bas...
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Oct 19 2017 |
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Deep learning
Goodfellow I., Bengio Y., Courville A., The MIT Press, Cambridge, MA, 2016. 800 pp. Type: Book (978-0-262035-61-3), Reviews: (2 of 4)
Deep learning is used everywhere, from environment perception in self-driving vehicles to natural language understanding, to fraud and real-time threat detection, to name only a few examples. This book introduces both the fundamental a...
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Jul 12 2017 |
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