Hands-On Advice for Using Quantum Computers in AI - Peter Wittek - at скачать в хорошем качестве

Hands-On Advice for Using Quantum Computers in AI - Peter Wittek - at

Hands-On Advice for Using Quantum Computers in AI Machine learning and quantum computing receive much attention, and the combination of the two is a recipe for a hype. Expectations are often out of proportions, but this is in sharp contrast with the reality of quantum computing: implementations are small-scale, imperfect, they suffer from noise and poor coherence time. In this talk, we study what can be done with contemporary quantum computers. The primary algorithmic primitives are solving sampling, optimization, and some variational problems efficiently with hybrid classical-quantum protocols. The main application areas in machine learning are intrinsically discrete or probabilistic models and certain types of neural networks. We will highlight a few applications created by a new breed of startup companies in Toronto that are being incubated to exploit the relevant quantum technologies. Peter Wittek is an Assistant Professor in the University of Toronto and an affiliate in the Vector Institute for Artificial Intelligence the Perimeter Institute for Theoretical Physics. He obtained his PhD from the National University of Singapore. His research explores the synergies between artificial intelligence, machine learning, quantum information theory, and quantum computing. As the Academic Director of the Quantum Program in the Creative Destruction Lab, he oversees two dozen quantum software startups a year that exploit contemporary quantum technologies in a commercial setting.