Dr. Vedran Dunjko from the Max Planck Institute for Quantum Optics will visit our group and give a talk on "Machine learning and Quantum Information Processing: match or hype?" on Friday, May 4th at 10.30am at Pfaffenwaldring 57, Room 6.331.
Abstract
The nascent field of Quantum Machine Learning (QML) has been generating a substantial buzz in the last few years. QML research is typically driven by two basic objectives: finding ways in which quantum information processing (QIP) can help with machine learning (ML) problems, and, conversely, understanding the extent to which ML can be beneficially applied in QIP settings. In this overview talk, I will introduce basic ideas from QIP and use them to showcase how the parallels between the disciplines of QIP and ML drive these main research lines of QML. This will be substantiated through a selection of recent results which probe the potential and limitations of quantum-enhanced learning, followed by a snapshot of fresh proposals exploiting ML techniques in the context of quantum experiments. Such results have been used to suggest not only that (Q)ML applications may be among the best reasons to build quantum computers in the first place, but also that ML may find vital applications in building genuinely useful quantum computers. Whether or not such claims have merit, or are perhaps understatements, will be discussed as well.
Time permitting, the talk will finish with a more personal take on the field, which also touches the broader topic of the interplay of artificial general intelligence and quantum mechanics.