I will present an overview of quantum reservoir computing research done in my group at the University of Turku in Finland. Quantum reservoir computing is a paradigm for harnessing generic quantum systems to solve machine learning tasks. It offers a remarkably direct path from hardware to experiments, can in principle do the job of hundreds of classical neurons with just a few qubits, and is amenable to coherent processing of quantum signals to facilitate, e.g., state tomography with relatively simple resources. We specialize in continuous-variable schemes but have recently considered also schemes amenable to be run on Finnish quantum computers. I will conclude the talk with some research questions we hope to tackle in the near future.
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