  Quantum computers require precise control over parameters and careful
engineering of the underlying physical system. In contrast, neural networks
have evolved to tolerate imprecision and inhomogeneity. Here, using a reservoir
computing architecture we show how a random network of quantum nodes can be
used as a robust hardware for quantum computing. Our network architecture
induces quantum operations by optimising only a single layer of quantum nodes,
a key advantage over the traditional neural networks where many layers of
neurons have to be optimised. We demonstrate how a single network can induce
different quantum gates, including a universal gate set. Moreover, in the
few-qubit regime, we show that sequences of multiple quantum gates in quantum
circuits can be compressed with a single operation, potentially reducing the
operation time and complexity. As the key resource is a random network of
nodes, with no specific topology or structure, this architecture is a hardware
friendly alternative paradigm for quantum computation.
