With advent of quantum internet, it becomes crucial to find novel ways to
connect distributed quantum testbeds and develop novel technologies and
research that extend innovations in managing the qubit performance. Numerous
emerging technologies are focused on quantum repeaters and specialized hardware
to extend the quantum distance over special-purpose channels. However, there is
little work that utilizes current network technology, invested in optic
technologies, to merge with quantum technologies. In this paper we argue for an
AI-enabled control that allows optimized and efficient conversion between qubit
and photon energies, to enable optic and quantum devices to work together. Our
approach integrates AI techniques, such as deep reinforcement learning
algorithms, with physical quantum transducer to inform real-time conversion
between the two wavelengths. Learning from simulated environment, the trained
AI-enabled transducer will lead to optimal quantum transduction to maximize the
qubit lifetime.