PlasmoniAC is a 3-year long H2020 research project aiming to release a whole new class of energy- and size-efficient feed-forward and recurrent artificial plasmonic neurons with up to 100 GHz clock frequencies and 1 and 6 orders of magnitude better energy- and footprint-efficiencies, comparing to the current electronics-based state-of-the art. It adopts the best-in-class material and technology platforms for optimizing computational power, size and energy at every of its constituent functions, harnessing the proven high-bandwidth and low-loss credentials of photonic interconnects together with the nm-size memory function of memristor nanoelectronics, bridging them by introducing plasmonics as the ideal technology for offering photonic-level bandwidths and electronic-level footprint computations within ultra-low energy consumption envelopes. In a holistic hardware/software co-design approach, PlasmoniAC will follow the path from technology development to addressing real application needs by developing a new set of DL training models and algorithms and embedding its new technology into ready-to-use software libraries.