Optical machine learning has emerged as an important research area that, by leveraging the advantages inherent to optical signals, such as parallelism and high speed, paves the way for a future where optical hardware can process data at the speed of light. In this work, we present such optical devices for data processing in the form of single-layer nanoscale holographic perceptrons trained to perform optical inference tasks. We experimentally show the functionality of these passive optical devices in the example of decryptors trained to perform optical inference of single or whole classes of keys through symmetric and asymmetric decryption. The decryptors, designed for operation in the near-infrared region, are nanoprinted on complementary metal-oxide–semiconductor chips by galvo-dithered two-photon nanolithography with axial nanostepping of 10 nm1,2, achieving a neuron density of >500 million neurons per square centimetre. This power-efficient commixture of machine learning and on-chip integration may have a transformative impact on optical decryption3, sensing4, medical diagnostics5 and computing6,7.

Neuromorphic computing applies concepts extracted from neuroscience to develop devices shaped like neural systems and achieve brain-like capacity and efficiency. In this way, neuromorphic machines, able to learn from the surrounding environment to deduce abstract concepts and to make decisions, promise to start a technological revolution transforming our society and our life. Current electronic implementations of neuromorphic architectures are still far from competing with their biological counterparts in terms of real-time information-processing capabilities, packing density and energy efficiency. A solution to this impasse is represented by the application of photonic principles to the neuromorphic domain creating in this way the field of neuromorphic photonics. This new field combines the advantages of photonics and neuromorphic architectures to build systems with high efficiency, high interconnectivity and high information density, and paves the way to ultrafast, power efficient and low cost and complex signal processing. In this Perspective, we review the rapid development of the neuromorphic computing field both in the electronic and in the photonic domain focusing on the role and the applications of memristors. We discuss the need and the possibility to conceive a photonic memristor and we offer a positive outlook on the challenges and opportunities for the ambitious goal of realising the next generation of full-optical neuromorphic hardware.

ErbB2 overexpression drives oncogenesis in 20–30% cases of breast cancer. Oncogenic potential of ErbB2 is linked to inefficient endocytic traffic into lysosomes and preferential recycling. However, regulation of ErbB2 recycling is incompletely understood. We used a high-content immunofluorescence imaging-based kinase inhibitor screen on SKBR-3 breast cancer cells to identify kinases whose inhibition alters the clearance of cell surface ErbB2 induced by Hsp90 inhibitor 17-AAG. Less ErbB2 clearance was observed with broad-spectrum PKC inhibitor Ro 31-8220. A similar effect was observed with Go 6976, a selective inhibitor of classical Ca2+-dependent PKCs (α, β1, βII, and γ). PKC activation by PMA promoted surface ErbB2 clearance but without degradation, and ErbB2 was observed to move into a juxtanuclear compartment where it colocalized with PKC-α and PKC-δ together with the endocytic recycling regulator Arf6. PKC-α knockdown impaired the juxtanuclear localization of ErbB2. ErbB2 transit to the recycling compartment was also impaired upon PKC-δ knockdown. PMA-induced Erk phosphorylation was reduced by ErbB2 inhibitor lapatinib, as well as by knockdown of PKC-δ but not that of PKC-α. Our results suggest that activation of PKC-α and -δ mediates a novel positive feedback loop by promoting ErbB2 entry into the endocytic recycling compartment, consistent with reported positive roles for these PKCs in ErbB2-mediated tumorigenesis. As the endocytic recycling compartment/pericentrion has emerged as a PKC-dependent signaling hub for G-protein-coupled receptors, our findings raise the possibility that oncogenesis by ErbB2 involves previously unexplored PKC-dependent endosomal signaling.