Principles of Neuromorphic Photonics

In an age overrun with information, the ability to process reams of data has become crucial. The demand for data will continue to grow as smart gadgets multiply and become increasingly integrated into our daily lives. Next-generation industries in artificial intelligence services and high-performance computing are so far supported by microelectronic platforms. These data-intensive enterprises rely on continual improvements in hardware. Their prospects are running up against a stark reality: conventional one-size-fits-all solutions offered by digital electronics can no longer satisfy this need, as Moore's law (exponential hardware scaling), interconnection density, and the von Neumann architecture reach their limits. With its superior speed and reconfigurability, analog photonics can provide some relief to these problems; however, complex applications of analog photonics have remained largely unexplored due to the absence of a robust photonic integration industry. Recently, the landscape for commercially-manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. The scientific community has set out to build bridges between the domains of photonic device physics and neural networks, giving rise to the field of \emph{neuromorphic photonics}. This article reviews the recent progress in integrated neuromorphic photonics. We provide an overview of neuromorphic computing, discuss the associated technology (microelectronic and photonic) platforms and compare their metric performance. We discuss photonic neural network approaches and challenges for integrated neuromorphic photonic processors while providing an in-depth description of photonic neurons and a candidate interconnection architecture. We conclude with a future outlook of neuro-inspired photonic processing.Comment: 28 pages, 19 figure

A Survey Examining Neuromorphic Architecture in Space and Challenges from Radiation

Inspired by the human brain's structure and function, neuromorphic computing has emerged as a promising approach for developing energy-efficient and powerful computing systems. Neuromorphic computing offers significant processing speed and power consumption advantages in aerospace applications. These two factors are crucial for real-time data analysis and decision-making. However, the harsh space environment, particularly with the presence of radiation, poses significant challenges to the reliability and performance of these computing systems. This paper comprehensively surveys the integration of radiation-resistant neuromorphic computing systems in aerospace applications. We explore the challenges posed by space radiation, review existing solutions and developments, present case studies of neuromorphic computing systems used in space applications, discuss future directions, and discuss the potential benefits of this technology in future space missions.Comment: Submitted to IEEE Journal on Miniaturization for Air and Space System

Trends and challenges in neuroengineering: toward "Intelligent" neuroprostheses through brain-"brain inspired systems" communication

Future technologies aiming at restoring and enhancing organs function will intimately rely on near-physiological and energy-efficient communication between living and artificial biomimetic systems. Interfacing brain-inspired devices with the real brain is at the forefront of such emerging field, with the term "neurobiohybrids" indicating all those systems where such interaction is established. We argue that achieving a "high-level" communication and functional synergy between natural and artificial neuronal networks in vivo, will allow the development of a heterogeneous world of neurobiohybrids, which will include "living robots" but will also embrace “intelligent” neuroprostheses for augmentation of brain function. The societal and economical impact of intelligent neuroprostheses is likely to be potentially strong, as they will offer novel therapeutic perspectives for a number of diseases, and going beyond classical pharmaceutical schemes. However, they will unavoidably raise fundamental ethical questions on the intermingling between man and machine and more specifically, on how deeply it should be allowed that brain processing is affected by implanted "intelligent" artificial systems. Following this perspective, we provide the reader with insights on ongoing developments and trends in the field of neurobiohybrids. We address the topic also from a "community building" perspective, showing through a quantitative bibliographic analysis, how scientists working on the engineering of brain-inspired devices and brain-machine interfaces are increasing their interactions. We foresee that such trend preludes to a formidable technological and scientific revolution in brain-machine communication and to the opening of new avenues for restoring or even augmenting brain function for therapeutic purposes

On the eve of artificial minds

I review recent technological, empirical, and theoretical developments related to building sophisticated cognitive machines. I suggest that rapid growth in robotics, brain-like computing, new theories of large-scale functional modeling, and financial resources directed at this goal means that there will soon be a significant increase in the abilities of artificial minds. I propose a specific timeline for this development over the next fifty years and argue for its plausibility. I highlight some barriers to the development of this kind of technology, and discuss the ethical and philosophical consequences of such a development. I conclude that researchers in this field, governments, and corporations must take care to be aware of, and willing to discuss, both the costs and benefits of pursuing the construction of artificial minds

Magnetic domain walls : Types, processes and applications

Domain walls (DWs) in magnetic nanowires are promising candidates for a variety of applications including Boolean/unconventional logic, memories, in-memory computing as well as magnetic sensors and biomagnetic implementations. They show rich physical behaviour and are controllable using a number of methods including magnetic fields, charge and spin currents and spin-orbit torques. In this review, we detail types of domain walls in ferromagnetic nanowires and describe processes of manipulating their state. We look at the state of the art of DW applications and give our take on the their current status, technological feasibility and challenges.Comment: 32 pages, 25 figures, review pape

Analog Printed Spiking Neuromorphic Circuit

Biologically-inspired Spiking Neural Networks have emerged as a promising avenue for energy-efficient, high-performance neuromorphic computing. With the demand for highly-customized and cost-effective solutions in emerging application domains like soft robotics, wearables, or IoT-devices, Printed Electronics has emerged as an alternative to traditional silicon technologies leveraging soft materials and flexible substrates. In this paper, we propose an energy-efficient analog printed spiking neuromorphic circuit and a corresponding learning algorithm. Simulations on 13 benchmark datasets show an average of 3.86× power improvement with similar classification accuracy compared to previous works

Intelligent Computing: The Latest Advances, Challenges and Future

Computing is a critical driving force in the development of human civilization. In recent years, we have witnessed the emergence of intelligent computing, a new computing paradigm that is reshaping traditional computing and promoting digital revolution in the era of big data, artificial intelligence and internet-of-things with new computing theories, architectures, methods, systems, and applications. Intelligent computing has greatly broadened the scope of computing, extending it from traditional computing on data to increasingly diverse computing paradigms such as perceptual intelligence, cognitive intelligence, autonomous intelligence, and human-computer fusion intelligence. Intelligence and computing have undergone paths of different evolution and development for a long time but have become increasingly intertwined in recent years: intelligent computing is not only intelligence-oriented but also intelligence-driven. Such cross-fertilization has prompted the emergence and rapid advancement of intelligent computing. Intelligent computing is still in its infancy and an abundance of innovations in the theories, systems, and applications of intelligent computing are expected to occur soon. We present the first comprehensive survey of literature on intelligent computing, covering its theory fundamentals, the technological fusion of intelligence and computing, important applications, challenges, and future perspectives. We believe that this survey is highly timely and will provide a comprehensive reference and cast valuable insights into intelligent computing for academic and industrial researchers and practitioners