23 papers · ranked by Valyu relevance
Adnan Mehonić, Anthony J. Kenyon
New computing technologies inspired by the brain promise fundamentally different ways to process information with extreme energy efficiency and the ability to handle the avalanche of unstructured and noisy data that we are generating at an ever-increasing rate. To realise this promise requires a brave and coordinated…
Dmitry Ivanov, Aleksandr Chezhegov, Andrey Grunin, М. Г. Киселев + 1 more
'Denis Larionov'] Modern AI systems, based on von Neumann architecture and classical neural networks, have a number of fundamental limitations in comparison with the brain. This article discusses such limitations and the ways they can be mitigated. Next, it presents an overview of currently available neuromorphic AI…
Ruslan V. Kutluyarov, Aida G. Zakoyan, Grigory S. Voronkov, Elizaveta P. Grakhova + 2 more
Neuromorphic photonics is a cutting-edge fusion of neuroscience-inspired computing and photonics technology to overcome the constraints of conventional computing architectures. Its significance lies in the potential to transform information processing by mimicking the parallelism and efficiency of the human brain.…
Zhengguang Zhu, Nicholas Schaffer, Xiao Yang
Neuromorphic devices are bioinspired electronic systems that mimic key structures and functions of the nervous system, enabling integration and communication between living tissues and machines. This review examines how neuromorphic devices and computing are designed to emulate the structure, organization, and function…
Dmitry Ivanov, Aleksandr Chezhegov, Mikhail Kiselev, Andrey Grunin + 1 more
'Denis Larionov'] Modern artificial intelligence (AI) systems, based on von Neumann architecture and classical neural networks, have a number of fundamental limitations in comparison with the mammalian brain. In this article we discuss these limitations and ways to mitigate them. Next, we present an overview of…
Adnan Mehonić, Daniele Ielmini, Kaushik Roy, Onur Mutlu + 49 more
'Shahar Kvatinsky' 'Teresa Serrano‐Gotarredona' 'B. Linares-Barranco' 'Sabina Spiga' 'Sergey Savel’ev' 'A. G. Balanov' 'Nitin Chawla' 'Giuseppe Desoli' 'Gerardo Malavena' 'Christian Monzio Compagnoni' 'Zhongrui Wang' 'J. Joshua Yang' 'Syed Ghazi Sarwat' 'Abu Sebastian' 'Thomas Mikolajick' 'Beatriz Noheda' 'Stefan…
Maryada, Chiara De Luca, Arianna Rubino, Chenxi Wen + 4 more
Cortical microcircuits play a fundamental role in natural intelligence. While they inspired a wide range neural computation models and artificial intelligence algorithms, few attempts have been made to directly emulate them with an electronic computational substrate that uses the same physics of computation. Here we…
Michael L. Helde, Alexander G. Dimitrov
We adapted an olfactory neuromorphic algorithm to image and sound recognition. To achieve this, we carried out specific preprocessing procedures that were tailored to each modality. For images, we used the NIST digits dataset directly. For sound, we used samples from the Google Speech Command dataset. A gammatone…
Francesca Borghi, Thierry R. Nieus, Davide E. Galli, Paolo Milani
The brain’s ability to perform efficient and fault-tolerant data processing is strongly related to its peculiar interconnected adaptive architecture, based on redundant neural circuits interacting at different scales. By emulating the brain’s processing and learning mechanisms, computing technologies strive to achieve…
Wei Ou, Shitao Xiao, Chengyu Zhu, Wenbao Han + 1 more
With the development of technology, Moore's law will come to an end, and scientists are trying to find a new way out in brain-like computing. But we still know very little about how the brain works. At the present stage of research, brain-like models are all structured to mimic the brain in order to achieve some of the…
Dmitrii Zendrikov, Sergio Solinas, Giacomo Indiveri
Neuromorphic processing systems implementing spiking neural networks with mixed signal analog/digital electronic circuits and/or memristive devices represent a promising technology for edge computing applications that require low power, low latency, and that cannot connect to the cloud for off-line processing, either…
Gianvito Urgese, Antonio Rios-Navarro, Alejandro Linares-Barranco, Terrence C. Stewart + 1 more
The brain, this 3-pound mass of tissue that can easily be held in one's palm, has an inherent computational complexity that has always inspired efforts to endorse machines with some of its remarkable characteristics. Ironically, the brain computes in its own way, compared to analog or digital computers, despite sharing…
Toshiyuki Yamane, Akira Hirose, Bert Jan Offrein
The major energy consumer of today's digital processor is data movement between MAC processors and volatile main memories. This motivates integration of memory and computation called “in-memory computing.” Use of intrinsic properties of materials for in-memory computing is becoming very promising approach for in-memory…
Maryada, Saray Soldado-Magraner, Martino Sorbaro, Rodrigo Laje + 2 more
Many neural computations emerge from self-sustained patterns of activity in recurrent neural circuits, which rely on balanced excitation and inhibition. Neuromorphic electronic circuits that use the physics of silicon to emulate neuronal dynamics represent a promising approach for implementing the brain’s computational…
S. J. Ben Yoo, Luis El-Srouji, Suman Datta, Shimeng Yu + 10 more
Computing Approach with Photonic, Electronic, and Ionic Dynamicity in 3D integrated circuits Authors: ['S. J. Ben Yoo' 'Luis El-Srouji' 'Suman Datta' 'Shimeng Yu' 'Jean Anne C. Incorvia' 'Alberto Salleo' 'Volker J. Sorger' 'Juejun Hu' 'Lionel C. Kimerling' 'Kristofer E. Bouchard' 'Joy Geng' 'Rishidev Chaudhuri' 'Charan…
Davide Cipollini, Hugh Greatorex, Michele Mastella, Elisabetta Chicca + 1 more
In an era characterized by the rapid growth of data processing, developing new and efficient data processing technologies has become a priority. We address this by proposing a novel type of neuromorphic technology we call Fused-MemBrain. Our proposal is inspired by Golgi's theory modeling the brain as a syncytial…
Alessandro Bile, Hamed Tari, Riccardo Pepino, Arif Nabizada + 2 more
'Eugenio Fazio' 'Simon X. Yang'] In recent years, the need for systems capable of achieving the dynamic learning and information storage efficiency of the biological brain has led to the emergence of neuromorphic research. In particular, neuromorphic optics was born with the idea of reproducing the functional and…
Andrey E. Schegolev, M. V. Bastrakova, Michael A. Sergeev, A. A. Maksimovskaya + 2 more
'A. A. Maksimovskaya' 'N. V. Klenov' 'I. I. Soloviev'] The extensive development of the field of spiking neural networks has led to many areas of research that have a direct impact on people's lives. As the most bio-similar of all neural networks, spiking neural networks not only allow the solution of recognition and…
Hongwei Cai, Zheng Ao, Chunhui Tian, Zhuhao Wu + 5 more
Brain-inspired hardware emulates the structure and working principles of a biological brain and may address the hardware bottleneck for fast-growing artificial intelligence (AI). Current brain-inspired silicon chips are promising but still limit their power to fully mimic brain function for AI computing. Here, we…
Alexander James White, Belle Liu, Ming-Ju Hsieh, Meng-Fan Chang + 2 more
Biological neural circuits at various levels exhibit rapid adaptability to diverse environmental stimuli. Such fast response times imply that adaptation cannot rely solely on synaptic plasticity, which operates on a much slower timescale. Instead, circuits must be inherently hyper-flexible and receptive to switches in…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Authors not listed
A memristor is a two-terminal electronic component that modify its conductance state depending on how much charge has passed through it previously. Halide perovskites are materials recently employed for neuromorphic computing in this type of resistive switches. Their performance is rapidly improving, yet the activation…
Authors not listed
Artificial intelligence (AI) is reshaping scientific research by accelerating discovery and enabling the analysis of complex data that traditional methods struggle to handle. This review examines over 310,000 journal articles and patents from the CAS Content Collection (2015–2025), with a focus on, biomedical research…