A5051804629- Advanced Memory and Neural Computing
- Neural dynamics and brain function
- Neural Networks and Reservoir Computing
- Neural Networks and Applications
- Ferroelectric and Negative Capacitance Devices
- Neuroscience and Neural Engineering
- Neuroscience and Neuropharmacology Research
- EEG and Brain-Computer Interfaces
- Memory and Neural Mechanisms
- CCD and CMOS Imaging Sensors
- Neural and Behavioral Psychology Studies
- Fuzzy Logic and Control Systems
Intel (United States)
2021-2023
Intel (Israel)
2015
IBM (United States)
2013
IBM Research - Almaden
2012
University of Zurich
2010
ETH Zurich
2007-2010
Columbia University
2007-2010
SIB Swiss Institute of Bioinformatics
2007
Center for Theoretical Biological Physics
2007
Politecnico di Milano
2003-2004
Marching along the DARPA SyNAPSE roadmap, IBM unveils a trilogy of innovations towards TrueNorth cognitive computing system inspired by brain's function and efficiency. Judiciously balancing dual objectives functional capability implementation/operational cost, we develop simple, digital, reconfigurable, versatile spiking neuron model that supports one-to-one equivalence between hardware simulation is implementable using only 1272 ASIC gates. Starting with classic leaky integrate-and-fire...
The biologically inspired spiking neurons used in neuromorphic computing are nonlinear filters with dynamic state variables—very different from the stateless neuron models deep learning. next version of Intel's research processor, Loihi 2, supports a wide range stateful fully programmable dynamics. Here we showcase advanced that can be to efficiently process streaming data simulation experiments on emulated 2 hardware. In one example, Resonate-and-Fire (RF) compute Short Time Fourier...
The grand challenge of neuromorphic computation is to develop a flexible brain-inspired architecture capable wide array real-time applications, while striving towards the ultra-low power consumption and compact size biological neural systems. Toward this end, we fabricated building block modular architecture, neurosynaptic core. Our implementation consists 256 integrate-and-fire neurons 1,024×256 SRAM crossbar memory for synapses that fits in 4.2mm <sup...
A vast array of devices, ranging from industrial robots to self-driven cars or smartphones, require increasingly sophisticated processing real-world input data (image, voice, radio, ...). Interestingly, hardware neural network accelerators are emerging again as attractive candidate architectures for such tasks. The algorithms considered come two, largely separate, domains: machine-learning and neuroscience. These networks have very different characteristics, so it is unclear which approach...
Abstract A critical enabler for progress in neuromorphic computing research is the ability to transparently evaluate different solutions on important tasks and compare them state-of-the-art conventional solutions. The Intel Neuromorphic Deep Noise Suppression Challenge (Intel N-DNS Challenge), inspired by Microsoft DNS Challenge, tackles a ubiquitous commercially relevant task: real-time audio denoising. Audio denoising likely reap benefits of due its low-bandwidth, temporal nature relevance...
ORIGINAL RESEARCH article Front. Comput. Neurosci., 30 November 2007 | https://doi.org/10.3389/neuro.10.007.2007
A critical enabler for progress in neuromorphic computing research is the ability to transparently evaluate different solutions on important tasks and compare them state-of-the-art conventional solutions. The Intel Neuromorphic Deep Noise Suppression Challenge (Intel N-DNS Challenge), inspired by Microsoft DNS Challenge, tackles a ubiquitous commercially relevant task: real-time audio denoising. Audio denoising likely reap benefits of due its low-bandwidth, temporal nature relevance...
The biologically inspired spiking neurons used in neuromorphic computing are nonlinear filters with dynamic state variables -- very different from the stateless neuron models deep learning. next version of Intel's research processor, Loihi 2, supports a wide range stateful fully programmable dynamics. Here we showcase advanced that can be to efficiently process streaming data simulation experiments on emulated 2 hardware. In one example, Resonate-and-Fire (RF) compute Short Time Fourier...