Biologically-inspired training of spiking recurrent neural networks with neuromorphic hardware

Recurrent spiking neural networks (SNNs) are inspired by the working principles of biological nervous systems that offer unique temporal dynamics and event-based processing. Recently, the error backpropagation through time (BPTT) algorithm has been successfully employed to train SNNs offline, with comparable performance to artificial neural networks (ANNs) on complex tasks. However, BPTT has severe limitations for online learning scenarios of SNNs where the network is required to simultaneously process and learn from incoming data. Specifically, as BPTT separates the inference and update phases, it would require to store all neuronal states for calculating the weight updates backwards in time. To address these fundamental issues, alternative credit assignment schemes are required. Within this context, neuromorphic hardware (NMHW) implementations of SNNs can greatly benefit from in-memory computing (IMC) concepts that follow the brain-inspired collocation of memory and processing, further enhancing their energy efficiency. In this work, we utilize a biologically-inspired local and online training algorithm compatible with IMC, which approximates BPTT, e-prop, and present an approach to support both inference and training of a recurrent SNN using NMHW. To do so, we embed the SNN weights on an in-memory computing NMHW with phase-change memory (PCM) devices and integrate it into a hardware-in-the-loop training setup. We develop our approach with respect to limited precision and imperfections of the analog devices using a PCM-based simulation framework and a NMHW consisting of in-memory computing cores fabricated in 14nm CMOS technology with 256×256 PCM crossbar arrays. We demonstrate that our approach is robust even to 4-bit precision and achieves competitive performance to a floating-point 32-bit realization, while simultaneously equipping the SNN with online training capabilities and exploiting the acceleration benefits of NMHW

Biomimetic and bioinspired silica : recent developments and applications

In a previous review of biological and bioinspired silica formation (S. V. Patwardhan et al., Chem. Commun., 2005, 1113 [ref. 1]), we have identified and discussed the roles that organic molecules (additives) play in silica formation in vitro. Tremendous progress has been made in this field since and this review attempts to capture, with selected examples from the literature, the key advances in synthesising and controlling properties of silica-based materials using bioinspired approaches, i.e. conditions of near-neutral pH, all aqueous environments and room temperature. One important reason to investigate biosilicifying systems is to be able to develop novel materials and/or technologies suitable for a wide range of applications. Therefore, this review will also focus on applications arising from research on biological and bioinspired silica. A range of applications such as in the areas of sensors, coatings, hybrid materials, catalysis and biocatalysis and drug delivery have started appearing. Furthermore, scale-up of this technology suitable for large-scale manufacturing has proven the potential of biologically inspired synthesis

Quantum scale biomimicry of low dimensional growth: An unusual complex amorphous precursor route to TiO2 band confinement by shape adaptive biopolymer-like flexibility for energy applications

Crystallization via an amorphous pathway is often preferred by biologically driven processes enabling living species to better regulate activation energies to crystal formation that are intrinsically linked to shape and size of dynamically evolving morphologies. Templated ordering of 3-dimensional space around amorphous embedded non-equilibrium phases at heterogeneous polymer-metal interfaces signify important routes for the genesis of low-dimensional materials under stress-induced polymer confinement. We report the surface induced catalytic loss of P=O ligands to bond activated aromatization of C-C C=C and Ti=N resulting in confinement of porphyrin-TiO(2 )within polymer nanocages via particle attachment. Restricted growth nucleation of TiO2 to the quantum scale (˂= 2 nm) is synthetically assisted by nitrogen, phosphine and hydrocarbon polymer chemistry via self-assembly. Here, the amorphous arrest phase of TiO, is reminiscent of biogenic amorphous crystal growth patterns and polymer coordination has both a chemical and biomimetic significance arising from quantum scale confinement which is atomically challenging. The relative ease in adaptability of non-equilibrium phases renders host structures more shape compliant to congruent guests increasing the possibility of geometrical confinement. Here, we provide evidence for synthetic biomimicry akin to bio-polymerization mechanisms to steer disorder-to-order transitions via solvent plasticization-like behaviour. This challenges the rationale of quantum driven confinement processes by conventional processes. Further, we show the change in optoelectronic properties under quantum confinement is intrinsically related to size that affects their optical absorption band energy range in DSSC.This work was supported by the National Research Foundation of Korea (NRF) grant funded by Korea government (MEST) NRF-2012R1A1A2008196, NRF 2012R1A2A2A01047189, NRF 2017R1A2B4008801, 2016R1D1A1A02936936, (NRF-2018R1A4A1059976, NRF-2018R1A2A1A13078704) and NRF Basic Research Programme in Science and Engineering by the Ministry of Education (No. 2017R1D1A1B03036226) and by the INDO-KOREA JNC program of the National Research Foundation of Korea Grant No. 2017K1A3A1A68. We thank BMSI (A*STAR) and NSCC for support. SJF is funded by grant IAF25 PPH17/01/a0/009 funded by A* STAR/NRF/EDB. CSV is the founder of a spinoff biotech Sinopsee Therapeutics. The current work has no conflicting interests with the company. We would like to express our very great appreciation to Ms. Hyoseon Kim for her technical expertise during HRTEM imaging

Amorphous Computing

The goal of amorphous computing is to identify organizationalprinciples and create programming technologies for obtainingintentional, pre-specified behavior from the cooperation of myriadunreliable parts that are arranged in unknown, irregular, andtime-varying ways. The heightened relevance of amorphous computingtoday stems from the emergence of new technologies that could serve assubstrates for information processing systems of immense power atunprecedentedly low cost, if only we could master the challenge ofprogramming them. This document is a review of amorphous computing

The Software Continuum Concept: Towards a Biologically Inspired Model for Robust E-Business Software Automation

This paper introduces a new concept, the software continuum concept based on the observation that exists a general parallelism between the software continuum from bits to business/Internet ecosystems and the natural continuum from particles to ecosystems. The general parallelism suggests that homeomorphisms may be identified and therefore some concepts, processes, and/or mechanisms in one continuum can be investigated for application in the other continuum. We argue that the homeomorphisms give rise to a biologically-inspired architectural framework for addressing robust control, robust intelligence, and robust autonomy issues in e-business software and other business-IT integration challenges. As application, we examine the mapping of a major enterprise-level architecture framework to the biologically-inspired framework. Design considerations for robust intelligence and autonomy in large-scale software automation and some major systemic features for flexible business-IT integration are also discussed