Editing Neuromorphic computing (section)

{{Short description|Integrated circuit technology}}
{{Use American English|date = January 2019}}
{{Use mdy dates|date = January 2019}}

'''Neuromorphic computing''' is an approach to computing that is inspired by the structure and function of the human brain.<ref>{{Cite journal |last1=Ham |first1=Donhee |last2=Park |first2=Hongkun |last3=Hwang |first3=Sungwoo |last4=Kim |first4=Kinam |title=Neuromorphic electronics based on copying and pasting the brain |url=https://www.nature.com/articles/s41928-021-00646-1 |journal=Nature Electronics |year=2021 |language=en |volume=4 |issue=9 |pages=635–644 |doi=10.1038/s41928-021-00646-1 |s2cid=240580331 |issn=2520-1131|url-access=subscription }}</ref><ref>{{Cite journal |last1=van de Burgt |first1=Yoeri |last2=Lubberman |first2=Ewout |last3=Fuller |first3=Elliot J. |last4=Keene |first4=Scott T. |last5=Faria |first5=Grégorio C. |last6=Agarwal |first6=Sapan |last7=Marinella |first7=Matthew J. |last8=Alec Talin |first8=A. |last9=Salleo |first9=Alberto |date=April 2017 |title=A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing |url=https://www.nature.com/articles/nmat4856 |journal=Nature Materials |language=en |volume=16 |issue=4 |pages=414–418 |doi=10.1038/nmat4856 |pmid=28218920 |bibcode=2017NatMa..16..414V |issn=1476-4660}}</ref> A neuromorphic computer/chip is any device that uses physical [[artificial neuron]]s to do computations.<ref>{{cite journal|last1=Mead|first1=Carver|title=Neuromorphic electronic systems|journal=Proceedings of the IEEE|date=1990|volume=78|issue=10|pages=1629–1636|doi=10.1109/5.58356|s2cid=1169506 |url=https://authors.library.caltech.edu/53090/1/00058356.pdf}}</ref><ref name=":2" /> In recent times, the term ''neuromorphic'' has been used to describe [[Analogue electronics|analog]], [[Digital electronics|digital]], [[Mixed-signal integrated circuit|mixed-mode analog/digital VLSI]], and software systems that implement models of [[neural system]]s (for [[perception]], [[motor control]], or [[multisensory integration]]). Recent advances have even discovered ways to mimic the human nervous system through liquid solutions of chemical systems.<ref>{{Cite journal |last1=Tomassoli |first1=Laura |last2=Silva-Dias |first2=Leonardo |last3=Dolnik |first3=Milos |last4=Epstein |first4=Irving R. |last5=Germani |first5=Raimondo |last6=Gentili |first6=Pier Luigi |date=2024-02-08 |title=Neuromorphic Engineering in Wetware: Discriminating Acoustic Frequencies through Their Effects on Chemical Waves |url=https://pubs.acs.org/doi/10.1021/acs.jpcb.3c08429 |journal=The Journal of Physical Chemistry B |language=en |volume=128 |issue=5 |pages=1241–1255 |doi=10.1021/acs.jpcb.3c08429 |pmid=38285636 |issn=1520-6106|url-access=subscription }}</ref> An article published by AI researchers at [[Los Alamos National Laboratory]] states that, "neuromorphic computing, the [[next generation]] of [[Artificial intelligence|AI]], will be smaller, faster, and more efficient than the [[human brain]]."<ref>{{Cite web |last=Dickman |first=Kyle |title=Neuromorphic computing: the future of AI {{!}} LANL |url=https://www.lanl.gov/media/publications/1663/1269-neuromorphic-computing |access-date=2025-04-16 |website=Kyle Dickman |language=en}}</ref>

A key aspect of neuromorphic engineering is understanding how the [[Morphology (biology)|morphology]] of individual neurons, circuits, applications, and overall architectures creates desirable computations, affects how [[information]] is represented, influences robustness to damage, incorporates learning and development, adapts to local change (plasticity), and facilitates evolutionary change.

Neuromorphic engineering is an [[Interdisciplinarity|interdisciplinary]] subject that takes inspiration from [[biology]], [[physics]], [[mathematics]], [[computer science]], and [[electronic engineering]]<ref name=":2" /> to design [[Artificial neural network|artificial neural systems]], such as [[Machine vision|vision systems]], head-eye systems, auditory processors, and autonomous robots, whose physical architecture and design principles are based on those of biological nervous systems.<ref>{{Cite journal | doi = 10.1155/2012/705483| title = Qualitative Functional Decomposition Analysis of Evolved Neuromorphic Flight Controllers| journal = Applied Computational Intelligence and Soft Computing| volume = 2012| pages = 1–21| year = 2012| last1 = Boddhu | first1 = S. K. | last2 = Gallagher | first2 = J. C. | doi-access = free}}</ref> One of the first applications for neuromorphic engineering was proposed by [[Carver Mead]]<ref>{{Cite journal |last1=Mead |first1=Carver A. |last2=Mahowald |first2=M. A. |date=1988-01-01 |title=A silicon model of early visual processing %2888%2990024-X |journal=Neural Networks |language=en |volume=1 |issue=1 |pages=91–97 |doi=10.1016/0893-6080(88)90024-X |issn=0893-6080|url=https://resolver.caltech.edu/CaltechAUTHORS:20141223-110732666 }}</ref> in the late 1980s.