Hyperdimensional computing: Difference between revisions

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{{Short description|Computational approach}}

'''Hyperdimensional computing''' ('''HDC''') is an approach to computation, particularly [[artificial general intelligence|Artificial General Intelligence]]. HDC is motivated by the observation that the [[Cerebellum|cerebellum cortex]] operates on high-dimensional data representations.<ref>{{Citation |last1=Zou |first1=Zhuowen |title=Spiking Hyperdimensional Network: Neuromorphic Models Integrated with Memory-Inspired Framework |date=2021-10-01 |arxiv=2110.00214 |last2=Alimohamadi |first2=Haleh |last3=Imani |first3=Farhad |last4=Kim |first4=Yeseong |last5=Imani |first5=Mohsen}}</ref> In HDC, information is thereby represented as a hyperdimensional (long) [[Vector (mathematics and physics)|vector]] called a hypervector. A hyperdimensional vector (hypervector) could include thousands of numbers that represent a point in a space of thousands of dimensions,<ref name=":0">{{Cite web |last=Ananthaswamy |first=Anan |date=April 13, 2023 |title=A New Approach to Computation Reimagines Artificial Intelligence |url=https://www.quantamagazine.org/a-new-approach-to-computation-reimagines-artificial-intelligence-20230413/?mc_cid=ad9a93c472&mc_eid=506130a407 |website=Quanta Magazine}}</ref> as vector symbolic architectures is an older name for the same approach. This researchResearch extenuates into [[Artificial immune system|Artificial Immune Systems]] for creating [[Artificial general intelligence|Artificial General Intelligence]]. This is primarily founded as extenuating into [[Morphology (biology)|Morphological Engineering]] and [[Morphogenetic robotics|Morphogenetic Engineering]] inside [[Amorphous computing|Amorphous Computation]].

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* {{Citation | vauthors=((Stock, M.)), ((Van Criekinge, W.)), ((Boeckaerts, D.)), ((Taelman, S.)), ((Van Haeverbeke, M.)), ((Dewulf, P.)), ((De Baets, B.)) | veditors=((Dutt, V.)) | year=2024 | title=Hyperdimensional computing: a fast, robust, and interpretable paradigm for biological data | publisher=Public Library of Science (PLOS) | journal = PLOS Computational Biology| volume=20 | issue=9 | pages=e1012426 | doi=10.1371/journal.pcbi.1012426 | doi-access=free | pmid=39316621 | arxiv=2402.17572 }}

* {{Citation | vauthors=((Cumbo, F.)), ((Chicco, D.)) | year=2025 | title=Hyperdimensional computing in biomedical sciences: a brief review| volume = 11 | issue = e2885 | journal = PeerJ Computer Science | pages=e2885 | doi=10.7717/peerj-cs.2885 | doi-access=free | pmc=12192801 }}

* {{Cite journal |last=Kanerva |first=Pentti |date=2009-06-01 |title=Hyperdimensional Computing: An Introduction to Computing in Distributed Representation with High-Dimensional Random Vectors |url=https://doi.org/10.1007/s12559-009-9009-8 |journal=Cognitive Computation |language=en |volume=1 |issue=2 |pages=139–159 |doi=10.1007/s12559-009-9009-8 |s2cid=733980 |issn=1866-9964|url-access=subscription }}

* {{Cite journal |last1=Neubert |first1=Peer |last2=Schubert |first2=Stefan |last3=Protzel |first3=Peter |date=2019-12-01 |title=An Introduction to Hyperdimensional Computing for Robotics |url=https://doi.org/10.1007/s13218-019-00623-z |journal=KI – Künstliche Intelligenz |language=en |volume=33 |issue=4 |pages=319–330 |doi=10.1007/s13218-019-00623-z |s2cid=202642163 |issn=1610-1987|url-access=subscription }}

* {{Cite arXiv |last1=Neubert |first1=Peer |last2=Schubert |first2=Stefan |date=2021-01-19 |title=Hyperdimensional computing as a framework for systematic aggregation of image descriptors |class=cs.CV |eprint=2101.07720v1 |language=en}}