Hyperdimensional computing: Difference between revisions

Revision as of 22:31, 19 February 2024

Revision as of 05:52, 28 February 2024

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{{Short description|Computational approach}}

'''Hyperdimensional computing''' ('''HDC''') is an approach to computation, particularly [[artificial 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 |url=http://arxiv.org/abs/2110.00214 |access-date=2024-02-16 |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 hypervector an array of numbers. 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> Vector Symbolic Architectures is an older name for the same broad approach.<ref name=":0" />

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