Presentation + Paper
13 November 2024 A demonstration of vector symbolic architecture as an effective integrated technology for AI at the network edge
Graham Bent, Cai Davies, Marc Roig Vilamala, Yuhua Li, Alun Preece, Gaetano Di Caterina, Alex Vicente Sola, Paul Kirkland, Gavin Pearson, Benomy Tutcher
Author Affiliations +
Abstract
Vector Symbolic Architecture (VSA), a.k.a. Hyperdimensional Computing has transformative potential for advancing cognitive processing capabilities at the network edge. This paper presents a technology integration experiment, demonstrating how the VSA paradigm offers robust solutions for generation-after-next AI deployment at the network edge. Specifically, we show how VSA effectively models and integrates the cognitive processes required to perform intelligence, surveillance, and reconnaissance (ISR). The experiment integrates functions across the observe, orientate, decide and act (OODA) loop, including the processing of sensed data via both a neuromorphic event-based camera and a standard CMOS frame-rate camera; declarative knowledge-based reasoning in a semantic vector space; action planning using VSA cognitive maps; access to procedural knowledge via large language models (LLMs); and efficient communication between agents via highly-compact binary vector representations. In contrast to previous ‘point solutions’ showing the effectiveness of VSA for individual OODA tasks, this work takes a ‘whole system’ approach, demonstrating the power of VSA as a uniform integration technology.
Conference Presentation
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Graham Bent, Cai Davies, Marc Roig Vilamala, Yuhua Li, Alun Preece, Gaetano Di Caterina, Alex Vicente Sola, Paul Kirkland, Gavin Pearson, and Benomy Tutcher "A demonstration of vector symbolic architecture as an effective integrated technology for AI at the network edge", Proc. SPIE 13206, Artificial Intelligence for Security and Defence Applications II, 1320613 (13 November 2024); https://doi.org/10.1117/12.3030952
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KEYWORDS
Cameras

Artificial intelligence

Object detection

Semantics

Binary data

Decision making

Device simulation

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