| Literature DB >> 31865886 |
A Serb1, I Kobyzev2, J Wang1, T Prodromakis1.
Abstract
One of the main, long-term objectives of artificial intelligence is the creation of thinking machines. To that end, substantial effort has been placed into designing cognitive systems; i.e. systems that can manipulate semantic-level information. A substantial part of that effort is oriented towards designing the mathematical machinery underlying cognition in a way that is very efficiently implementable in hardware. In this work, we propose a 'semi-holographic' representation system that can be implemented in hardware using only multiplexing and addition operations, thus avoiding the need for expensive multiplication. The resulting architecture can be readily constructed by recycling standard microprocessor elements and is capable of performing two key mathematical operations frequently used in cognition, superposition and binding, within a budget of below 6 pJ for 64-bit operands. Our proposed 'cognitive processing unit' is intended as just one (albeit crucial) part of much larger cognitive systems where artificial neural networks of all kinds and associative memories work in concord to give rise to intelligence. This article is part of the theme issue 'Harmonizing energy-autonomous computing and intelligence'.Keywords: hardware; hyperdimensional; processor
Year: 2019 PMID: 31865886 PMCID: PMC6939245 DOI: 10.1098/rsta.2019.0162
Source DB: PubMed Journal: Philos Trans A Math Phys Eng Sci ISSN: 1364-503X Impact factor: 4.226