The alchemy of computation: designing with the unknown

Miller, Julian F.

doi:10.1007/s11047-019-09738-6

Cited by 20 publications

(8 citation statements)

References 45 publications

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“…The approach belongs to same family of computation outsourcing techniques as in materio computing [70,71,97,72,73] and reservoir computing [112,64,22,56,23,107].…”

Section: Pathways To Prototypingmentioning

confidence: 99%

Towards proteinoid computers

Adamatzky

2021

Preprint

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Proteinoids -thermal proteins -are produced by heating amino acids to their melting point and initiation of polymerisation to produce polymeric chains. Proteinoids swell in aqueous solution into hollow microspheres. The proteinoid microspheres produce endogenous burst of electrical potential spikes and change patterns of their electrical activity in response to illumination. The microspheres can interconnect by pores and tubes and form networks with a programmable growth. We speculate on how ensembles of the proteinoid microspheres can be developed into unconventional computing devices.

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“…The approach belongs to same family of computation outsourcing techniques as in materio computing [70,71,97,72,73] and reservoir computing [112,64,22,56,23,107].…”

Section: Pathways To Prototypingmentioning

confidence: 99%

Towards proteinoid computers

Adamatzky

2021

Preprint

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“…To date, the enabling technology for "neuromorphic" systems, including non-linear components such as memristors, is based on top-down lithographic technologies typical of highly integrated components of digital computers [26]. While this remains an almost obliged solution [27,28], radically different approaches, grouped under the umbrella of "unconventional computing" (UCOMP) have been proposed and are actively investigated [10][11][12][27][28][29][30][31]. UCOMP has the goal to go beyond solutions based on Turing paradigm [27] by using hardware and physical architectures relying on emergent complexity and collective phenomena originating from various classes of physical substrates [4,[9][10][11][12][32][33][34][35]].…”

Section: Introductionmentioning

confidence: 99%

A binary classifier based on a reconfigurable dense network of metallic nanojunctions

Mirigliano

Paroli

Martini

et al. 2021

Neuromorph. Comput. Eng.

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Major efforts to reproduce the brain performances in terms of classification and pattern recognition have been focused on the development of artificial neuromorphic systems based on topdown lithographic technologies typical of highly integrated components of digital computers. Unconventional computing has been proposed as an alternative exploiting the complexity and collective phenomena originating from various classes of physical substrates. Materials composed of a large number of non-linear nanoscale junctions are of particular interest: these systems, obtained by the self-assembling of nano-objects like nanoparticles and nanowires, results in non-linear conduction properties characterized by spatiotemporal correlation in their electrical activity. This appears particularly useful for classification of complex features: nonlinear projection into a high-dimensional space can make data linearly separable, providing classification solutions that are computationally very expensive with digital computers. Recently we reported that nanostructured Au films fabricated from the assembling of gold clusters by supersonic cluster beam deposition show a complex resistive switching behaviour. Their non-linear electric behaviour is remarkably stable and reproducible allowing the facile training of the devices on precise resistive states. Here we report about the fabrication and characterization of a device that allows the binary classification of Boolean functions by exploiting the properties of cluster-assembled Au films interconnecting a generic pattern of electrodes. This device, that constitutes a generalization of the perceptron, can receive inputs from different electrode configurations and generate a complete set of Boolean functions of n variables for classification tasks. We also show that the non-linear and non-local electrical conduction of clusterassembled gold films, working at room temperature, allows the classification of non-linearly separable functions without previous training of the device.

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“…The technique is based on selecting a pair of input sites, applying all possible combinations of inputs, where logical values are represented by electrical characteristics of input signals, to the sites and recording outputs, represented by electrical responses of the substrate, on a set of the selected output sites. The approach belong to the family of reservoir computing [48,28,11,27,12] and in materio computing [32,33,47,34,35] techniques of analysing computational properties of physical and biological substrates.…”

Section: Introductionmentioning

confidence: 99%

Mining logical circuits in fungi

Roberts¹,

Adamatzky²

2021

Preprint

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Living substrates are capable for nontrivial mappings of electrical signals due to the substrate nonlinear electrical characteristics. This property can be used to realise Boolean functions. Input logical values are represented by amplitude or frequency of electrical stimuli. Output logical values are decoded from electrical responses of living substrates. We demonstrate how logical circuits can be implemented in mycelium bound composites. The mycelium bound composites (fungal materials) are getting growing recognition as building, packaging, decoration and clothing materials. Presently the fungal materials are passive. To make the fungal materials adaptive, i.e. sensing and computing, we should embed logical circuits into them. We demonstrate experimental laboratory prototypes of many-input Boolean functions implemented in fungal materials from oyster fungi P. ostreatus. We characterise complexity of the functions discovered via complexity of the space-time configurations of one-dimensional cellular automata governed by the functions. We show that the mycelium bound composites can implement representative functions from all classes of cellular automata complexity including the computationally universal. The results presented will make an impact in the field of unconventional computing, experimental demonstration of purposeful computing with fungi, and in the field of intelligent materials, as the prototypes of computing mycelium bound composites.

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The alchemy of computation: designing with the unknown

Cited by 20 publications

References 45 publications

Towards proteinoid computers

Towards proteinoid computers

A binary classifier based on a reconfigurable dense network of metallic nanojunctions

Mining logical circuits in fungi

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