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Cyborg werden: Möglichkeitshorizonte in feministischen Theorien und Science Fictions
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Fink, Dagmar. - : transcript Verlag, 2022. : DEU, 2022. : Bielefeld, 2022
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In: Gender Studies ; 291 (2022)
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Natural cybernetics and mathematical history: the principle of least choice in history
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In: https://hal.archives-ouvertes.fr/hal-03315004 ; 2021 (2021)
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Imagining the thinking machine: Technological myths and the rise of artificial intelligence
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A Measure of All Minds: A Classification of the Artificial Intelligence Strengths and Virtues & the Creation of the THETIS Dimensions of Cybernetic Wellbeing
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In: Master of Applied Positive Psychology (MAPP) Capstone Projects (2020)
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Unique information via dependency constraints
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In: Journal of Physics A: Mathematical and Theoretical, vol 52, iss 1 (2019)
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| 8 |
Inscription and ‘Anscription’: Surface and System in Cybernetics, Deconstruction, and Don DeLillo ...
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Inscription and ‘Anscription’: Surface and System in Cybernetics, Deconstruction, and Don DeLillo
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In: Humanities ; Volume 8 ; Issue 1 (2019)
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Inscription and ‘Anscription’: Surface and System in Cybernetics, Deconstruction, and Don DeLillo
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Zetter, Nathaniel. - : MDPI AG, 2019. : https://www.mdpi.com/2076-0787/8/1/5, 2019. : Humanities, 2019
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| 11 |
Mathematics in Motion: Cartesian Mechanism and the Prospect of Intelligent Machines
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| 12 |
The mirror for (artificial) intelligence: Working in whose reflection?
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Moore, Phoebe V.. - : Berlin: Wissenschaftszentrum Berlin für Sozialforschung (WZB), 2019
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Creativity and the cybernetics of self: Drama, embodied creation and feedback processes
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In: Davis, S, (2018). Creativity and the cybernetics of self: Drama, embodied creation and feedback processes. Burgoyne, S (Ed.), Creativity in theatre: Theory and action in theatre/drama education, p. 169-187Cham, Switzerland: Springer http://dx.doi.org/10.1007/978-3-319-78928-6_11 (2018)
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Robert Smithson and Cybernetics: Language, Technology and Abstraction ... : Robert Smithson und Kybernetik: Sprache, Technologie und Abstraktion ...
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| 15 |
Just Talking -- Modelling Casual Conversation ; 19th Annual Meeting of the Special Interest Group on Discourse and Dialogue
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Silence and overlap in chat and chunk phases of multiparty casual conversation ; 9th International Conference on Speech Prosody 2018
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Polychronization as a mechanism for language acquisition in spiking neural networks
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Abstract:
The capacity of an intelligent agent to process complex patterns in signals such as language rests heavily on the nature of the internal representation of the relevant information. Furthermore, the acquisition of internal representation is an inherently closed-loop process in which an intelligent agent enters into a conversation with its environment. The result is the construction of a necessarily generative model of language, where semantics are grounded in an agent's sensory-motor experience by way of an associative memory. This work explores the mechanisms underlying language acquisition by investigating the function and architecture of the neocortex, with the ultimate goal of understanding how mental states might arise from spiking activity. In particular, we focus on the phenomenon of polychronization, which may be described as the self-organization of a spiking neural network as a result of the interplay between network structure, spiking activity, and synaptic plasticity. What emerges are groups of neurons exhibiting time-locked patterns of spiking, reproducible spatio-temporal stamps consisting of the precisely timed activations of their constituent neurons. At a high level, these polychronous neural groups may be thought of as a form of temporal encoding of information within the network. We propose that this representation is well suited to language acquisition, as it naturally resembles the spatio-temporal patterns found in the speech signal, as well as other real-world signals. Toward this end, we develop a supervised method for training a spiking neural network to learn and recognize patterns that are relevant to language, such as those corresponding to phonetic primitives. We show that even for a simplified model, the mechanism of polychronization is capable of processing and representing such patterns, providing a basis for language acquisition in spiking neural networks.
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Keyword:
Associative Memory; Cybernetics; Language Acquisition; Multi-modal Learning; Neural Computing; Pattern Recognition; Polychronization; Self-Organization; Spiking Neural Network; Spiking Simulation; Supervised Learning
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URL: http://hdl.handle.net/2142/101655
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| 18 |
Building Teacher Self-Efficacy Through Administrator Feedback
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In: Dissertations (2018)
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Why the United States Must Adopt Lethal Autonomous Weapon Systems
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The New Dogs of War: The Future of Weaponized Artificial Intelligence
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