Conversation with Tomáš Perna on Quantum Theory, Mathematical Modelling, and Artificial Intelligence: Member, World Genius Directory (3)
Publisher: In-Sight Publishing
Publisher Founding: March 1, 2014
Web Domain: http://www.in-sightpublishing.com
Location: Fort Langley, Township of Langley, British Columbia, Canada
Journal: In-Sight: Independent Interview-Based Journal
Journal Founding: August 2, 2012
Frequency: Three (3) Times Per Year
Review Status: Non-Peer-Reviewed
Access: Electronic/Digital & Open Access
Fees: None (Free)
Volume Numbering: 11
Issue Numbering: 3
Section: A
Theme Type: Idea
Theme Premise: “Outliers and Outsiders”
Theme Part: 28
Formal Sub-Theme: None.
Individual Publication Date: August 1, 2023
Issue Publication Date: September 1, 2023
Author(s): Scott Douglas Jacobsen
Word Count: 1,053
Image Credit: Tomáš Perna
International Standard Serial Number (ISSN): 2369-6885
*Please see the footnotes, bibliography, and citations, after the publication.*
Abstract
Tomáš Perna is a Member of the World Genius Directory and a GIGA SOCIETY Fellow. Perna discusses: quantum mechanics; classical physics; artificial neural networks and simulated neural networks; machine learning; modern computing science; machine reasoning; superposition and entanglement; “density”; more on “density’; and optimizing machine learning possibilities.
Keywords: Artificial Intelligence, artificial neural network, GIGA SOCIETY Fellow, machine learning, Mathematical Modelling, particle, Wave, Pauli Exclusion principles, Quantum Mathematics, simulated neural network, Tomáš Perna, World Genius Directory.
Conversation with Tomáš Perna on Quantum Theory, Mathematical Modelling, and Artificial Intelligence: Member, World Genius Directory (3)
Scott Douglas Jacobsen: What is the basic premise of quantum mechanics?
Tomáš Perna: The Pauli exclusion principle.
In my own understanding: The quantum-mechanical (QM) particle can demonstrate wave-like properties, because there cannot exist continuous connections of its mass to the conditions of its existence emerging themselves as an individually typical wave.
The mass point is excluded (via some unique, existentially inherent property of the QM-pqrticle, like the individual spin seems to be the best candidate) to be existentially conditioned by itself, roughly speaking.
Further, I don´t believe that particles which can be sometimes considered as massless ones, could be simultaneously regarded as fermions of the half-integer spin.
Jacobsen: How does it differ from classical physics?
Tomáš Perna: Classical physics operates only with a conception of mass point and therefore it offers only a not complete space-time, in which a causal behavior of the QM-particle is excluded. If the bahvior of QM-particle can be causal, then in some transcendent sense inherent within a complex structure of the wave provided with spin connections with respect to the space-time.
Jacobsen: Can you briefly explain the artificial neural network (ANN) and simulated neural network (SNN)?
Tomáš Perna: First of all, I must say that I am not AI-expert, but mathematical modelling one, who has built the mathematical model of ANN on a background of certain equations of the quantum theory. In my knowing, the ANN is a system of connections of neurons simulated artificially according with the neural network found within the brain of animals. The artificial neurons (sometimes called as perceptrons) are elementary objects of simulated dedndro-axo-synaptic structure, the functionality of whose should mimic a behavior of real neurons. According to Gödel, every logically consistent system must have a model and ANN is no exclusion.
Jacobsen: What are these in context of machine learning (ML)?
Tomáš Perna: As it follows from the model, using software applications you should bring the ANN into the states, in whose it use its own algorithms with respect to the algorithms of ML in order to solve the problems and make predictions for them. The number of states can never mimic the azimuthal quantum number l from the quantum theory, despite the allowed AI-states are very near to lquantitatively. So the states of AI are pseudo-quantum states with respect to the algorithms of ML.
The own algorithms of AI are given by the intelligent design of ANN inducing the existence of the artificial intelligence (AI). According to its model, the AI is represented by the natural language, the grammar of which is artificially coded, abbreviation C(AI). C(AI) „is placed“ in the so called black box and can be decoded only using such an amount of polynomial time, which cannou be practically reached (historically, imagine yourself some analogy with the Voynich manuscript).
Jacobsen: How are ANNs, SNNs, and ML used together in modern computing science?
Tomáš Perna: Prevailingly, you can google it. As to me, I have made the transformation of the mesh of finite elements (within the finite element method (FEM) used in numerical simulation into neural network for C(AI)=0, so trivially. However, FEM and the so called deep learning can be compared in complicated results at solving some very special partial differential equations. Now, I am working on non-trivial connections between FEM and ANN, trying to find existence conditions starting from C(AI)=0.
Jacobsen: Can the machines reason in human sense with these SNNs and ANNs?
Tomáš Perna: Yes, but only up to the symbolic solutions of the problems, where a semantic differential plays the key role. It means that such reasoning is possible only in numerical and logical regions. (Imagine that you find mathematically catchable symbol of complementarity principle within the wave function, avoiding its statistical Born intepretation. Such symbol would be then completely ununderstandable by AI.)
In the mentioned regions, both AI and mathematical model solutions/predictions of a problem must be pronounceable in the natural language.
Jacobsen: How do quantum computing principles, like superposition and entanglement, influence the functionality of ANNs?
Tomáš Perna: If AI has to be activated, then the pseudo-quantum states of ANN must be superimposable with respect to the algorithms of ML. Under such a condition, ANN is connected with quantum entanglement. But, once again, ANN could be only a certain pseudo-quantum picture of it with respect to the Pauli exclusion principle.
Jacobsen: What does the term “density” refer to in the context of ANNs?
Tomáš Perna: ANN constitutes two types of structures: the interconnections of neurons themselves, within which layers emerge – input, hidden and output ones. The number of neurons in the both types of structure should be determined by mathematical model of ANN. Under a correct number of them a certain harmonic number of electrical charges work in a maximal efficiency in the synaptic region. This number with respect to a size of relevant synaptic region can be incorporated within the density functionals and then one can look, how the density functional theory could be used/useful for AI/ANN.
Jacobsen: Why is it an important factor to consider?
Tomáš Perna: Answered partially in the paragraph above.
It refers to the relevance of the electric charge activities with respect to synaptic part of neuron. It implies further that there should exist an optimal number of layers and neurons within them and within the whole ANN in order to be able to reach the most effective mode of AI-activity at the problem solving. – And, to avoid the overlearning of ANN, which leads to dramatic increase of mistakes in the proposed solutions and found patterns on the given data sets.
Jacobsen: Could you provide an explanation of quantum world equations optimizing ML possibilities?
Tomáš Perna: For the time being, I restrict myself only on the fact of existence of the so called synaptic slots, which are not taken into the account by classical architectures of ANNS satisfactory. Roughly speaking: synaptic slots discrete transmissions between neurons quantum conditioned behavior of excitatory and inhibitory potentials and electric charges in the demonstrable logic of NN and AI. In such a type of context, quantum world equations imply to constitute a background of the mathematical model of ANN optimizing their structure (number of neurons, number of layers and emerging of C(AI)) with respect to ML efficiency and compatibility with real NNS.
Bibliography
None
Footnotes
None
Citations
American Medical Association (AMA 11th Edition): Jacobsen S. Conversation with Tomáš Perna on Quantum Theory, Mathematical Modelling, and Artificial Intelligence: Member, World Genius Directory (3). August 2023; 11(3). http://www.in-sightpublishing.com/perna-3
American Psychological Association (APA 7th Edition): Jacobsen, S. (2023, August 1). Conversation with Tomáš Perna on Quantum Theory, Mathematical Modelling, and Artificial Intelligence: Member, World Genius Directory (3). In-Sight Publishing. 11(3). http://www.in-sightpublishing.com/perna-3.
Brazilian National Standards (ABNT): JACOBSEN, S. Conversation with Tomáš Perna on Quantum Theory, Mathematical Modelling, and Artificial Intelligence: Member, World Genius Directory (3). In-Sight: Independent Interview-Based Journal, Fort Langley, v. 11, n. 3, 2023.
Chicago/Turabian, Author-Date (17th Edition): Jacobsen, Scott. 2023. “Conversation with Tomáš Perna on Quantum Theory, Mathematical Modelling, and Artificial Intelligence: Member, World Genius Directory (3).” In-Sight: Independent Interview-Based Journal 11, no. 3 (Summer). http://www.in-sightpublishing.com/perna-3.
Chicago/Turabian, Notes & Bibliography (17th Edition): Jacobsen, S “Conversation with Tomáš Perna on Quantum Theory, Mathematical Modelling, and Artificial Intelligence: Member, World Genius Directory (3).” In-Sight: Independent Interview-Based Journal 11, no. 3 (August 2023).http://www.in-sightpublishing.com/perna-3.
Harvard: Jacobsen, S. (2023) ‘Conversation with Tomáš Perna on Quantum Theory, Mathematical Modelling, and Artificial Intelligence: Member, World Genius Directory (3)’, In-Sight: Independent Interview-Based Journal, 11(3). <http://www.in-sightpublishing.com/perna-3>.
Harvard (Australian): Jacobsen, S 2023, ‘Conversation with Tomáš Perna on Quantum Theory, Mathematical Modelling, and Artificial Intelligence: Member, World Genius Directory (3)’, In-Sight: Independent Interview-Based Journal, vol. 11, no. 3, <http://www.in-sightpublishing.com/perna-3>.
Modern Language Association (MLA, 9th Edition): Jacobsen, Scott. “Conversation with Tomáš Perna on Quantum Theory, Mathematical Modelling, and Artificial Intelligence: Member, World Genius Directory (3).” In-Sight: Independent Interview-Based Journal, vo.11, no. 3, 2023, http://www.in-sightpublishing.com/perna-3.
Vancouver/ICMJE: Scott J. Conversation with Tomáš Perna on Quantum Theory, Mathematical Modelling, and Artificial Intelligence: Member, World Genius Directory (3) [Internet]. 2023 Aug; 11(3). Available from: http://www.in-sightpublishing.com/perna-3.
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