Artificial Intelligence

1709 Submissions

[21] viXra:1709.0404 [pdf] submitted on 2017-09-26 13:26:47

A Suggestion on CLIPS/JIProlog/JNNS/ImageJ/Java Agents/JikesRVM Based Analysis of Cryo-EM/TEM/SEM Images Using HDF5 Image Format – Some Interesting & Feasible Implementations of Expert Systems to Understand Nano- Bio Material Systems and EM

Authors: D.N.T.Kumar
Comments: 7 Pages. Prolog/NN/Expert Systems/JikesRVM/Informatics/EM/Cryo-EM/TEM/SEM/Material Science/Java Agents/Nanotechnology.

In this short communication the importance of expert systems based imaging framework to probe Cryo-EM images is presented from a practical implementation point of view. Neural Networks or NN are an excellent tool to probe various domains of science and technology. Cryo-EM Technique holds bright future based on the application of NN.Prolog-NN based algorithms could form a powerful informatics and computational framework for researching the challenges of nano-bio Applications. Further,it is useful and important to study the behavior of NN in domains where knowledge does not exist, i.e to use the models to make bold predictions which form the basis for Cryo-EM Image Processing tasks and the discovery of new nano-bio phenomena.Indeed, the performance of NN is most useful to researchers in domains where the modeling and predicting “uncertainty” is known to be the greatest factor. All the methods presented here are also applicable to TEM/SEM/other EM Image Processing tasks as well.
Category: Artificial Intelligence

[20] viXra:1709.0403 [pdf] submitted on 2017-09-26 13:33:02

Kernel Principal Component Analysis as Mathematical Tool In Processing Cryo- EM Images – A Suggestion Using Kernel Based Data Processing Techniques in a Java Virtual Machine(JVM) Environment.

Authors: D.N.T.Kumar
Comments: 7 Pages. A Suggestion Using Kernel Based Data Processing Techniques in a Java Virtual Machine(JVM) Environment.

In this short communication,it was proposed to highlight some novel methodologies to probe,process and compute Cryo-EM Images in a unique way by using an open source Kernel-PCA and by interfacing the KERNEL-PCA via Java Matlab Interface(JMI) – JikesRVM system or any other Java Virtual Machine(JVM).The main reason to design and develop this kind of computing approach is to utilize the features of Java based technologies for futuristic applications in the promising and demanding domains of CRYO-EM Imaging in the nano-bio domains.This is one of the pioneering research topics in this domain with a lot of promise.Image de-noising and novelty detection paves the way and holds the key for better Cryo-EM image processing.
Category: Artificial Intelligence

[19] viXra:1709.0394 [pdf] submitted on 2017-09-26 11:50:52

How Does the ai Understand What's Going on

Authors: Dimiter Dobrev
Comments: 22 Pages.

Most researchers regard AI as a static function without memory. This is one of the few articles where AI is seen as a device with memory. When we have memory, we can ask ourselves: "Where am I?", and "What is going on?" When we have no memory, we have to assume that we are always in the same place and that the world is always in the same state.
Category: Artificial Intelligence

[18] viXra:1709.0323 [pdf] submitted on 2017-09-21 05:35:00

Recursive Future Average Of A Time Series Data Based On Cosine Similarity-RF

Authors: Ramesh Chandra Bagadi
Comments: 2 Pages.

In this research Technical Note the author have presented a Recursive Future Average Of A Time Series Data Based on Cosine Similarity.
Category: Artificial Intelligence

[17] viXra:1709.0322 [pdf] submitted on 2017-09-21 05:49:31

Recursive Future Average Of A Time Series Data Based On Cosine Similarity-RF {Version 2}

Authors: Ramesh Chandra Bagadi
Comments: 2 Pages.

In this research Technical Note the author have presented a Recursive Future Average Of A Time Series Data Based on Cosine Similarity.
Category: Artificial Intelligence

[16] viXra:1709.0313 [pdf] submitted on 2017-09-22 00:01:00

The Recursive Future Equation Based On The Ananda-Damayanthi Normalized Similarity Measure. {File Closing Version 2}. ISSN 1751-3030

Authors: Ramesh Chandra Bagadi
Comments: 3 Pages.

In this research Technical Note the author have presented a Recursive Future Average Of A Time Series Data Based on Cosine Similarity.
Category: Artificial Intelligence

[15] viXra:1709.0217 [pdf] submitted on 2017-09-14 08:11:16

Quantum Thinking Machines

Authors: George Rajna
Comments: 24 Pages.

Quantum computers can be made to utilize effects such as quantum coherence and entanglement to accelerate machine learning. [16] Neural networks learn how to carry out certain tasks by analyzing large amounts of data displayed to them. [15] Who is the better experimentalist, a human or a robot? When it comes to exploring synthetic and crystallization conditions for inorganic gigantic molecules, actively learning machines are clearly ahead, as demonstrated by British Scientists in an experiment with polyoxometalates published in the journal Angewandte Chemie. [14] Machine learning algorithms are designed to improve as they encounter more data, making them a versatile technology for understanding large sets of photos such as those accessible from Google Images. Elizabeth Holm, professor of materials science and engineering at Carnegie Mellon University, is leveraging this technology to better understand the enormous number of research images accumulated in the field of materials science. [13] With the help of artificial intelligence, chemists from the University of Basel in Switzerland have computed the characteristics of about two million crystals made up of four chemical elements. The researchers were able to identify 90 previously unknown thermodynamically stable crystals that can be regarded as new materials. [12] The artificial intelligence system's ability to set itself up quickly every morning and compensate for any overnight fluctuations would make this fragile technology much more useful for field measurements, said co-lead researcher Dr Michael Hush from UNSW ADFA. [11] Quantum physicist Mario Krenn and his colleagues in the group of Anton Zeilinger from the Faculty of Physics at the University of Vienna and the Austrian Academy of Sciences have developed an algorithm which designs new useful quantum experiments. As the computer does not rely on human intuition, it finds novel unfamiliar solutions. [10] Researchers at the University of Chicago's Institute for Molecular Engineering and the University of Konstanz have demonstrated the ability to generate a quantum logic operation, or rotation of the qubit, that-surprisingly—is intrinsically resilient to noise as well as to variations in the strength or duration of the control. Their achievement is based on a geometric concept known as the Berry phase and is implemented through entirely optical means within a single electronic spin in diamond. [9]
Category: Artificial Intelligence

[14] viXra:1709.0211 [pdf] submitted on 2017-09-14 06:46:27

Analyzing Huge Volumes of Data

Authors: George Rajna
Comments: 23 Pages.

Neural networks learn how to carry out certain tasks by analyzing large amounts of data displayed to them. [15] Who is the better experimentalist, a human or a robot? When it comes to exploring synthetic and crystallization conditions for inorganic gigantic molecules, actively learning machines are clearly ahead, as demonstrated by British Scientists in an experiment with polyoxometalates published in the journal Angewandte Chemie. [14] Machine learning algorithms are designed to improve as they encounter more data, making them a versatile technology for understanding large sets of photos such as those accessible from Google Images. Elizabeth Holm, professor of materials science and engineering at Carnegie Mellon University, is leveraging this technology to better understand the enormous number of research images accumulated in the field of materials science. [13] With the help of artificial intelligence, chemists from the University of Basel in Switzerland have computed the characteristics of about two million crystals made up of four chemical elements. The researchers were able to identify 90 previously unknown thermodynamically stable crystals that can be regarded as new materials. [12] The artificial intelligence system's ability to set itself up quickly every morning and compensate for any overnight fluctuations would make this fragile technology much more useful for field measurements, said co-lead researcher Dr Michael Hush from UNSW ADFA. [11] Quantum physicist Mario Krenn and his colleagues in the group of Anton Zeilinger from the Faculty of Physics at the University of Vienna and the Austrian Academy of Sciences have developed an algorithm which designs new useful quantum experiments. As the computer does not rely on human intuition, it finds novel unfamiliar solutions. [10] Researchers at the University of Chicago's Institute for Molecular Engineering and the University of Konstanz have demonstrated the ability to generate a quantum logic operation, or rotation of the qubit, that - surprisingly—is intrinsically resilient to noise as well as to variations in the strength or duration of the control. Their achievement is based on a geometric concept known as the Berry phase and is implemented through entirely optical means within a single electronic spin in diamond. [9]
Category: Artificial Intelligence

[13] viXra:1709.0161 [pdf] submitted on 2017-09-13 10:30:45

AI is Reinforcing Stereotypes

Authors: George Rajna
Comments: 46 Pages.

Following the old saying that "knowledge is power", companies are seeking to infer increasingly intimate properties about their customers as a way to gain an edge over their competitors. [27] Researchers from Human Longevity, Inc. (HLI) have published a study in which individual faces and other physical traits were predicted using whole genome sequencing data and machine learning. [26] Artificial intelligence can improve health care by analyzing data from apps, smartphones and wearable technology. [25] Now, researchers at Google's DeepMind have developed a simple algorithm to handle such reasoning—and it has already beaten humans at a complex image comprehension test. [24] A marimba-playing robot with four arms and eight sticks is writing and playing its own compositions in a lab at the Georgia Institute of Technology. The pieces are generated using artificial intelligence and deep learning. [23] Now, a team of researchers at MIT and elsewhere has developed a new approach to such computations, using light instead of electricity, which they say could vastly improve the speed and efficiency of certain deep learning computations. [22] Physicists have found that the structure of certain types of quantum learning algorithms is very similar to their classical counterparts—a finding that will help scientists further develop the quantum versions. [21] We should remain optimistic that quantum computing and AI will continue to improve our lives, but we also should continue to hold companies, organizations, and governments accountable for how our private data is used, as well as the technology's impact on the environment. [20] It's man vs machine this week as Google's artificial intelligence programme AlphaGo faces the world's top-ranked Go player in a contest expected to end in another victory for rapid advances in AI. [19] Google's computer programs are gaining a better understanding of the world, and now it wants them to handle more of the decision-making for the billions of people who use its services. [18] Microsoft on Wednesday unveiled new tools intended to democratize artificial intelligence by enabling machine smarts to be built into software from smartphone games to factory floors. [17]
Category: Artificial Intelligence

[12] viXra:1709.0159 [pdf] submitted on 2017-09-13 06:47:26

Mergeable Nervous Robots

Authors: George Rajna
Comments: 49 Pages.

Researchers at the Université libre de Bruxelles have developed self-reconfiguring modular robots that can merge, split and even self-heal while retaining full sensorimotor control. [29] A challenging brain technique called whole-cell patch clamp electrophysiology or whole-cell recording (WCR) is a procedure so delicate and complex that only a handful of humans in the whole world can do it. [28] ComText allows robots to understand contextual commands such as, " Pick up the box I put down. " [27] McMaster and Ryerson universities today announced the Smart Robots for Health Communication project, a joint research initiative designed to introduce social robotics and artificial intelligence into clinical health care. [26] Artificial intelligence can improve health care by analyzing data from apps, smartphones and wearable technology. [25] Now, researchers at Google's DeepMind have developed a simple algorithm to handle such reasoning—and it has already beaten humans at a complex image comprehension test. [24] A marimba-playing robot with four arms and eight sticks is writing and playing its own compositions in a lab at the Georgia Institute of Technology. The pieces are generated using artificial intelligence and deep learning. [23] Now, a team of researchers at MIT and elsewhere has developed a new approach to such computations, using light instead of electricity, which they say could vastly improve the speed and efficiency of certain deep learning computations. [22] Physicists have found that the structure of certain types of quantum learning algorithms is very similar to their classical counterparts—a finding that will help scientists further develop the quantum versions. [21] We should remain optimistic that quantum computing and AI will continue to improve our lives, but we also should continue to hold companies, organizations, and governments accountable for how our private data is used, as well as the technology's impact on the environment. [20] It's man vs machine this week as Google's artificial intelligence programme AlphaGo faces the world's top-ranked Go player in a contest expected to end in another victory for rapid advances in AI. [19]
Category: Artificial Intelligence

[11] viXra:1709.0142 [pdf] submitted on 2017-09-11 20:53:40

Brain Emotional Learning Based Intelligent Controller for Velocity Control of an Electro Hydraulic Servo System

Authors: Zohreh Alzahra Sanai Dashti, Milad Gholami, Masoud Hajimani
Comments: 7 Pages. IOSR Journal of Electrical and Electronics Engineering (IOSR - JEEE) e - ISSN: 2278 - 1676,p - ISSN: 2320 - 3331, Volume 12, Issue 4 Ver. I I (Jul. – Aug. 2017), PP 29 - 35

In this paper, a biologically motivated controller based on mammalian limbic system called Brain Emotional Learning Based Intelligent Controller (BELBIC) is used for velocity control of an Electro Hydraulic Servo System (EHSS) in presence of flow nonlinearities, internal friction and noise. It is shown that this technique can be successfully used to stabilize any chosen operating point of the system with noise and without noise. All derived results are validated by computer simulation of a nonlinear mathematical model of the system. The controllers which introduced have big range for control the system. We compare BELBIC controller results with feedbacks linearization, backstepping and PID controller.
Category: Artificial Intelligence

[10] viXra:1709.0141 [pdf] submitted on 2017-09-11 20:56:32

Design & Implementation of Fuzzy Parallel Distributed Compensation Controller for Magnetic Levitation System

Authors: Milad Gholami, Zohreh Alzahra Sanai Dashti, Masoud Hajimani
Comments: 9 Pages. IOSR Journal of Electrical and Electronics Engineering (IOSR - JEEE) e - ISSN : 2278 - 1676,p - ISSN: 2320 - 3331, Volume 12, Issue 4 Ver. I I (Jul. – Aug. 2017), PP 20 - 28

This study applies technique parallel distributed compensation (PDC) for position control of a Magnetic levitation system. PDC method is based on nonlinear Takagi-Sugeno (T-S) fuzzy model. It is shown that this technique can be successfully used to stabilize any chosen operating point of the system. All derived results are validated by experimental and computer simulation of a nonlinear mathematical model of the system. The controllers which introduced have big range for control the system.
Category: Artificial Intelligence

[9] viXra:1709.0125 [pdf] submitted on 2017-09-11 07:51:38

Machine Learning Monitoring Air Quality

Authors: George Rajna
Comments: 23 Pages.

UCLA researchers have developed a cost-effective mobile device to measure air quality. It works by detecting pollutants and determining their concentration and size using a mobile microscope connected to a smartphone and a machine-learning algorithm that automatically analyzes the images of the pollutants. [15] Who is the better experimentalist, a human or a robot? When it comes to exploring synthetic and crystallization conditions for inorganic gigantic molecules, actively learning machines are clearly ahead, as demonstrated by British Scientists in an experiment with polyoxometalates published in the journal Angewandte Chemie. [14] Machine learning algorithms are designed to improve as they encounter more data, making them a versatile technology for understanding large sets of photos such as those accessible from Google Images. Elizabeth Holm, professor of materials science and engineering at Carnegie Mellon University, is leveraging this technology to better understand the enormous number of research images accumulated in the field of materials science. [13] With the help of artificial intelligence, chemists from the University of Basel in Switzerland have computed the characteristics of about two million crystals made up of four chemical elements. The researchers were able to identify 90 previously unknown thermodynamically stable crystals that can be regarded as new materials. [12] The artificial intelligence system's ability to set itself up quickly every morning and compensate for any overnight fluctuations would make this fragile technology much more useful for field measurements, said co-lead researcher Dr Michael Hush from UNSW ADFA. [11]
Category: Artificial Intelligence

[8] viXra:1709.0108 [pdf] replaced on 2017-09-10 08:24:10

A New Semantic Theory of Nature Language

Authors: Kun Xing
Comments: 70 Pages.

Formal Semantics and Distributional Semantics are two important semantic frameworks in Natural Language Processing (NLP). Cognitive Semantics belongs to the movement of Cognitive Linguistics, which is based on contemporary cognitive science. Each framework could deal with some meaning phenomena, but none of them fulfills all requirements proposed by applications. A unified semantic theory characterizing all important language phenomena has both theoretical and practical significance; however, although many attempts have been made in recent years, no existing theory has achieved this goal yet. This article introduces a new semantic theory that has the potential to characterize most of the important meaning phenomena of natural language and to fulfill most of the necessary requirements for philosophical analysis and for NLP applications. The theory is based on a unified representation of information, and constructs a kind of mathematical model called cognitive model to interpret natural language expressions in a compositional manner. It accepts the empirical assumption of Cognitive Semantics, and overcomes most shortcomings of Formal Semantics and of Distributional Semantics. The theory, however, is not a simple combination of existing theories, but an extensive generalization of classic logic and Formal Semantics. It inherits nearly all advantages of Formal Semantics, and also provides descriptive contents for objects and events as fine-gram as possible, descriptive contents which represent the results of human cognition.
Category: Artificial Intelligence

[7] viXra:1709.0096 [pdf] submitted on 2017-09-08 13:34:21

Robots Understand Brain Function

Authors: George Rajna
Comments: 48 Pages.

A challenging brain technique called whole-cell patch clamp electrophysiology or whole-cell recording (WCR) is a procedure so delicate and complex that only a handful of humans in the whole world can do it. [28] ComText allows robots to understand contextual commands such as, " Pick up the box I put down. " [27] McMaster and Ryerson universities today announced the Smart Robots for Health Communication project, a joint research initiative designed to introduce social robotics and artificial intelligence into clinical health care. [26] Artificial intelligence can improve health care by analyzing data from apps, smartphones and wearable technology. [25] Now, researchers at Google's DeepMind have developed a simple algorithm to handle such reasoning—and it has already beaten humans at a complex image comprehension test. [24] A marimba-playing robot with four arms and eight sticks is writing and playing its own compositions in a lab at the Georgia Institute of Technology. The pieces are generated using artificial intelligence and deep learning. [23] Now, a team of researchers at MIT and elsewhere has developed a new approach to such computations, using light instead of electricity, which they say could vastly improve the speed and efficiency of certain deep learning computations. [22] Physicists have found that the structure of certain types of quantum learning algorithms is very similar to their classical counterparts—a finding that will help scientists further develop the quantum versions. [21] We should remain optimistic that quantum computing and AI will continue to improve our lives, but we also should continue to hold companies, organizations, and governments accountable for how our private data is used, as well as the technology's impact on the environment. [20] It's man vs machine this week as Google's artificial intelligence programme AlphaGo faces the world's top-ranked Go player in a contest expected to end in another victory for rapid advances in AI. [19] Google's computer programs are gaining a better understanding of the world, and now it wants them to handle more of the decision-making for the billions of people who use its services. [18]
Category: Artificial Intelligence

[6] viXra:1709.0068 [pdf] submitted on 2017-09-06 07:16:28

Identification of Individuals

Authors: George Rajna
Comments: 44 Pages.

Researchers from Human Longevity, Inc. (HLI) have published a study in which individual faces and other physical traits were predicted using whole genome sequencing data and machine learning. [26] Artificial intelligence can improve health care by analyzing data from apps, smartphones and wearable technology. [25] Now, researchers at Google's DeepMind have developed a simple algorithm to handle such reasoning—and it has already beaten humans at a complex image comprehension test. [24] A marimba-playing robot with four arms and eight sticks is writing and playing its own compositions in a lab at the Georgia Institute of Technology. The pieces are generated using artificial intelligence and deep learning. [23] Now, a team of researchers at MIT and elsewhere has developed a new approach to such computations, using light instead of electricity, which they say could vastly improve the speed and efficiency of certain deep learning computations. [22] Physicists have found that the structure of certain types of quantum learning algorithms is very similar to their classical counterparts—a finding that will help scientists further develop the quantum versions. [21] We should remain optimistic that quantum computing and AI will continue to improve our lives, but we also should continue to hold companies, organizations, and governments accountable for how our private data is used, as well as the technology's impact on the environment. [20] It's man vs machine this week as Google's artificial intelligence programme AlphaGo faces the world's top-ranked Go player in a contest expected to end in another victory for rapid advances in AI. [19] Google's computer programs are gaining a better understanding of the world, and now it wants them to handle more of the decision-making for the billions of people who use its services. [18] Microsoft on Wednesday unveiled new tools intended to democratize artificial intelligence by enabling machine smarts to be built into software from smartphone games to factory floors. [17] The closer we can get a machine translation to be on par with expert human translation, the happier lots of people struggling with translations will be. [16]
Category: Artificial Intelligence

[5] viXra:1709.0067 [pdf] submitted on 2017-09-06 07:32:22

Analyzing the Monotonicity of Belief Interval Based Uncertainty Measures in Belief Function Theory

Authors: Xinyang Deng, Shiyu Wang, Yong Deng
Comments: 21 Pages.

Measuring the uncertainty of pieces of evidence is an open issue in belief function theory. A rational uncertainty measure for belief functions should meet some desirable properties, where monotonicity is an very important property. Recently, measuring the total uncertainty of a belief function based on its associated belief intervals becomes a new research idea and have attracted increasing interest. Several belief interval based uncertainty measures have been proposed for belief functions. In this paper, we summarize the properties of these uncertainty measures and especially investigate whether the monotonicity is satisfied by the measures. This study provide a comprehensive comparison to these belief interval based uncertainty measures and is very useful for choosing the appropriate uncertainty measure in the practical applications.
Category: Artificial Intelligence

[4] viXra:1709.0048 [pdf] submitted on 2017-09-05 04:26:06

On the Dual Nature of Logical Variables and Clause-Sets

Authors: Elnaserledinellah Mahmood Abdelwahab
Comments: © 2016 Journal Academica Foundation. All rights reserved. With perpetual, non-exclusive license for viXra.org - Originally received 08-04-2016 - accepted 09-12-2016 - published 09-15-2016 J.Acad.(N.Y.)6,3:202-239 (38 pages) - ISSN 2161-3338

This paper describes the conceptual approach behind the proposed solution of the 3SAT problem recently published in [Abdelwahab 2016]. It is intended for interested readers providing a step-by-step, mostly informal explanation of the new paradigm proposed there completing the picture from an epistemological point of view with the concept of duality on center-stage. After a brief introduction discussing the importance of duality in both, physics and mathematics as well as past efforts to solve the P vs. NP problem, a theorem is proven showing that true randomness of input-variables is a property of algorithms which has to be given up when discrete, finite domains are considered. This insight has an already known side effect on computation paradigms, namely: The ability to de-randomize probabilistic algorithms. The theorem uses a canonical type of de-randomization which reveals dual properties of logical variables and Clause-Sets. A distinction is made between what we call the syntactical Container Expression (CE) and the semantic Pattern Expression (PE). A single sided approach is presumed to be insufficient to solve anyone of the dual problems of efficiently finding an assignment validating a 3CNF Clause-Set and finding a 3CNF-representation for a given semantic pattern. The deeply rooted reason, hereafter referred to as The Inefficiency Principle, is conjectured to be the inherent difficulty of translating one expression into the other based on a single-sided perspective. It expresses our inability to perceive and efficiently calculate complementary properties of a logical formula applying one view only. It is proposed as an alternative to the commonly accepted P≠NP conjecture. On the other hand, the idea of algorithmically using information deduced from PE to guide the instantiation of variables in a resolution procedure applied on a CE is as per [Abdelwahab 2016] able to provide an efficient solution to the 3SAT-problem. Finally, linking de-randomization to this positive solution has various well-established and important consequences for probabilistic complexity classes which are shown to hold.
Category: Artificial Intelligence

[3] viXra:1709.0019 [pdf] submitted on 2017-09-02 07:01:40

Understanding Robots

Authors: George Rajna
Comments: 46 Pages.

ComText allows robots to understand contextual commands such as, " Pick up the box I put down. " [27] McMaster and Ryerson universities today announced the Smart Robots for Health Communication project, a joint research initiative designed to introduce social robotics and artificial intelligence into clinical health care. [26] Artificial intelligence can improve health care by analyzing data from apps, smartphones and wearable technology. [25] Now, researchers at Google's DeepMind have developed a simple algorithm to handle such reasoning—and it has already beaten humans at a complex image comprehension test. [24] A marimba-playing robot with four arms and eight sticks is writing and playing its own compositions in a lab at the Georgia Institute of Technology. The pieces are generated using artificial intelligence and deep learning. [23] Now, a team of researchers at MIT and elsewhere has developed a new approach to such computations, using light instead of electricity, which they say could vastly improve the speed and efficiency of certain deep learning computations. [22] Physicists have found that the structure of certain types of quantum learning algorithms is very similar to their classical counterparts—a finding that will help scientists further develop the quantum versions. [21] We should remain optimistic that quantum computing and AI will continue to improve our lives, but we also should continue to hold companies, organizations, and governments accountable for how our private data is used, as well as the technology's impact on the environment. [20] It's man vs machine this week as Google's artificial intelligence programme AlphaGo faces the world's top-ranked Go player in a contest expected to end in another victory for rapid advances in AI. [19] Google's computer programs are gaining a better understanding of the world, and now it wants them to handle more of the decision-making for the billions of people who use its services. [18] Microsoft on Wednesday unveiled new tools intended to democratize artificial intelligence by enabling machine smarts to be built into software from smartphone games to factory floors. [17]
Category: Artificial Intelligence

[2] viXra:1709.0007 [pdf] submitted on 2017-09-01 10:31:26

Computing, Cognition and Information Compression

Authors: J Gerard Wolff
Comments: 21 Pages.

This article develops the idea that the storage and processing of information in computers and in brains may often be understood as information compression. The article first reviews what is meant by information and, in particular, what is meant by redundancy, a concept which is fundamental in all methods for information compression. Principles of information compression are described. The major part of the article describes how these principles may be seen in a range of observations and ideas in computing and cognition: the phenomena of adaptation and inhibition in nervous systems; 'neural' computing; the creation and recognition of 'objects' and 'classes'in perception and cognition; stereoscopic vision and random-dot stereograms; the organisation of natural languages; the organisation of grammars; the organisation of functional, structured, logic and object-oriented computer programs; the application and de-referencing of identifiers in computing; retrieval of information from databases; access and retrieval of information from computer memory; logical deduction and resolution theorem proving; inductive reasoning and probabilistic inference; parsing; normalisation of databases.
Category: Artificial Intelligence

[1] viXra:1709.0004 [pdf] submitted on 2017-09-01 06:49:15

Simple Chess Puzzle

Authors: George Rajna
Comments: 26 Pages.

Researchers at the University of St Andrews have thrown down the gauntlet to computer programmers to find a solution to a "simple" chess puzzle which could, in fact, take thousands of years to solve and net a $1m prize. [11] It appears that we are approaching a unique time in the history of man and science where empirical measures and deductive reasoning can actually inform us spiritually. Integrated Information Theory (IIT)-put forth by neuroscientists Giulio Tononi and Christof Koch-is a new framework that describes a way to experimentally measure the extent to which a system is conscious. [10] There is also connection between statistical physics and evolutionary biology, since the arrow of time is working in the biological evolution also. From the standpoint of physics, there is one essential difference between living things and inanimate clumps of carbon atoms: The former tend to be much better at capturing energy from their environment and dissipating that energy as heat. [8] This paper contains the review of quantum entanglement investigations in living systems, and in the quantum mechanically modeled photoactive prebiotic kernel systems. [7] The human body is a constant flux of thousands of chemical/biological interactions and processes connecting molecules, cells, organs, and fluids, throughout the brain, body, and nervous system. Up until recently it was thought that all these interactions operated in a linear sequence, passing on information much like a runner passing the baton to the next runner. However, the latest findings in quantum biology and biophysics have discovered that there is in fact a tremendous degree of coherence within all living systems. The accelerating electrons explain not only the Maxwell Equations and the Special Relativity, but the Heisenberg Uncertainty Relation, the Wave-Particle Duality and the electron's spin also, building the Bridge between the Classical and Quantum Theories. The Planck Distribution Law of the electromagnetic oscillators explains the electron/proton mass rate and the Weak and Strong Interactions by the diffraction patterns. The Weak Interaction changes the diffraction patterns by moving the electric charge from one side to the other side of the diffraction pattern, which violates the CP and Time reversal symmetry. The diffraction patterns and the locality of the self-maintaining electromagnetic potential explains also the Quantum Entanglement, giving it as a natural part of the Relativistic Quantum Theory and making possible to understand the Quantum Biology.
Category: Artificial Intelligence