Using Neurobiological Frameworks for Anomaly Detection in System Log Streams
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Approximate Pattern Matching Using Hierarchical Graph Construction and Sparse Distributed Representation
Portland State University PDXScholar Dissertations and Theses Dissertations and Theses 9-29-2020 Approximate Pattern Matching Using Hierarchical Graph Construction and Sparse Distributed Representation Aakanksha Mathuria Portland State University Follow this and additional works at: https://pdxscholar.library.pdx.edu/open_access_etds Part of the Electrical and Computer Engineering Commons Let us know how access to this document benefits ou.y Recommended Citation Mathuria, Aakanksha, "Approximate Pattern Matching Using Hierarchical Graph Construction and Sparse Distributed Representation" (2020). Dissertations and Theses. Paper 5581. https://doi.org/10.15760/etd.7453 This Thesis is brought to you for free and open access. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of PDXScholar. Please contact us if we can make this document more accessible: [email protected]. Approximate Pattern Matching using Hierarchical Graph Construction and Sparse Distributed Representation by Aakanksha Mathuria A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Electrical and Computer Engineering Thesis Committee: Dan Hammerstrom, Chair Christof Teuscher Nirupama Bulusu Portland State University 2020 Abstract With recent developments in deep networks, there have been significant advances in visual object detection and recognition. However, some of these networks are still easily fooled/hacked and have shown ”bag of features” kinds of failures. Some of this is due to the fact that even deep networks make only marginal use of the complex structure that exists in real-world images. Primate visual systems appear to capture the structure in images, but how? In the research presented here, we are studying approaches for robust pattern matching using static, 2D Blocks World images based on graphical representations of the various components of an image. -
Mind-Crafting: Anticipatory Critique of Transhumanist Mind-Uploading in German High Modernist Novels Nathan Jensen Bates a Disse
Mind-Crafting: Anticipatory Critique of Transhumanist Mind-Uploading in German High Modernist Novels Nathan Jensen Bates A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington 2018 Reading Committee: Richard Block, Chair Sabine Wilke Ellwood Wiggins Program Authorized to Offer Degree: Germanics ©Copyright 2018 Nathan Jensen Bates University of Washington Abstract Mind-Crafting: Anticipatory Critique of Transhumanist Mind-Uploading in German High Modernist Novels Nathan Jensen Bates Chair of the Supervisory Committee: Professor Richard Block Germanics This dissertation explores the question of how German modernist novels anticipate and critique the transhumanist theory of mind-uploading in an attempt to avert binary thinking. German modernist novels simulate the mind and expose the indistinct limits of that simulation. Simulation is understood in this study as defined by Jean Baudrillard in Simulacra and Simulation. The novels discussed in this work include Thomas Mann’s Der Zauberberg; Hermann Broch’s Die Schlafwandler; Alfred Döblin’s Berlin Alexanderplatz: Die Geschichte von Franz Biberkopf; and, in the conclusion, Irmgard Keun’s Das Kunstseidene Mädchen is offered as a field of future inquiry. These primary sources disclose at least three aspects of the mind that are resistant to discrete articulation; that is, the uploading or extraction of the mind into a foreign context. A fourth is proposed, but only provisionally, in the conclusion of this work. The aspects resistant to uploading are defined and discussed as situatedness, plurality, and adaptability to ambiguity. Each of these aspects relates to one of the three steps of mind- uploading summarized in Nick Bostrom’s treatment of the subject. -
Sustainable Development, Technological Singularity and Ethics
European Research Studies Journal Volume XXI, Issue 4, 2018 pp. 714- 725 Sustainable Development, Technological Singularity and Ethics Vyacheslav Mantatov1, Vitaly Tutubalin2 Abstract: The development of modern convergent technologies opens the prospect of a new technological order. Its image as a “technological singularity”, i.e. such “transhuman” stage of scientific and technical progress, on which the superintelligence will be practically implemented, seems to be quite realistic. The determination of the basic philosophical coordinates of this future reality in the movement along the path of sustainable development of mankind is the most important task of modern science. The article is devoted to the study of the basic ontological, epistemological and moral aspects in the reception of the coming technological singularity. The method of this study is integrating dialectical and system approach. The authors come to the conclusion: the technological singularity in the form of a “computronium” (superintelligence) opens up broad prospects for the sustainable development of mankind in the cosmic dimension. This superintelligence will become an ally of man in the process of cosmic evolution. Keywords: Technological Singularity, Superintelligence, Convergent Technologies, Cosmocentrism, Human and Universe JEL code: Q01, Q56. 1East Siberia State University of Technology and Management, Ulan-Ude, Russia [email protected] 2East Siberia State University of Technology and Management, Ulan-Ude, Russia, [email protected] V. Mantatov, V. Tutubalin 715 1. Introduction Intelligence organizes the world by organizing itself. J. Piaget Technological singularity is defined as a certain moment or stage in the development of mankind, when scientific and technological progress will become so fast and complex that it will be unpredictable. -
Generative Models, Structural Similarity, and Mental Representation
The Mind as a Predictive Modelling Engine: Generative Models, Structural Similarity, and Mental Representation Daniel George Williams Trinity Hall College University of Cambridge This dissertation is submitted for the degree of Doctor of Philosophy August 2018 The Mind as a Predictive Modelling Engine: Generative Models, Structural Similarity, and Mental Representation Daniel Williams Abstract I outline and defend a theory of mental representation based on three ideas that I extract from the work of the mid-twentieth century philosopher, psychologist, and cybernetician Kenneth Craik: first, an account of mental representation in terms of idealised models that capitalize on structural similarity to their targets; second, an appreciation of prediction as the core function of such models; and third, a regulatory understanding of brain function. I clarify and elaborate on each of these ideas, relate them to contemporary advances in neuroscience and machine learning, and favourably contrast a predictive model-based theory of mental representation with other prominent accounts of the nature, importance, and functions of mental representations in cognitive science and philosophy. For Marcella Montagnese Preface Declaration This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except as declared in the Preface and specified in the text. It is not substantially the same as any that I have submitted, or, is being concurrently submitted for a degree or diploma or other qualification at the University of Cambridge or any other University or similar institution except as declared in the Preface and specified in the text. I further state that no substantial part of my dissertation has already been submitted, or, is being concurrently submitted for any such degree, diploma or other qualification at the University of Cambridge or any other University or similar institution except as declared in the Preface and specified in the text. -
Transhumanism Between Human Enhancement and Technological Innovation*
Transhumanism Between Human Enhancement and Technological Innovation* Ion Iuga Abstract: Transhumanism introduces from its very beginning a paradigm shift about concepts like human nature, progress and human future. An overview of its ideology reveals a strong belief in the idea of human enhancement through technologically means. The theory of technological singularity, which is more or less a radicalisation of the transhumanist discourse, foresees a radical evolutionary change through artificial intelligence. The boundaries between intelligent machines and human beings will be blurred. The consequence is the upcoming of a post-biological and posthuman future when intelligent technology becomes autonomous and constantly self-improving. Considering these predictions, I will investigate here the way in which the idea of human enhancement modifies our understanding of technological innovation. I will argue that such change goes in at least two directions. On the one hand, innovation is seen as something that will inevitably lead towards intelligent machines and human enhancement. On the other hand, there is a direction such as “Singularity University,” where innovation is called to pragmatically solving human challenges. Yet there is a unifying spirit which holds together the two directions and I think it is the same transhumanist idea. Keywords: transhumanism, technological innovation, human enhancement, singularity Each of your smartphones is more powerful than the fastest supercomputer in the world of 20 years ago. (Kathryn Myronuk) If you understand the potential of these exponential technologies to transform everything from energy to education, you have different perspective on how we can solve the grand challenges of humanity. (Ray Kurzweil) We seek to connect a humanitarian community of forward-thinking people in a global movement toward an abundant future (Singularity University, Impact report 2014). -
ARCHITECTS of INTELLIGENCE for Xiaoxiao, Elaine, Colin, and Tristan ARCHITECTS of INTELLIGENCE
MARTIN FORD ARCHITECTS OF INTELLIGENCE For Xiaoxiao, Elaine, Colin, and Tristan ARCHITECTS OF INTELLIGENCE THE TRUTH ABOUT AI FROM THE PEOPLE BUILDING IT MARTIN FORD ARCHITECTS OF INTELLIGENCE Copyright © 2018 Packt Publishing All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book. Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information. Acquisition Editors: Ben Renow-Clarke Project Editor: Radhika Atitkar Content Development Editor: Alex Sorrentino Proofreader: Safis Editing Presentation Designer: Sandip Tadge Cover Designer: Clare Bowyer Production Editor: Amit Ramadas Marketing Manager: Rajveer Samra Editorial Director: Dominic Shakeshaft First published: November 2018 Production reference: 2201118 Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK ISBN 978-1-78913-151-2 www.packt.com Contents Introduction ........................................................................ 1 A Brief Introduction to the Vocabulary of Artificial Intelligence .......10 How AI Systems Learn ........................................................11 Yoshua Bengio .....................................................................17 Stuart J. -
The Transhumanist Reader Is an Important, Provocative Compendium Critically Exploring the History, Philosophy, and Ethics of Transhumanism
TH “We are in the process of upgrading the human species, so we might as well do it E Classical and Contemporary with deliberation and foresight. A good first step is this book, which collects the smartest thinking available concerning the inevitable conflicts, challenges and opportunities arising as we re-invent ourselves. It’s a core text for anyone making TRA Essays on the Science, the future.” —Kevin Kelly, Senior Maverick for Wired Technology, and Philosophy “Transhumanism has moved from a fringe concern to a mainstream academic movement with real intellectual credibility. This is a great taster of some of the best N of the Human Future emerging work. In the last 10 years, transhumanism has spread not as a religion but as a creative rational endeavor.” SHU —Julian Savulescu, Uehiro Chair in Practical Ethics, University of Oxford “The Transhumanist Reader is an important, provocative compendium critically exploring the history, philosophy, and ethics of transhumanism. The contributors anticipate crucial biopolitical, ecological and planetary implications of a radically technologically enhanced population.” M —Edward Keller, Director, Center for Transformative Media, Parsons The New School for Design A “This important book contains essays by many of the top thinkers in the field of transhumanism. It’s a must-read for anyone interested in the future of humankind.” N —Sonia Arrison, Best-selling author of 100 Plus: How The Coming Age of Longevity Will Change Everything IS The rapid pace of emerging technologies is playing an increasingly important role in T overcoming fundamental human limitations. The Transhumanist Reader presents the first authoritative and comprehensive survey of the origins and current state of transhumanist Re thinking regarding technology’s impact on the future of humanity. -
The Technological Singularity and the Transhumanist Dream
ETHICAL CHALLENGES The technological singularity and the transhumanist dream Miquel Casas Araya Peralta In 1997, an AI beat a human world chess champion for the first time in history (it was IBM’s Deep Blue playing Garry Kasparov). Fourteen years later, in 2011, IBM’s Watson beat two winners of Jeopardy! (Jeopardy is a general knowledge quiz that is very popular in the United States; it demands a good command of the language). In late 2017, DeepMind’s AlphaZero reached superhuman levels of play in three board games (chess, go and shogi) in just 24 hours of self-learning without any human intervention, i.e. it just played itself. Some of the people who have played against it say that the creativity of its moves make it seem more like an alien that a computer program. But despite all that, in 2019 nobody has yet designed anything that can go into a strange kitchen and fry an egg. Are our machines truly intelligent? Successes and failures of weak AI The fact is that today AI can solve ever more complex specific problems with a level of reliability and speed beyond our reach at an unbeatable cost, but it fails spectacularly in the face of any challenge for which it has not been programmed. On the other hand, human beings have become used to trivialising everything that can be solved by an algorithm and have learnt to value some basic human skills that we used to take for granted, like common sense, because they make us unique. Nevertheless, over the last decade, some influential voices have been warning that our skills PÀGINA 1 / 9 may not always be irreplaceable. -
Artificial Intelligence: How Does It Work, Why Does It Matter, and What Can We Do About It?
Artificial intelligence: How does it work, why does it matter, and what can we do about it? STUDY Panel for the Future of Science and Technology EPRS | European Parliamentary Research Service Author: Philip Boucher Scientific Foresight Unit (STOA) PE 641.547 – June 2020 EN Artificial intelligence: How does it work, why does it matter, and what can we do about it? Artificial intelligence (AI) is probably the defining technology of the last decade, and perhaps also the next. The aim of this study is to support meaningful reflection and productive debate about AI by providing accessible information about the full range of current and speculative techniques and their associated impacts, and setting out a wide range of regulatory, technological and societal measures that could be mobilised in response. AUTHOR Philip Boucher, Scientific Foresight Unit (STOA), This study has been drawn up by the Scientific Foresight Unit (STOA), within the Directorate-General for Parliamentary Research Services (EPRS) of the Secretariat of the European Parliament. To contact the publisher, please e-mail [email protected] LINGUISTIC VERSION Original: EN Manuscript completed in June 2020. DISCLAIMER AND COPYRIGHT This document is prepared for, and addressed to, the Members and staff of the European Parliament as background material to assist them in their parliamentary work. The content of the document is the sole responsibility of its author(s) and any opinions expressed herein should not be taken to represent an official position of the Parliament. Reproduction and translation for non-commercial purposes are authorised, provided the source is acknowledged and the European Parliament is given prior notice and sent a copy. -
Anomalous Behavior Detection Framework Using HTM-Based Semantic Folding Technique
Hindawi Computational and Mathematical Methods in Medicine Volume 2021, Article ID 5585238, 14 pages https://doi.org/10.1155/2021/5585238 Research Article Anomalous Behavior Detection Framework Using HTM-Based Semantic Folding Technique Hamid Masood Khan ,1 Fazal Masud Khan,1 Aurangzeb Khan,2 Muhammad Zubair Asghar ,1 and Daniyal M. Alghazzawi 3 1Institute of Computing and Information Technology, Gomal University, D.I.Khan, Pakistan 2Department of Computer Science, University of Science and Technology, Bannu, Pakistan 3Information Systems Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia Correspondence should be addressed to Muhammad Zubair Asghar; [email protected] Received 23 January 2021; Revised 17 February 2021; Accepted 26 February 2021; Published 16 March 2021 Academic Editor: Waqas Haider Bangyal Copyright © 2021 Hamid Masood Khan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Upon the working principles of the human neocortex, the Hierarchical Temporal Memory model has been developed which is a proposed theoretical framework for sequence learning. Both categorical and numerical types of data are handled by HTM. Semantic Folding Theory (SFT) is based on HTM to represent a data stream for processing in the form of sparse distributed representation (SDR). For natural language perception and production, SFT delivers a solid structural background for semantic evidence description to the fundamentals of the semantic foundation during the phase of language learning. Anomalies are the patterns from data streams that do not follow the expected behavior. -
Approximate Pattern Matching Using Hierarchical Graph Construction and Sparse Distributed Representation
Portland State University PDXScholar Electrical and Computer Engineering Faculty Publications and Presentations Electrical and Computer Engineering 7-23-2019 Approximate Pattern Matching using Hierarchical Graph Construction and Sparse Distributed Representation Aakanksha Mathuria Portland State University, [email protected] Dan Hammerstrom Portland State University Follow this and additional works at: https://pdxscholar.library.pdx.edu/ece_fac Part of the Engineering Commons Let us know how access to this document benefits ou.y Citation Details "Approximate Pattern Matching using Hierarchical Graph Construction and Sparse Distributed Representation," A. Mathuria, D.W. Hammerstrom, International Conference on Neuromorphic Systems, Knoxville, TN, July 23-5, 2019 This Conference Proceeding is brought to you for free and open access. It has been accepted for inclusion in Electrical and Computer Engineering Faculty Publications and Presentations by an authorized administrator of PDXScholar. Please contact us if we can make this document more accessible: [email protected]. Approximate Pattern Matching using Hierarchical Graph Construction and Sparse Distributed Representation Aakanksha Mathuria Electrical and Computer Engineering Portland State University USA [email protected] Dan W. Hammerstrom Electrical and Computer Engineering Portland State University USA [email protected] ABSTRACT training on large numbers of images. None of these techniques actually captures the spatial relationships of the low level or high- With recent developments in deep networks, there have been level features, which biological networks appear to do. significant advances in visual object detection and Efficient graph representations capture the higher order recognition. However, some of these networks are still easily information content of the objects and provide algorithmic benefits fooled/hacked and have shown “bag of features” failures. -
Biologically-Inspired Machine Intelligence Technique for Activity Classification in Smart Home Environments
Biologically-Inspired Machine Intelligence Technique for Activity Classification in Smart Home Environments Talal Sarheed Alshammari A thesis submitted in partial fulfillment of the requirement of Staffordshire University for the degree of Doctor of Philosophy May 2019 List of Publications 2 REFEREED JOURNAL PUBLICATIONS OpenSHS: Open Smart Home Simulator May, 2017 Sensors Journal MDPI 2 REFEREED JOURNAL PUBLICATIONS SIMADL: Simulated Activities of Daily Living Dataset. April, 2018 Data Journal MDPI 2 REFEREED CONFERENCE PUBLICATIONS Evaluating Machine Learning Techniques for Activity Classifica- February ,2018 tion in Smart Home Environments World Academy of Science, Engineering and Technology International Journal of Infor- mation and Communication Engineering i Acknowledgements I would like to thank my supervisors Dr. Mohamed Sedky and Chris Howard for encour- aging and supporting me during my Ph.D study. They were very helpful and provided me their assistance throughout my Ph.D journey. It was very good experience to improve my research skills. Due to this experience, I learned new knowledge, found new ideas from your supervision. I appreciate your consideration, efforts and kind cooperation, you deserve all the thanks. I would like to thank to my parents and my wife for their unconditional support that has helped me for achieving this thesis. I would like to thank the Ministry of Education in Saudi Arabia and Hail university for funding and supporting this research. ii Contents List of Publicationsi Acknowledgements ii Table of Contents