DOCSLIB.ORG

Redefining Ingenuity®

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Redefining Ingenuity® 5% 2% Air Force OTHER REDEFINING ® 24% Army INGENUITY 28% FEDERAL CIVILIAN WHOM 54% SAIC® is a premier technology DEPARTMENT integrator solving our nation’s most WE SERVE OF DEFENSE OUR CUSTOMER MIX* complex modernization and readiness 14% challenges. Our robust portfolio of 16% Navy/Marine INTELLIGENCE Corps offerings across the defense, space, civilian, and intelligence markets 11% Other DoD includes high-end solutions in * Last twelve months (LTM) as of the end of the fourth quarter of fiscal year 2019 for SAIC (February 1, 2019), including the trailing twelve engineering, IT, and mission solutions. months of revenues from the acquisition of Engility Holdings, Inc. Using our expertise and understanding of existing and emerging technologies, SAIC AT A GLANCE we integrate the best components from our own portfolio and our partner 23,000 $6.5B ecosystem to deliver innovative, EMPLOYEES REVENUES* effective, and efficient solutions. 6,000+ ~90% VETERANS PRIME CONTRACTS HOLD A SECURITY CONTRACT 60% CLEARANCE 3,000+ VEHICLES HEADQUARTERS CEO NYSE TICKER SAIC.COM CONNECT 12010 Sunset Hills Road Nazzic Keene SAIC Reston, VA 20190 August 2019 • WHAT WE DO: Our Practices Enterprise IT Software Cyber Advanced Analytics Engineering, Training & Mission & Simulation Integration, & Logistics Solutions • Infrastructure engineering and • App modernization and migration • Governance, risk and • Data frameworks and • Digital engineering services • Training delivery modernization • Mission and enterprise software compliance environments • Technical and knowledge • Training asset development • Cloud integration development • Cyberspace operations • Data management processes and management services • Training infrastructure and support toolkits • Digital platform services • Artificial intelligence/machine • Security operation and incident • Mission engineering and concept • Program management, business, • User experience and support learning enabled software management • Modeling and simulation development and office support development • Personal compute services • Infrastructure security • Analysis services • System definition services • Strategic comms and multimedia • Cloud-native software • Cyber training • Mission applications and tools • System build and test services production • IT operations and business development integration • System operation and • Acquisition management • Transformation services sustainment services • Logistics and supply chain services WHO WE ARE OPERATING MODEL LOCATIONS Southwestern Indiana Civilian Markets Defense Systems National Security Group Group Group Solutions & Technology Group D.C. Metro 7,000+ employees San Diego Metro Virginia Beach Charleston VISION Huntsville Serve as the premier technology integrator in our market by making a profound difference Oklahoma City supporting our customers’ missions, engaging the best talent in industry, and providing strong shareholder returns. 500+ employees CORE VALUES SAIC also has employees deployed in 40+ international countries in support of our customers’ missions. Integrity I Mission Understanding I Empowerment I Creativity © SAIC. All rights reserved. This presentation consists of SAIC general capabilities information that does not contain controlled technical data as defined by 20-0479 the International Traffic in Arms (ITAR) Part 120.10 or Export Administration Regulations (EAR) Part 734.7-11. SAIC-CR00223.
Load more

Recommended publications
  • At Least in Biophysical Novelties Amihud Gilead
    The Twilight of Determinism: At Least in Biophysical Novelties Amihud Gilead Department of Philosophy, Eshkol Tower, University of Haifa, Haifa 3498838 Email: [email protected] Abstract. In the 1990s, Richard Lewontin referred to what appeared to be the twilight of determinism in biology. He pointed out that DNA determines only a little part of life phenomena, which are very complex. In fact, organisms determine the environment and vice versa in a nonlinear way. Very recently, biophysicists, Shimon Marom and Erez Braun, have demonstrated that controlled biophysical systems have shown a relative autonomy and flexibility in response which could not be predicted. Within the boundaries of some restraints, most of them genetic, this freedom from determinism is well maintained. Marom and Braun have challenged not only biophysical determinism but also reverse-engineering, naive reductionism, mechanism, and systems biology. Metaphysically possibly, anything actual is contingent.1 Of course, such a possibility is entirely excluded in Spinoza’s philosophy as well as in many philosophical views at present. Kant believed that anything phenomenal, namely, anything that is experimental or empirical, is inescapably subject to space, time, and categories (such as causality) which entail the undeniable validity of determinism. Both Kant and Laplace assumed that modern science, such as Newton’s physics, must rely upon such a deterministic view. According to Kant, free will is possible not in the phenomenal world, the empirical world in which we 1 This is an assumption of a full-blown metaphysics—panenmentalism—whose author is Amihud Gilead. See Gilead 1999, 2003, 2009 and 2011, including literary, psychological, and natural applications and examples —especially in chemistry —in Gilead 2009, 2010, 2013, 2014a–c, and 2015a–d.
    [Show full text]
  • Artificial General Intelligence and Classical Neural Network
    Artificial General Intelligence and Classical Neural Network Pei Wang Department of Computer and Information Sciences, Temple University Room 1000X, Wachman Hall, 1805 N. Broad Street, Philadelphia, PA 19122 Web: http://www.cis.temple.edu/∼pwang/ Email: [email protected] Abstract— The research goal of Artificial General Intelligence • Capability. Since we often judge the level of intelligence (AGI) and the notion of Classical Neural Network (CNN) are of other people by evaluating their problem-solving capa- specified. With respect to the requirements of AGI, the strength bility, some people believe that the best way to achieve AI and weakness of CNN are discussed, in the aspects of knowledge representation, learning process, and overall objective of the is to build systems that can solve hard practical problems. system. To resolve the issues in CNN in a general and efficient Examples: various expert systems. way remains a challenge to future neural network research. • Function. Since the human mind has various cognitive functions, such as perceiving, learning, reasoning, acting, I. ARTIFICIAL GENERAL INTELLIGENCE and so on, some people believe that the best way to It is widely recognized that the general research goal of achieve AI is to study each of these functions one by Artificial Intelligence (AI) is twofold: one, as certain input-output mapping. Example: various intelligent tools. • As a science, it attempts to provide an explanation of • Principle. Since the human mind seems to follow certain the mechanism in the human mind-brain complex that is principles of information processing, some people believe usually called “intelligence” (or “cognition”, “thinking”, that the best way to achieve AI is to let computer systems etc.).
    [Show full text]
  • Artificial Intelligence: Distinguishing Between Types & Definitions
    19 NEV. L.J. 1015, MARTINEZ 5/28/2019 10:48 AM ARTIFICIAL INTELLIGENCE: DISTINGUISHING BETWEEN TYPES & DEFINITIONS Rex Martinez* “We should make every effort to understand the new technology. We should take into account the possibility that developing technology may have im- portant societal implications that will become apparent only with time. We should not jump to the conclusion that new technology is fundamentally the same as some older thing with which we are familiar. And we should not hasti- ly dismiss the judgment of legislators, who may be in a better position than we are to assess the implications of new technology.”–Supreme Court Justice Samuel Alito1 TABLE OF CONTENTS INTRODUCTION ............................................................................................. 1016 I. WHY THIS MATTERS ......................................................................... 1018 II. WHAT IS ARTIFICIAL INTELLIGENCE? ............................................... 1023 A. The Development of Artificial Intelligence ............................... 1023 B. Computer Science Approaches to Artificial Intelligence .......... 1025 C. Autonomy .................................................................................. 1026 D. Strong AI & Weak AI ................................................................ 1027 III. CURRENT STATE OF AI DEFINITIONS ................................................ 1029 A. Black’s Law Dictionary ............................................................ 1029 B. Nevada .....................................................................................
    [Show full text]
  • Ingenuity in Mathematics Ross Honsberger 10.1090/Nml/023
    AMS / MAA ANNELI LAX NEW MATHEMATICAL LIBRARY VOL 23 Ingenuity in Mathematics Ross Honsberger 10.1090/nml/023 INGENUITY IN MATHEMAmCS NEW MATHEMATICAL LIBRARY PUBLISHED BY THEMATHEMATICAL ASSOCIATION OF AMERICA Editorial Committee Basil Gordon, Chairman (1975-76) Anneli Lax, Editor University of California, L.A. New York University Ivan Niven (1 975-77) University of Oregon M. M. Schiffer (1975-77) Stanford University The New Mathematical Library (NML) was begun in 1961 by the School Mathematics Study Group to make available to high school students short expository books on various topics not usually covered in the high school syllabus. In a decade the NML matured into a steadily growing series of some twenty titles of interest not only to the originally intended audience, but to college students and teachers at all levels. Previously published by Random House and L. W. Singer, the NML became a publication series of the Mathematical Association of America (MAA) in 1975. Under the auspices of the MAA the NML will continue to grow and will remain dedicated to its original and expanded purposes. INGENUITY IN MATHEMATICS by Ross Honsberger University of Waterloo, Canada 23 MATHEMATICAL ASSOCIATION OF AMERICA Illustrated by George H. Buehler Sixth Printing © Copyright 1970, by the Mathematical Association of America A11 rights reserved under International and Pan-American Copyright Conventions. Published in Washington by The Mathematical Association of America Library of Congress Catalog Card Number: 77-134351 Print ISBN 978-0-88385-623-9 Electronic ISBN 978-0-88385-938-4 Manufactured in the United States of America Note to the Reader his book is one of a series written by professional mathematicians Tin order to make some important mathematical ideas interesting and understandable to a large audience of high school students and laymen.
    [Show full text]
  • Artificial Intelligence/Artificial Wisdom
    Artificial Intelligence/Artificial Wisdom - A Drive for Improving Behavioral and Mental Health Care (06 September to 10 September 2021) Department of Computer Science & Information Technology Central University of Jammu, J&K-181143 Preamble An Artificial Intelligence is the capability of a machine to imitate intelligent human behaviour. Machine learning is based on the idea that machines should be able to learn and adapt through experience. Machine learning is a subset of AI. That is, all machine learning counts as AI, but not all AI counts as machine learning. Artificial intelligence (AI) technology holds both great promises to transform mental healthcare and potential pitfalls. Artificial intelligence (AI) is increasingly employed in healthcare fields such as oncology, radiology, and dermatology. However, the use of AI in mental healthcare and neurobiological research has been modest. Given the high morbidity and mortality in people with psychiatric disorders, coupled with a worsening shortage of mental healthcare providers, there is an urgent need for AI to help identify high-risk individuals and provide interventions to prevent and treat mental illnesses. According to the publication Spectrum News, a form of AI called "deep learning" is sometimes better able than human beings to spot relevant patterns. This five days course provides an overview of AI approaches and current applications in mental healthcare, a review of recent original research on AI specific to mental health, and a discussion of how AI can supplement clinical practice while considering its current limitations, areas needing additional research, and ethical implications regarding AI technology. The proposed workshop is envisaged to provide opportunity to our learners to seek and share knowledge and teaching skills in cutting edge areas from the experienced and reputed faculty.
    [Show full text]
  • Machine Guessing – I
    Machine Guessing { I David Miller Department of Philosophy University of Warwick COVENTRY CV4 7AL UK e-mail: [email protected] ⃝c copyright D. W. Miller 2011{2018 Abstract According to Karl Popper, the evolution of science, logically, methodologically, and even psy- chologically, is an involved interplay of acute conjectures and blunt refutations. Like biological evolution, it is an endless round of blind variation and selective retention. But unlike biological evolution, it incorporates, at the stage of selection, the use of reason. Part I of this two-part paper begins by repudiating the common beliefs that Hume's problem of induction, which com- pellingly confutes the thesis that science is rational in the way that most people think that it is rational, can be solved by assuming that science is rational, or by assuming that Hume was irrational (that is, by ignoring his argument). The problem of induction can be solved only by a non-authoritarian theory of rationality. It is shown also that because hypotheses cannot be distilled directly from experience, all knowledge is eventually dependent on blind conjecture, and therefore itself conjectural. In particular, the use of rules of inference, or of good or bad rules for generating conjectures, is conjectural. Part II of the paper expounds a form of Popper's critical rationalism that locates the rationality of science entirely in the deductive processes by which conjectures are criticized and improved. But extreme forms of deductivism are rejected. The paper concludes with a sharp dismissal of the view that work in artificial intelligence, including the JSM method cultivated extensively by Victor Finn, does anything to upset critical rationalism.
    [Show full text]
  • Body, Mind and Spirit—Philosophical Reflections for Researching
    education sciences Article Body, Mind and Spirit—Philosophical Reflections for Researching Education about the Holocaust Katalin Eszter Morgan Historisches Institut, Fakultät für Geisteswissenschaften, Universität Duisburg-Essen, Campus Essen, Universitätsstr, 12 45117 Essen, Germany; [email protected], Tel.: +49-201-183-7395 Received: 14 August 2017; Accepted: 14 September 2017; Published: 20 September 2017 Abstract: This reflective essay draws a sketch of the theoretical and philosophical foundations in preparation for conducting a research project that investigates how German school learners deal with the memories of Shoah survivors. The essay explores some communication challenges and opportunities presented by the use of the double linguistic medium—German and English. The central philosophical argument is that there is a conceptual conflation of and confusion around the word Geist (spirit/mind), and that the difference between the spirit and the mind needs to be explored and clarified. For this purpose Hegel’s thoughts on the spirit are considered and related to theories of memory. Also, Theodor Lessing’s reflections on the origins of hatred are touched upon, which he traces back to the splitting of the spirit from the mind. How the body, mind and spirit work together is highlighted with a biographical example of a descendant of a Nazi perpetrator. By way of conclusion, the philosophical and methodological implications for researching education about the Shoah are briefly discussed. Keywords: education about the holocaust; Hegel; spirit; mind; Geist; memory; language 1. Introduction This essay sketches out some theoretical and philosophical ideas in preparation for conducting a research project that investigates how learners deal with the memories of Holocaust survivors in German schools.
    [Show full text]
  • How Empiricism Distorts Ai and Robotics
    HOW EMPIRICISM DISTORTS AI AND ROBOTICS Dr Antoni Diller School of Computer Science University of Birmingham Birmingham, B15 2TT, UK email: [email protected] Abstract rently, Cog has no legs, but it does have robotic arms and a head with video cameras for eyes. It is one of the most im- The main goal of AI and Robotics is that of creating a hu- pressive robots around as it can recognise various physical manoid robot that can interact with human beings. Such an objects, distinguish living from non-living things and im- android would have to have the ability to acquire knowl- itate what it sees people doing. Cynthia Breazeal worked edge about the world it inhabits. Currently, the gaining of with Cog when she was one of Brooks’s graduate students. beliefs through testimony is hardly investigated in AI be- She said that after she became accustomed to Cog’s strange cause researchers have uncritically accepted empiricism. appearance interacting with it felt just like playing with a Great emphasis is placed on perception as a source of baby and it was easy to imagine that Cog was alive. knowledge. It is important to understand perception, but There are several major research projects in Japan. A even more important is an understanding of testimony. A common rationale given by scientists engaged in these is sketch of a theory of testimony is presented and an appeal the need to provide for Japan’s ageing population. They say for more research is made. their robots will eventually act as carers for those unable to look after themselves.
    [Show full text]
  • Artificial Intelligence for Robust Engineering & Science January 22
    Artificial Intelligence for Robust Engineering & Science January 22 – 24, 2020 Organizing Committee General Chair: Logistics Chair: David Womble Christy Hembree Program Director, Artificial Intelligence Project Support, Artificial Intelligence Oak Ridge National Laboratory Oak Ridge National Laboratory Committee Members: Jacob Hinkle Justin Newcomer Research Scientist, Computational Sciences Manager, Machine Intelligence and Engineering Sandia National Laboratories Oak Ridge National Laboratory Frank Liu Clayton Webster Distinguished R&D Staff, Computational Distinguished Professor, Department of Sciences and Mathematics Mathematics Oak Ridge National Laboratory University of Tennessee–Knoxville Robust engineering is the process of designing, building, and controlling systems to avoid or mitigate failures and everything fails eventually. This workshop will examine the use of artificial intelligence and machine learning to predict failures and to use this capability in the maintenance and operation of robust systems. The workshop comprises four sessions examining the technical foundations of artificial intelligence and machine learning to 1) Examine operational data for failure indicators 2) Understand the causes of the potential failure 3) Deploy these systems “at the edge” with real-time inference and continuous learning, and 4) Incorporate these capabilities into robust system design and operation. The workshop will also include an additional session open to attendees for “flash” presentations that address the conference theme. AGENDA Wednesday, January 22, 2020 7:30–8:00 a.m. │ Badging, Registration, and Breakfast 8:00–8:45 a.m. │ Welcome and Introduction Jeff Nichols, Oak Ridge National Laboratory David Womble, Oak Ridge National Laboratory 8:45–9:30 a.m. │ Keynote Presentation: Dave Brooks, General Motors Company AI for Automotive Engineering 9:30–10:00 a.m.
    [Show full text]
  • The Virtues of Ingenuity: Reasoning and Arguing Without Bias
    Topoi DOI 10.1007/s11245-013-9174-y The Virtues of Ingenuity: Reasoning and Arguing without Bias Olivier Morin Ó Springer Science+Business Media Dordrecht 2013 Abstract This paper describes and defends the ‘‘virtues Ingenuity is the use of reasoning to gather information of ingenuity’’: detachment, lucidity, thoroughness. Philos- and to solve problems. This paper is about its virtues,in ophers traditionally praise these virtues for their role in the both senses of the term: the things that ingenuity is good practice of using reasoning to solve problems and gather for, and the qualities that it takes to be good at it. The information. Yet, reasoning has other, no less important philosophical tradition, particularly since Bacon and uses. Conviction is one of them. A recent revival of rhet- Descartes, has praised detachment, freedom from pre- oric and argumentative approaches to reasoning (in psy- judice, and objectivity, in terms that may sound quaintly chology, philosophy and science studies) has highlighted excessive today. The celebration of ingenuity often went the virtues of persuasiveness and cast a new light on some along with a demotion of other uses of reasoning. Con- of its apparent vices—bad faith, deluded confidence, con- viction, or persuasion—the use of reasoning to change firmation and myside biases. Those traits, it is often argued, other people’s minds—was one of them. Conviction and will no longer look so detrimental once we grasp their ingenuity arguably require different dispositions: a con- proper function: arguing in order to persuade, rather than vincing argumentation benefits from a sensitivity to other thinking in order to solve problems.
    [Show full text]
  • Artificial Intelligence and National Security
    Artificial Intelligence and National Security Artificial intelligence will have immense implications for national and international security, and AI’s potential applications for defense and intelligence have been identified by the federal government as a major priority. There are, however, significant bureaucratic and technical challenges to the adoption and scaling of AI across U.S. defense and intelligence organizations. Moreover, other nations—particularly China and Russia—are also investing in military AI applications. As the strategic competition intensifies, the pressure to deploy untested and poorly understood systems to gain competitive advantage could lead to accidents, failures, and unintended escalation. The Bipartisan Policy Center and Georgetown University’s Center for Security and Emerging Technology (CSET), in consultation with Reps. Robin Kelly (D-IL) and Will Hurd (R-TX), have worked with government officials, industry representatives, civil society advocates, and academics to better understand the major AI-related national and economic security issues the country faces. This paper hopes to shed more clarity on these challenges and provide actionable policy recommendations, to help guide a U.S. national strategy for AI. BPC’s effort is primarily designed to complement the work done by the Obama and Trump administrations, including President Barack Obama’s 2016 The National Artificial Intelligence Research and Development Strategic Plan,i President Donald Trump’s Executive Order 13859, announcing the American AI Initiative,ii and the Office of Management and Budget’s subsequentGuidance for Regulation of Artificial Intelligence Applications.iii The effort is also designed to further June 2020 advance work done by Kelly and Hurd in their 2018 Committee on Oversight 1 and Government Reform (Information Technology Subcommittee) white paper Rise of the Machines: Artificial Intelligence and its Growing Impact on U.S.
    [Show full text]
  • The Agency of Assemblages and the North American Blackout
    The Agency of Assemblages and the North American Blackout Jane Bennett The Agency of Assemblages Globalization names a state of affairs in which Earth, no longer simply an eco- logical or geological category, has become a salient unit of political analysis. More than locality or nation, Earth is the whole in which the parts (e.g., finance capital, CO2 emissions, refugees, viruses, pirated DVDs, ozone, human rights, weapons of mass destruction) now circulate. There have been various attempts to theorize this complex, gigantic whole and to characterize the kind of relationality obtaining between its parts. Network is one such attempt, as is Michael Hardt and Antonio Negri’s empire.1 My term of choice to describe this whole and its style of structuration, is, following Gilles Deleuze, the assemblage.2 I am grateful to Natalie Baggs, Diana Coole, William Connolly, Ben Corson, Jennifer Culbert, Ann Curthoys, John Docker, Ruby Lal, Patchen Markell, Gyanendra Pandey, Paul Saurette, Michael Shapiro, and the editorial committee of Public Culture for their contributions to this essay. 1. See Michael Hardt and Antonio Negri, Empire (Cambridge, Mass.: Harvard University Press, 2001) and Multitude: War and Democracy in the Age of Empire (New York: Penguin, 2004). 2. An assemblage is, first, an ad hoc grouping, a collectivity whose origins are historical and circumstantial, though its contingent status says nothing about its efficacy, which can be quite strong. An assemblage is, second, a living, throbbing grouping whose coherence coexists with energies and countercultures that exceed and confound it. An assemblage is, third, a web with an uneven topography: some of the points at which the trajectories of actants cross each other are more heavily trafficked than others, and thus power is not equally distributed across the assemblage.
    [Show full text]