IBM's Watson Supercomputer
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History of AI at IBM and How IBM Is Leveraging Watson for Intellectual Property
History of AI at IBM and How IBM is Leveraging Watson for Intellectual Property 2019 ECC Conference June 9-11 at Marist College IBM Intellectual Property Management Solutions 1 IBM Intellectual Property Management Solutions © 2017-2019 IBM Corporation Who are We? At IBM for 37 years I currently work in the Technology and Intellectual Property organization, a combination of CHQ and Research. I have worked as an engineer in Procurement, Testing, MLC Packaging, and now T&IP. Currently Lead Architect on IP Advisor with Watson, a Watson based Patent and Intellectual Property Analytics tool. • Master Inventor • Number of patents filed ~ 24+ • Number of submissions in progress ~ 4+ • Consult/Educate outside companies on all things IP (from strategy to commercialization, including IP 101) • Technical background: Semiconductors, Computers, Programming/Software, Tom Fleischman Intellectual Property and Analytics [email protected] Is the manager of the Intellectual Property Management Solutions team in CHQ under the Technology and Intellectual Property group. Current OM for IP Advisor with Watson application, used internally and externally. Past Global Business Services in the PLM and Supply Chain practices. • Number of patents filed – 2 (2018) • Number of submissions in progress - 2 • Consult/Educate outside companies on all things IP (from strategy to commercialization, including IP 101) • Schaumburg SLE Sue Hallen • Technical background: Registered Professional Engineer in Illinois, Structural Engineer by [email protected] degree, lots of software development and implementation for PLM clients 2 IBM Intellectual Property Management Solutions © 2017-2019 IBM Corporation How does IBM define AI? IBM refers to it as Augmented Intelligence…. • Not artificial or meant to replace Human Thinking…augments your work AI Terminology Machine Learning • Provides computers with the ability to continuing learning without being pre-programmed. -
Big Blue in the Bottomless Pit: the Early Years of IBM Chile
Big Blue in the Bottomless Pit: The Early Years of IBM Chile Eden Medina Indiana University In examining the history of IBM in Chile, this article asks how IBM came to dominate Chile’s computer market and, to address this question, emphasizes the importance of studying both IBM corporate strategy and Chilean national history. The article also examines how IBM reproduced its corporate culture in Latin America and used it to accommodate the region’s political and economic changes. Thomas J. Watson Jr. was skeptical when he The history of IBM has been documented first heard his father’s plan to create an from a number of perspectives. Former em- international subsidiary. ‘‘We had endless ployees, management experts, journalists, and opportunityandlittleriskintheUS,’’he historians of business, technology, and com- wrote, ‘‘while it was hard to imagine us getting puting have all made important contributions anywhere abroad. Latin America, for example to our understanding of IBM’s past.3 Some seemed like a bottomless pit.’’1 However, the works have explored company operations senior Watson had a different sense of the outside the US in detail.4 However, most of potential for profit within the world market these studies do not address company activi- and believed that one day IBM’s sales abroad ties in regions of the developing world, such as would surpass its growing domestic business. Latin America.5 Chile, a slender South Amer- In 1949, he created the IBM World Trade ican country bordered by the Pacific Ocean on Corporation to coordinate the company’s one side and the Andean cordillera on the activities outside the US and appointed his other, offers a rich site for studying IBM younger son, Arthur K. -
The Evolution of Ibm Research Looking Back at 50 Years of Scientific Achievements and Innovations
FEATURES THE EVOLUTION OF IBM RESEARCH LOOKING BACK AT 50 YEARS OF SCIENTIFIC ACHIEVEMENTS AND INNOVATIONS l Chris Sciacca and Christophe Rossel – IBM Research – Zurich, Switzerland – DOI: 10.1051/epn/2014201 By the mid-1950s IBM had established laboratories in New York City and in San Jose, California, with San Jose being the first one apart from headquarters. This provided considerable freedom to the scientists and with its success IBM executives gained the confidence they needed to look beyond the United States for a third lab. The choice wasn’t easy, but Switzerland was eventually selected based on the same blend of talent, skills and academia that IBM uses today — most recently for its decision to open new labs in Ireland, Brazil and Australia. 16 EPN 45/2 Article available at http://www.europhysicsnews.org or http://dx.doi.org/10.1051/epn/2014201 THE evolution OF IBM RESEARCH FEATURES he Computing-Tabulating-Recording Com- sorting and disseminating information was going to pany (C-T-R), the precursor to IBM, was be a big business, requiring investment in research founded on 16 June 1911. It was initially a and development. Tmerger of three manufacturing businesses, He began hiring the country’s top engineers, led which were eventually molded into the $100 billion in- by one of world’s most prolific inventors at the time: novator in technology, science, management and culture James Wares Bryce. Bryce was given the task to in- known as IBM. vent and build the best tabulating, sorting and key- With the success of C-T-R after World War I came punch machines. -
Treatment and Differential Diagnosis Insights for the Physician's
Treatment and differential diagnosis insights for the physician’s consideration in the moments that matter most The role of medical imaging in global health systems is literally fundamental. Like labs, medical images are used at one point or another in almost every high cost, high value episode of care. Echocardiograms, CT scans, mammograms, and x-rays, for example, “atlas” the body and help chart a course forward for a patient’s care team. Imaging precision has improved as a result of technological advancements and breakthroughs in related medical research. Those advancements also bring with them exponential growth in medical imaging data. The capabilities referenced throughout this document are in the research and development phase and are not available for any use, commercial or non-commercial. Any statements and claims related to the capabilities referenced are aspirational only. There were roughly 800 million multi-slice exams performed in the United States in 2015 alone. Those studies generated approximately 60 billion medical images. At those volumes, each of the roughly 31,000 radiologists in the U.S. would have to view an image every two seconds of every working day for an entire year in order to extract potentially life-saving information from a handful of images hidden in a sea of data. 31K 800MM 60B radiologists exams medical images What’s worse, medical images remain largely disconnected from the rest of the relevant data (lab results, patient-similar cases, medical research) inside medical records (and beyond them), making it difficult for physicians to place medical imaging in the context of patient histories that may unlock clues to previously unconsidered treatment pathways. -
Cell Broadband Engine Spencer Dennis Nicholas Barlow the Cell Processor
Cell Broadband Engine Spencer Dennis Nicholas Barlow The Cell Processor ◦ Objective: “[to bring] supercomputer power to everyday life” ◦ Bridge the gap between conventional CPU’s and high performance GPU’s History Original patent application in 2002 Generations ◦ 90 nm - 2005 ◦ 65 nm - 2007 (PowerXCell 8i) ◦ 45 nm - 2009 Cost $400 Million to develop Team of 400 engineers STI Design Center ◦ Sony ◦ Toshiba ◦ IBM Design PS3 Employed as CPU ◦ Clocked at 3.2 GHz ◦ theoretical maximum performance of 23.04 GFLOPS Utilized alongside NVIDIA RSX 'Reality Synthesizer' GPU ◦ Complimented graphical performance ◦ 8 Synergistic Processing Elements (SPE) ◦ Single Dual Issue Power Processing Element (PPE) ◦ Memory IO Controller (MIC) ◦ Element Interconnect Bus (EIB) ◦ Memory IO Controller (MIC) ◦ Bus Interface Controller (BIC) Architecture Overview SPU/SPE Synergistic Processing Unit/Element SXU - Synergistic Execution Unit LS - Local Store SMF - Synergistic Memory Frontend EIB - Element Interconnect Bus PPE - Power Processing Element MIC - Memory IO Controller BIC - Bus Interface Controller Synergistic Processing Element (SPE) 128-bit dual-issue SIMD dataflow ○ “Single Instruction Multiple Data” ○ Optimized for data-level parallelism ○ Designed for vectorized floating point calculations. ◦ Workhorses of the Processor ◦ Handle most of the computational workload ◦ Each contains its own Instruction + Data Memory ◦ “Local Store” ▫ Embedded SRAM SPE Continued Responsible for governing SPEs ◦ “Extensions” of the PPE Shares main memory with SPE ◦ can initiate -
Lecture Notes in Computer Science 7032 Commenced Publication in 1973 Founding and Former Series Editors: Gerhard Goos, Juris Hartmanis, and Jan Van Leeuwen
Lecture Notes in Computer Science 7032 Commenced Publication in 1973 Founding and Former Series Editors: Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen Editorial Board David Hutchison Lancaster University, UK Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M. Kleinberg Cornell University, Ithaca, NY, USA Alfred Kobsa University of California, Irvine, CA, USA Friedemann Mattern ETH Zurich, Switzerland John C. Mitchell Stanford University, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel Oscar Nierstrasz University of Bern, Switzerland C. Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen TU Dortmund University, Germany Madhu Sudan Microsoft Research, Cambridge, MA, USA Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Gerhard Weikum Max Planck Institute for Informatics, Saarbruecken, Germany Lora Aroyo Chris Welty Harith Alani Jamie Taylor Abraham Bernstein Lalana Kagal Natasha Noy Eva Blomqvist (Eds.) The Semantic Web – ISWC 2011 10th International Semantic Web Conference Bonn, Germany, October 23-27, 2011 Proceedings, Part II 13 Volume Editors Lora Aroyo VU University Amsterdam, The Netherlands; [email protected] Chris Welty IBM Research, Yorktown Heights, NY, USA; [email protected] Harith Alani The Open University, Milton Keynes, UK; [email protected] Jamie Taylor Google, Mountain View, CA, USA; [email protected] Abraham Bernstein University of Zurich, -
Cheryl Watson's
Cheryl Watson’s 1998, No. 6 TUNING Letter A PRACTICAL JOURNAL OF S/390 TUNING AND MEASUREMENT ADVICE Inside this issue... This Issue: My heart attack is important news, at least from my point of view. See page 2. But I'm feeling really great these days, thanks to A Note From Cheryl & Tom .2 modern medicine. Management Issues #20 ......3 Class Schedule .....................4 Upgrading a processor is the focus of this issue. How to size, S/390 News how to understand the difference between speed and capacity, and GRS Star .............................5 how to avoid typical problems after an upgrade are all covered MXG & CA-MICS.................5 starting on page 14. CMOS & Compression ......5 Y2K ......................................6 Java and Component Broker are featured in two articles pro- Java .....................................6 vided by Glenn Anderson of IBM Education (page 6). Component Broker ............7 LE.........................................9 IBM is now recommending that multi-system sites be at WSC Flashes ....................10 OS/390 R5 before freezing systems for Y2K. See WSC Flash The Net..............................11 98044 on page 10 for this important item. Pubs & APARs .................12 Focus: Processor Upgrades A known integrity exposure in ISPF has existed for the five Sizing Processors............14 years since ISPF V4, but new customers keep running into the Migration Issues...............23 problem. See page 29. Upgrade Problems...........26 Cheryl's Updates New Web links and important new manuals and books are Most Common Q&As.......28 listed in our S/390 News starting on page 12. TCP/IP................................28 ISPF Exposure..................29 Don't go to OS/390 R5 without checking with your TCP/IP WLM Update .....................30 vendors or you could be in serious trouble. -
An Overview of Ontoclean
8 An Overview of OntoClean Nieola Guarino1 and Christopher A. Welty lLaboratory for Applied Ontology (ISTC-CNR) Polo Tecnologico, Via Solteri 38, 38100 Trento, ITAL Y [email protected] 2IBM Watson Research Center 19 Skyline Dr., Hawthome, NY 10532, USA [email protected] Summary. OntoClean is a methodology for validating the ontologie al adequaey of taxonomie relationships. It is based on highly general ontologieal notions drawn from philosophy, like essence, identity, and unity, whieh are used to ehar aeterize relevant aspeets of the intended meaning of the properties, classes, and relations that make up an ontology. These aspeets are represented by formal metaproperties, whieh impose several eonstraints on the taxonomie strueture of an ontology. The analysis of these eonstraints helps in evaluating and validating the ehoiees made. In this ehapter we present an informal overview ofthe philoso phieal notions involved and their role in OntoClean, review some eommon onto logieal pitfalls, and walk through the example that has appeared in pieees in pre vious papers and has been the basis of numerous tutorials and talks. 8.1 Introduction The OntoClean methodology was first introdueed in aseries of eonferenee-Iength papers in 2000 [Guarino and Welty, 2000a-e; Welty and Guarino, 2001], and re eeived mueh attention and use in subsequent years. The main eontribution of On toClean was the beginning of a formal foundation for ontologieal analysis. Alan Reetor, a seasoned veteran at ontologieal analysis in the medieal domain, said of OntoClean, " ... what you have done is reduee the amount of time I spend arguing with doetors that the way I want to model the world is right..." [Reetor, 2002]. -
Watson Machine Learning for Z/OS — Jamar Smith Data Scientist, North America Z Hybrid Cloud [email protected]
Watson Machine Learning for z/OS — Jamar Smith Data Scientist, North America z Hybrid Cloud [email protected] 1 Goal Demonstrate the value of enterprise analytics on the IBM Z platform. 2 Agenda Enterprise Analytics Strategy Machine Learning Overview Value of Analytics in Place IBM Cloud Pak 4 Data 3 Enterprise Analytics Strategy 4 Current trends in analytics The need for Pervasive Analytics is increasing in almost every industry Real time or near real time analytic results are necessary Need to leverage all relevant data sources available for insight Ease demands on highly sought-after analytic skill base Embrace rapid pace of innovation 5 Data gravity key to enterprise analytics Performance matters Core transactional for variety of data on systems of record are and off IBM Z on IBM Z Predominance of data Real-time / near real- originates on IBM Z, time insights are z/OS (transactions, valuable member info, …) Data volume is large, distilling data Data Security / data privacy provides operational needs to be preserved efficiencies Gravity Podcast: http://www.ibmbigdatahub.com/podcast/making-data-simple-what-data-gravity 6 IBM Z Analytics Keep your data in place – a different approach to enterprise analytics • Keep data in place for analytics • Keep data in place, encrypted and secure • Minimize latency, cost and complexity of data movement • Transform data on platform • Improve data quality and governance • Apply the same resiliency to analytics as your operational applications • Combine insight from structured & unstructured data from z and non-z data sources • Leverage existing people, processes and infrastructure 7 Machine Learning Overview 8 What is Machine Learning? Computers that learn without being explicitly programmed. -
Cristobalthesis
Open Personalization: Involving Third Parties in Improving the User Experience of Websites Dissertation presented to the Department of Computer Languages and Systems of the University of the Basque Country in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy (“international” mention) Cristóbal Arellano Bartolomé Supervisors: Prof. Dr. Oscar Díaz García Dr. Jon Iturrioz Sánchez San Sebastián, Spain, 2013 This work was hosted by the University of the Basque Country (Faculty of Computer Sciences). The author enjoyed a doctoral grant under de FPI (Formacion de Personal Investigador) from the Spanish Ministry of Science & Education during the years 2007 to 2011. The work was was co- supported by the Spanish Ministry of Education, and the European Social Fund under contracts (TIN2005-05610), MODELINE (TIN2008-06507- C02-01) and Scriptongue (TIN2011-23839). Summary Traditional software development captures the user needs during the requirement analysis. The Web makes this endeavour even harder due to the difficulty to determine who these users are. In an attempt to tackle the heterogeneity of the user base, Web Personalization techniques are proposed to guide the users’ experience. In addition, Open Innovation allows organisations to look beyond their internal resources to develop new products or improve existing processes. This thesis sits in between by introducing Open Personalization as a means to incorporate actors other than webmasters in the personalization of web applications. The aim is to provide the technological basis that builds up a trusty environment for webmasters and companion actors to collaborate, i.e. "an architecture of participation". Such architecture very much depends on these actors’ profile. -
An Introduction to the Cell Broadband Engine Architecture
IBM Systems & Technology Group An Introduction to the Cell Broadband Engine Architecture Owen Callanan IBM Ireland, Dublin Software Lab. Email: [email protected] 1 Cell Programming Workshop 5/7/2009 © 2009 IBM Corporation IBM Systems & Technology Group Agenda About IBM Ireland development Cell Introduction Cell Architecture Programming the Cell – SPE programming – Controlling data movement – Tips and tricks Trademarks – Cell Broadband Engine and Cell Broadband Engine Architecture are trademarks of Sony Computer Entertainment, Inc. 2 Cell Programming Workshop 5/7/2009 © 2009 IBM Corporation IBM Systems & Technology Group Introduction - Development in IBM Ireland Lotus Software Research Tivoli Industry Assets & Models RFID Center of Competence High Performance Computing 3 Cell Programming Workshop 5/7/2009 © 2009 IBM Corporation IBM Systems & Technology Group Introduction – HPC in IBM Dublin Lab Blue Gene team Deep Computing Visualization (DCV) Dynamic Application Virtualization (DAV) Other areas also – E.g. RDMA communications systems 4 Cell Programming Workshop 5/7/2009 © 2009 IBM Corporation IBM Systems & Technology Group Cell Introduction 5 Cell Programming Workshop 5/7/2009 © 2009 IBM Corporation IBM Systems & Technology Group Cell Broadband Engine History IBM, SCEI/Sony, Toshiba Alliance formed in 2000 Design Center opens March 2001 ~$400M Investment, 5 years, 600 people February 7, 2005: First technical disclosures January 12, 2006: Alliance extended 5 additional years YKT, EFK, BURLINGTON, ENDICOTT ROCHESTER -
Semantic Web: a Review of the Field Pascal Hitzler [email protected] Kansas State University Manhattan, Kansas, USA
Semantic Web: A Review Of The Field Pascal Hitzler [email protected] Kansas State University Manhattan, Kansas, USA ABSTRACT which would probably produce a rather different narrative of the We review two decades of Semantic Web research and applica- history and the current state of the art of the field. I therefore do tions, discuss relationships to some other disciplines, and current not strive to achieve the impossible task of presenting something challenges in the field. close to a consensus – such a thing seems still elusive. However I do point out here, and sometimes within the narrative, that there CCS CONCEPTS are a good number of alternative perspectives. The review is also necessarily very selective, because Semantic • Information systems → Graph-based database models; In- Web is a rich field of diverse research and applications, borrowing formation integration; Semantic web description languages; from many disciplines within or adjacent to computer science, Ontologies; • Computing methodologies → Description log- and a brief review like this one cannot possibly be exhaustive or ics; Ontology engineering. give due credit to all important individual contributions. I do hope KEYWORDS that I have captured what many would consider key areas of the Semantic Web field. For the reader interested in obtaining amore Semantic Web, ontology, knowledge graph, linked data detailed overview, I recommend perusing the major publication ACM Reference Format: outlets in the field: The Semantic Web journal,1 the Journal of Pascal Hitzler. 2020. Semantic Web: A Review Of The Field. In Proceedings Web Semantics,2 and the proceedings of the annual International of . ACM, New York, NY, USA, 7 pages.