POV – Watson Privacy, Compliance, & Security
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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. -
About the Author
ABOUT THE AUTHOR Dr. Arvind Sathi is the World Wide Communication Sector archi- tect for big data at IBM® . Dr. Sathi received his Ph.D. in business administration from Carnegie Mellon University and worked under Nobel Prize winner Dr. Herbert A. Simon. Dr. Sathi is a seasoned professional with more than 20 years of leadership in information management architecture and delivery. His primary focus has been in creating visions and roadmaps for advanced analytics at lead- ing IBM clients in telecommunications, media and entertainment, and energy and utilities organizations worldwide. He has con- ducted a number of workshops on big data assessment and roadmap development. Prior to joining IBM, Dr. Sathi was a pioneer in d eveloping k nowledge-based solutions for CRM at Carnegie Group. At BearingPoint, he led the development of enterprise integration, master data man- agement (MDM), and operations support systems / business support systems (OSS/BSS) solutions for the communications market, and also developed horizontal solutions for communications, fi nancial services, and public services. At IBM, Dr. Sathi has led several infor- mation management programs in MDM, data security, business intel- ligence, advanced analytics, big data, and related areas, and provided strategic architecture oversight to IBM’s strategic accounts. He has also delivered a number of workshops and presentations at industry con- ferences on technical subjects, including MDM and data architecture, 202 ABOUT THE AUTHOR and he holds two patents in data masking. His fi rst book, Customer Experience Analytics , was released by MC Press in October 2011, and his second book, Big Data Analytics , was released in October 2012. -
Interconnect 2017 IBM Watson Iot Journey
IBM Watson IoT InterConnect Journey Map 2017 March 19 – 23 MGM Grand & Mandalay Bay Las Vegas, Nevada It all adds up! This is the conference you cannot afford to miss. 3 2/17/2017 The most influential thinkers, leaders, and innovators will join Ginni Rometty and IBM’s greatest minds to show you everything you need to know about cloud. Amy Wilkinson Bruce Schneier Dr. Sabine Hauert Mike McAvoy Prof Nick Jennings CEO of Ingenuity, Professor at Security Expert and CTO, President and Co-Founder President and CEO – Onion, Inc., CB FREng, Stanford Business School, Resilient of Robohub.org, Asst. Prof in EVP of Sales – Fusion Media Vice-Provost (Research), Author of The Creator's Code Robotics at Univ of Bristol Group (FMG) Imperial College London Adrian Gropper Don Tapscott Wayne Brady Daniel Hoffman Robert S. Mueller III, Former MD CTO, Patient Privacy Co-author, Emmy Winning Actor, Singer, Former Intelligence Officer, CIA Director, FBI and Partner, Rights Foundation Blockchain Revolution Dancer, Comedian, and WilmerHale Cyberbullying Activist 4 Asset Management Keynotes & Sessions This guide provides the comprehensive view of Asset Management journey at 2017 InterConnect. Review the complete sessions and build your personalized agenda with the Watson Sessions Expert Tool. Asset Management Keynotes & Sessions Time Session Title Location Sunday, March 19 Facilities Management Maximo Users Group 13:00 - 13:30 IAB-4388 Facilities MUG: Facilities Management Maximo User Group Business Meeting Mandalay Bay North, Level 0-South Pacific D 13:30 - 14:15 -
Think Journey Business and AI Campus
Think Journey Business and AI Campus March 19–March 22 Mandalay Bay Convention Center Las Vegas Think is the flagship IBM® conference built to help enhance or jumpstart your journey to AI and the cloud. Forty-thousand of the world’s most inspiring innovators, leaders and thinkers will be in attendance; gathering to learn how AI can solve business challenges, and to discuss the current state of the art and the future possibilities of AI. Think is IBM’s only conference in 2018, and it will be your last chance until Think 2019 to learn how to make the most of AI for your business. 1 Table of Contents Top seven things to know about AI, Watson™ and Think 2018 03 Access to Watson expertise and leadership 03 Think week at-a-glance 04 Watson clients and partners 04 Entertainment at Think 04 Watson Primer 05 Watson at Work Activations 06 Future of the Call Center in Augmented Reality 07 With Watson Studio 08 The eight sessions everyone should attend 09 Watson tech talks for beginners to experts 11 Client sessions not to be missed 13 Think Campus Map 20 Watson Campus Map 20 IBM Events mobile app 21 Transportation 21 Think Journey | Business and AI Campus 2 Top seven things to know about AI, Watson and Think 2018 1. Be the first to hear about the newest Watson AI products and solutions to be unveiled at Think 2. Attend one of 50+ client-led sessions to learn about projects with Watson 3. Develop or evolve your AI strategy and business case in hands-on sessions with IBM AI experts 4. -
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 -
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. -
Building the Cognitive Enterprise: Nine Action Areas Deep Dive
Research Insights Building the Cognitive Enterprise: Nine Action Areas Deep Dive This Deep Dive document is the in- depth version. For an abridged version, please read, “Building the Cognitive Enterprise: Nine Action Areas, Core Concepts.” Building the Cognitive Enterprise | 1 Mark Foster Senior Vice President IBM Services and Global Business Services Introduction A new era of business reinvention is dawning. Organizations are facing an unprecedented convergence of technological, social, and regulatory forces. As artificial intelligence, blockchain, automation, Internet of Things, 5G, and edge computing become pervasive, their combined impact will reshape standard business architectures. The “outside-in” digital transformation of the past decade is giving way to the “inside-out” potential of data exploited with these exponential technologies. We call this next-generation business model the Cognitive Enterprise™. 2 | Building the Cognitive Enterprise Table of contents Executive summary 3 Introduction to the Cognitive Enterprise 4 Chapter 1 Market-making Business Platforms 11 – Double down on “Big Bets” 15 – Create a new business blueprint 19 – Orchestrate compelling change 22 – Action guide 25 Chapter 2 Intelligent Workflows 26 – Embed exponential technologies 31 – Drive value from data 37 – Deploy through hybrid multicloud 39 – Action guide 42 Chapter 3 Enterprise Experience and Humanity 43 – Elevate human-technology partnerships 47 – Cultivate smart leadership, skills, and culture 51 – Perform with purposeful agility 55 – Action guide 58 Chapter 4 New way of building: Garage 59 Conclusion A new way to grow, a new way to compete 64 Related IBM Institute for Business Value studies 65 Notes and sources 66 Executive summary | 3 Executive summary The impact of the convergence of multiple exponential ever-clearer strategic bets that they are placing. -
Changeman ZMF Administrator's Guide
ChangeManZMF Administrator’s Guide © Copyright 2001-2019 Micro Focus or one of its affiliates. The only warranties for products and services of Micro Focus and its affiliates and licensors (“Micro Focus”) are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. Micro Focus shall not be liable for technical or editorial errors or omissions contained herein. The information contained herein is subject to change without notice. Contains Confidential Information. Except as specifically indicated otherwise, a valid license is required for possession, use or copying. Consistent with FAR 12.211 and 12.212, Commercial Computer Software, Computer Software Documentation, and Technical Data for Commercial Items are licensed to the U.S. Government under vendor's standard commercial license. Product version: 8.2 Patch 2 Publication date: September 2019 Table of Contents Welcome to ChangeMan® ZMF. 9 Guide to ChangeMan ZMF Documentation. 9 ChangeMan ZMF Documentation Suite . 9 Using the Manuals . 11 Searching the ChangeMan ZMF Documentation Suite. 11 Using the ISPF Interface . 13 Description of the ISPF Interface. 13 Using Online Help . 13 Typographical Conventions . 14 Notes . 14 Chapter 1 Introduction . 15 Global Administrator . 16 Application Administrator . 16 Security Administrator . 16 ChangeMan ZMF Monitor . 17 General Administrator . 17 Chapter 2 What is ChangeMan ZMF? . 19 Change Package . 20 Impact Analysis . 20 Checkout . 20 Staging. 21 Audit . 21 Recompile and Relink . 22 Freeze . 22 Promotion . 23 Approval . 23 Production Installation . 23 Baseline Libraries and Delta Decks. 24 Backout Management Facilities . 24 Emergency Changes. 24 ChangeMan ZMF Life Cycle . 24 Chapter 3 Pre-Implementation Decisions . -
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.