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PACI to Increase Civil ID Fees to KD 5 from April 1
N IO T IP R C S B U S WEDNESDAY, FEBRUARY 3, 2016 RABI ALTHANI 24, 1437 AH www.kuwaittimes.net No Zika virus Alphabet Egypt actress McIlroy cases detected passes Apple Yousra aims inspired by in Kuwait: as biggest to raise Mideast ‘unreal’ Health 5Ministry company27 AIDS37 awareness Djokovic16 PACI to increase civil ID Min 07º fees to KD 5 from April 1 Max 21º High Tide 07:38 & 18:33 Silk City to be financed through BOT, PPP Low Tide 01:16 & 12:22 40 PAGES 40 16775 NO: FILS 150 By A Saleh and B Izzak KUWAIT: Director of The Public Authority for Civil White House race wide open Information (PACI) Musaed Mahmoud Al-Asoussi said that PACI will increase the charges collected for issuing civil ID cards from KD 2 to KD 5 and the charges for issuing a replacement from KD 10 to KD 20 from April. Asoussi Cruz bests Trump, Rubio Clinton edges Sanders explained that the fee increases had been recommended by the Audit Bureau because the actual cost of issuing ID DES MOINES, Iowa: The US presi- • cards exceeds KD 4.5, while the current fee is only KD 2. dential race looked suddenly wide Asoussi said PACI had accordingly finished adjusting its open yesterday after frontrunners systems and that the recommendation had been Donald Trump and Hillary Clinton reviewed by the fatwa and legislation department and suffered chastening evenings in PACI’s board of directors before Minister of State for Iowa, the first step on the long road Cabinet Affairs Sheikh Mohammed Al-Abdullah decided to the White House. -
“Where the Internet Lives” Data Centers As Cloud Infrastructure
C HAPTER 3 “Where the Internet Lives” Data Centers as Cloud Infrastructure JN OEN IFER H LT AND PATRICK VONDERAU mblazoned with the headline “Transparency,” Google released dozens of Einterior and exterior glossy images of their data centers on the company’s website in 2012. Inviting the public to “come inside” and “see where the In- ternet lives,” Google proudly announced they would reveal “what we’re made of— inside and out” by offering virtual tours through photo galleries of the tech- nology, the people, and the places making up their data centers.1 Google’s tours showed the world a glimpse of these structures with a series of photographs showcasing “the physical Internet,” as the site characterized it. The pictures consisted mainly of slick, artful images of buildings, wires, pipes, servers, and dedicated workers who populate the centers. Apple has also put the infrastructure behind its cloud services on display for the digital audience by featuring a host of infographics, statistics, and polished inside views of the company’s “environmentally responsible” data center fa- cilities on its website.2 Facebook, in turn, features extensive photo and news coverage of its global physical infrastructure on dedicated Facebook pages, while Microsoft presents guided video tours of their server farms for free download on its corporate website.3 Even smaller data centers like those owned by Eu- ropean Internet service provider Bahnhof AB, located in Sweden, are increas- ingly on digital exhibit, with their corporate parents offering various images of server racks, cooling and power technology, or even their meeting rooms, Copyright © ${Date}. -
Google's Hyperscale Data Centres and Infrastructure Ecosystem in Europe
GOOGLE’S HYPERSCALE DATA CENTRES AND INFRASTRUCTURE ECOSYSTEM IN EUROPE Economic impact study CLIENT: GOOGLE SEPTEMBER 2019 AUTHORS Dr Bruno Basalisco, Managing economist, Head of Digital Economy service Martin Bo Westh Hansen, Managing economist, Head of Energy & Climate service Tuomas Haanperä, Managing economist Erik Dahlberg, Senior economist Morten May Hansen, Economist Joshua Brown, Analyst Laurids Leo Münier, Analyst 0 Malthe Faber Laursen, Analyst Helge Sigurd Næss-Schmidt, Partner EXECUTIVE SUMMARY Digital transformation is a defining challenge and opportunity for the European economy, provid- ing the means to reinvent and improve how firms, consumers, governments, and citizens interact and do business with each other. European consumers, firms, and society stand to benefit from the resulting innovative products, processes, services, and business models – contributing to EU productivity. To maximise these benefits, it is key that the private and public sector can rely on an advanced and efficient cloud value chain. Considerable literature exists on cloud solutions and their transformative impact across the econ- omy. This report contributes by focusing on the analysis of the cloud value chain, taking Google as a relevant case study. It assesses the economic impact of the Google European hyperscale data cen- tres and related infrastructures which, behind the scenes, underpin online services such as cloud solutions. Thus, the report is an applied analysis of these infrastructure layers “above the cloud” (upstream inputs to deliver cloud solutions) and quantifies Google’s European economic contribu- tion associated with these activities. Double-clicking the cloud Services, such as Google Cloud, are a key example of a set of solutions that can serve a variety of Eu- ropean business needs and thus support economic productivity. -
Received Citations As a Main SEO Factor of Google Scholar Results Ranking
RECEIVED CITATIONS AS A MAIN SEO FACTOR OF GOOGLE SCHOLAR RESULTS RANKING Las citas recibidas como principal factor de posicionamiento SEO en la ordenación de resultados de Google Scholar Cristòfol Rovira, Frederic Guerrero-Solé and Lluís Codina Nota: Este artículo se puede leer en español en: http://www.elprofesionaldelainformacion.com/contenidos/2018/may/09_esp.pdf Cristòfol Rovira, associate professor at Pompeu Fabra University (UPF), teaches in the Depart- ments of Journalism and Advertising. He is director of the master’s degree in Digital Documenta- tion (UPF) and the master’s degree in Search Engines (UPF). He has a degree in Educational Scien- ces, as well as in Library and Information Science. He is an engineer in Computer Science and has a master’s degree in Free Software. He is conducting research in web positioning (SEO), usability, search engine marketing and conceptual maps with eyetracking techniques. https://orcid.org/0000-0002-6463-3216 [email protected] Frederic Guerrero-Solé has a bachelor’s in Physics from the University of Barcelona (UB) and a PhD in Public Communication obtained at Universitat Pompeu Fabra (UPF). He has been teaching at the Faculty of Communication at the UPF since 2008, where he is a lecturer in Sociology of Communi- cation. He is a member of the research group Audiovisual Communication Research Unit (Unica). https://orcid.org/0000-0001-8145-8707 [email protected] Lluís Codina is an associate professor in the Department of Communication at the School of Com- munication, Universitat Pompeu Fabra (UPF), Barcelona, Spain, where he has taught information science courses in the areas of Journalism and Media Studies for more than 25 years. -
Machine Learning for Marketers
Machine Learning for Marketers A COMPREHENSIVE GUIDE TO MACHINE LEARNING CONTENTS pg 3 Introduction pg 4 CH 1 The Basics of Machine Learning pg 9 CH. 2 Supervised vs Unsupervised Learning and Other Essential Jargon pg 13 CH. 3 What Marketers can Accomplish with Machine Learning pg 18 CH. 4 Successful Machine Learning Use Cases pg 26 CH. 5 How Machine Learning Guides SEO pg 30 CH. 6 Chatbots: The Machine Learning you are Already Interacting with pg 36 CH. 7 How to Set Up a Chatbot pg 45 CH. 8 How Marketers Can Get Started with Machine Learning pg 58 CH. 9 Most Effective Machine Learning Models pg 65 CH. 10 How to Deploy Models Online pg 72 CH. 11 How Data Scientists Take Modeling to the Next Level pg 79 CH. 12 Common Problems with Machine Learning pg 84 CH. 13 Machine Learning Quick Start INTRODUCTION Machine learning is a term thrown around in technol- ogy circles with an ever-increasing intensity. Major technology companies have attached themselves to this buzzword to receive capital investments, and every major technology company is pushing its even shinier parentartificial intelligence (AI). The reality is that Machine Learning as a concept is as days that only lives and breathes data science? We cre- old as computing itself. As early as 1950, Alan Turing was ated this guide for the marketers among us whom we asking the question, “Can computers think?” In 1969, know and love by giving them simpler tools that don’t Arthur Samuel helped define machine learning specifi- require coding for machine learning. -
Whitepaper Revised
Why Integrating Brand Safety In Your Video Advertising Strategy Is A Must The state of brand safety in video advertising, and how AI and computer vision can power the next-gen tech. ADS ADS ADS ADS Redefining the limits of contextual targeting with AI 1 Importance of brand safety Definition of brand safety Brand safety in the age of user generated content What creates an ‘unsafe’ environment Brand control is key State of brand safety on social video 2 platforms The rise and rise of YouTube’s brand safety crisis Facebook, Twitter and Tik Tok face similar issues 3 Why brand safety in video is elusive Keyword blacklists are killing reach and monetization Whitelisted channels lack authenticity The problematic programmatic pipes Human vetting will only go so far Advertisers choose reach over safety 4 A successful brand safety strategy Is artificial intelligence the answer? Context is important, in-video context is everything Redefining the limits of contextual targeting with AI The brand safety crisis Where it all began March 2017 marked the first major brand safety catastrophe in the video advertising world. Guardian, the British daily newspaper, blacklisted YouTube when it found its ads running alongside hate speech and extremist content. Subsequently, household brands like Toyota, Proctor & Gamble, AT&T, Verizon pulled out millions of dollars’ worth of ad spend from YouTube. For the first time, YouTube was dealing not only with reputation damage but also revenue damage. And it wouldn’t be the last time - YouTube continued to be blamed for hurtful brand exposure, despite introducing corrective measures throughout 2017, 2018 and 2019. -
Extinction Rebellion: Unabombers Without Bombs Page 5
EXTINCTION REBELLION: UNABOMBERS WITHOUT BOMBS PAGE 5 ALSO IN THIS ISSUE: The Great Ka-Pao! Silicon The Proteus Fund, Green Pension Valley’s Strike Against “Dark Money” 11 Hold-Up 20 Conservatives 37 Shapeshifter www.CapitalResearch.org Want to know more about the donors, foundations, nonprofits, activists, and others working to influence public policy? Visit: INFLUENCE WATCH.ORG Launched by Capital Research Center in August 2017, InfluenceWatch w i l l bring unprecedented transparency to the history, motives, and i n t e r conn ect ions o f all entities invo lve d in the advocacy m o v ement. Today, our growing website includes over 6,800 pages and over 1,200 full profiles, with more added each week. L ear n mor e a t In f l uen c e Wa t c h .o r g ISSUE 6, 2019 CONTENTS GREEN WATCH 3 Extinction Rebellion: COMMENTARY 5 Unabombers Without Bombs Donor Advised By Ken Braun “Dark Money”? By Hayden Ludwig LABOR WATCH The Great Green 11 Pension Hold-Up By Neil Meghami Capital Research is a monthly publication of the Capital Research Center (CRC), a nonpartisan education and research organization, classified by the IRS as a 501(c)(3) public charity. CRC is an independent, tax-exempt DECEPTION & MISDIRECTION institution governed by an independent Ka-Pao! Silicon Valley’s board of trustees. We rely on private 20 financial support from the general Strike Against Conservatives public—individuals, foundations, By David Hogberg and corporations—for our income. We accept no government funds and perform no contract work. -
Data Centers
REPORT HIGHLIGHTS Technological innovations are rapidly changing our lives, our Heat sensing drones deployed after natural disasters to locate businesses, and our economy. Technology, no longer an isolated survivors and deliver lifesaving equipment can arrive at the scene business sector, is a facilitator enabling innovation, growth, and faster than first responders. Wearable technologies that we sport the strengthening of America’s traditional business sectors. From help us lead healthier lifestyles. Distance learning courses empower transportation and energy to finance and medicine, businesses children and adults to learn new skills or trades to keep up with rely on technology to interact with their customers, improve their the constantly evolving job market. Innovations in science, energy, services, and make their operations more globally competitive. manufacturing, health care, education, transportation and many Innovative technology is deeply integrated into the economy and other fields—and their jobs—are being powered by data centers. is the driving force behind the creation of new jobs in science, health care, education, transportation, and more. Technology has But the benefits of data centers go beyond powering America’s fundamentally transformed our economy—and is poised to fuel even cutting-edge innovations. The economic impact, direct and indirect, more growth in the future. is substantial. Overall, there were 6 million jobs in the U.S. technology industry last While being built, a typical data center employs 1,688 local workers, year, and we expect this to increase by 4.1% in 2017. Technology- provides $77.7 million in wages for those workers, produces $243.5 related jobs run the gamut—from transportation logistics and million in output along the local economy’s supply chain, and warehousing to programmers and radiologists. -
Mapreduce Programming Oct 30, 2012
15-440" MapReduce Programming Oct 30, 2012" Topics" n" Large-scale computing" l" Traditional high-performance computing (HPC)! l" Cluster computing! n" MapReduce" l" Definition! l" Examples! n" Implementation" n" Alternatives to MapReduce" n" Properties" – 1 –! Typical HPC Machine" Compute Nodes" Compute Nodes n" High end processor(s)" CPU CPU CPU • • • n" Lots of RAM" Mem Mem Mem Network" n" Specialized" Network n" Very high performance" Storage Server" • • • n" RAID-based disk array" Storage Server – 2 –! HPC Machine Example" Jaguar Supercomputer" n" 3rd fastest in world" Compute Nodes" n" 18,688 nodes in largest partition" n" 2X 2.6Ghz 6-core AMD Opteron" n" 16GB memory" n" Total: 2.3 petaflop / 300 TB memory" Network" n" 3D torus" l" Each node connected to 6 neighbors via 6.0 GB/s links! Storage Server" n" 10PB RAID-based disk array" – 3 –! HPC Programming Model" Application Programs Software Packages Machine-Dependent Programming Model Hardware n" Programs described at very low level" l" Specify detailed control of processing & communications! n" Rely on small number of software packages" l" Written by specialists! l" Limits classes of problems & solution methods! – 4 –! Bulk Synchronous Programming" Solving Problem Over Grid" n" E.g., finite-element computation" Partition into Regions" n" p regions for p processors" Map Region per Processor" n" Local computation sequential" n" Periodically communicate boundary values with neighbors" – 5 –! Typical HPC Operation" Characteristics" n" Long-lived processes" Message Passing" n" Make use -
Envisioning the Cloud: the Next Computing Paradigm
Marketspace® Point of View Envisioning the Cloud: The Next Computing Paradigm March 20, 2009 Jeffrey F. Rayport Andrew Heyward Research Associates Raj Beri Jake Samuelson Geordie McClelland Funding for this paper was provided by Google, Inc Table of Contents Executive Summary .................................................................................... i Introduction................................................................................................ 1 Understanding the cloud...................................................................... 3 The network is the (very big, very powerful) computer .................... 6 How the data center became possible ............................................. 8 The passengers are driving the bus ...................................................11 Where we go from here......................................................................12 Benefits and Opportunities in the Cloud ..............................................14 Anywhere/anytime access to software............................................14 Specialization and customization of applications...........................17 Collaboration .......................................................................................20 Processing power on demand...........................................................21 Storage as a universal service............................................................23 Cost savings in the cloud ....................................................................24 Enabling the Cloud -
The Machine Learning Journey with Google
The Machine Learning Journey with Google Google Cloud Professional Services The information, scoping, and pricing data in this presentation is for evaluation/discussion purposes only and is non-binding. For reference purposes, Google's standard terms and conditions for professional services are located at: https://enterprise.google.com/terms/professional-services.html. 1 What is machine learning? 2 Why all the attention now? Topics How Google can support you inyour 3 journey to ML 4 Where to from here? © 2019 Google LLC. All rights reserved. What is machine0 learning? 1 Machine learning is... a branch of artificial intelligence a way to solve problems without explicitly codifying the solution a way to build systems that improve themselves over time © 2019 Google LLC. All rights reserved. Key trends in artificial intelligence and machine learning #1 #2 #3 #4 Democratization AI and ML will be core Specialized hardware Automation of ML of AI and ML competencies of for deep learning (e.g., MIT’s Data enterprises (CPUs → GPUs → TPUs) Science Machine & Google’s AutoML) #5 #6 #7 Commoditization of Cloud as the platform ML set to transform deep learning for AI and ML banking and (e.g., TensorFlow) financial services © 2019 Google LLC. All rights reserved. Use of machine learning is rapidly accelerating Used across products © 2019 Google LLC. All rights reserved. Google Translate © 2019 Google LLC. All rights reserved. Why all the attention0 now? 2 Machine learning allows us to solve problems without codifying the solution. © 2019 Google LLC. All rights reserved. San Francisco New York © 2019 Google LLC. All rights reserved. -
And with Google Or Related Entities
What We Can Learn from Google’s Support for Hillary Clinton Google executives and employees bet heavily on a Clinton victory, hoping to extend the company’s influence on the Obama White House. They lost that bet, and are left scrambling to find an entrée to the Trump Administration. Google’s playbook with Clinton reveals how the company most likely will seek to influence the new administration. There already are signs of that influence: Joshua Wright, who co-wrote a Google-funded paper while on the faculty of George Mason University and currently works at Google’s main antitrust law firm, was named to the Trump transition team on competition issues. Alex Pollock, of the Google-funded R Street Institute, has also been named to oversee the transition at the FTC, which oversees Google's conduct. Introduction Google’s extraordinarily close relationship with President Obama’s administration led to a long list of policy victories of incalculable value to its business.1 An in-depth examination of the company’s efforts to extend that special relationship into the next administration, which it wrongly predicted would be led by Hillary Clinton, reveal what we might expect from Google for the incoming Trump administration. Google’s executives and employees employed a variety of strategies to elect Hillary Clinton and defeat Donald Trump. Google permeated Clinton’s sphere of influence on a broad scale, rivaling the influence it exerted over the Obama administration. A review found at least 57 people were affiliated with both Clinton—in her presidential campaign, in her State Department, at her family foundation—and with Google or related entities.