Google's 'Project Nightingale' Gathers Personal Health Data
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July 23, 2020 the Honorable William P. Barr Attorney General United
July 23, 2020 The Honorable William P. Barr Attorney General United States Department of Justice 950 Pennsylvania Avenue, NW Washington, DC 20530 Dear Attorney General Barr: We write to raise serious concerns regarding Google LLC’s (Google) proposed acquisition of Fitbit, Inc. (Fitbit).1 We are aware that the Antitrust Division of the Department of Justice is investigating this transaction and has issued a Second Request to gather additional information about the acquisition’s potential effects on competition.2 Amid reports that Google is offering modest, short-term concessions to overseas enforcers to avoid a full-scale investigation of the transaction in Europe,3 we write to urge the Division to continue with its efforts to conduct a thorough and comprehensive review of this proposed merger and to take any and all enforcement action warranted by the law and the evidence. It is no exaggeration to say that Google is under intense antitrust scrutiny across the globe. As you know, the company has been under investigation for potential anticompetitive conduct across a number of product markets by the Department and numerous state attorneys general, as well as by a number of foreign competition enforcers, some of which are also reviewing the proposed Fitbit acquisition. Competition concerns about Google are widespread and bipartisan. Against this backdrop, in November 2019, Google announced its proposed acquisition of Fitbit for $2.1 billion, a staggering 71 percent premium over Fitbit’s pre-announcement stock price.4 Fitbit—which makes wearable technology devices, such as smartwatches and fitness trackers— has more than 28 million active users submitting sensitive location and health data to the company. -
Identificação De Textos Em Imagens CAPTCHA Utilizando Conceitos De
Identificação de Textos em Imagens CAPTCHA utilizando conceitos de Aprendizado de Máquina e Redes Neurais Convolucionais Relatório submetido à Universidade Federal de Santa Catarina como requisito para a aprovação da disciplina: DAS 5511: Projeto de Fim de Curso Murilo Rodegheri Mendes dos Santos Florianópolis, Julho de 2018 Identificação de Textos em Imagens CAPTCHA utilizando conceitos de Aprendizado de Máquina e Redes Neurais Convolucionais Murilo Rodegheri Mendes dos Santos Esta monografia foi julgada no contexto da disciplina DAS 5511: Projeto de Fim de Curso e aprovada na sua forma final pelo Curso de Engenharia de Controle e Automação Prof. Marcelo Ricardo Stemmer Banca Examinadora: André Carvalho Bittencourt Orientador na Empresa Prof. Marcelo Ricardo Stemmer Orientador no Curso Prof. Ricardo José Rabelo Responsável pela disciplina Flávio Gabriel Oliveira Barbosa, Avaliador Guilherme Espindola Winck, Debatedor Ricardo Carvalho Frantz do Amaral, Debatedor Agradecimentos Agradeço à minha mãe Terezinha Rodegheri, ao meu pai Orlisses Mendes dos Santos e ao meu irmão Camilo Rodegheri Mendes dos Santos que sempre estiveram ao meu lado, tanto nos momentos de alegria quanto nos momentos de dificuldades, sempre me deram apoio, conselhos, suporte e nunca duvidaram da minha capacidade de alcançar meus objetivos. Agradeço aos meus colegas Guilherme Cornelli, Leonardo Quaini, Matheus Ambrosi, Matheus Zardo, Roger Perin e Victor Petrassi por me acompanharem em toda a graduação, seja nas disciplinas, nos projetos, nas noites de estudo, nas atividades extracurriculares, nas festas, entre outros desafios enfrentados para chegar até aqui. Agradeço aos meus amigos de infância Cássio Schmidt, Daniel Lock, Gabriel Streit, Gabriel Cervo, Guilherme Trevisan, Lucas Nyland por proporcionarem momentos de alegria mesmo a distância na maior parte da caminhada da graduação. -
4. Google Health a Number of Companies Offer to Store Personal
4. Google Health A number of companies offer to store personal health records on the Web. Companies in this business hope to capitalize on the huge market of interested consumers seeking online health information and controlled health spending. The newest entry is Google Health with its technical know-how, deep pockets, and familiarity to consumers. A trial of Google's program with Cleveland Clinic patients was quickly oversubscribed, quelling fears that patients would worry about the security of their records. Google Health users will create their own electronic medical record online, with the capability to enter and manage health information and access it online from anywhere. This portable medical record will be accessible regardless of doctor, moves, insurance changes, etc. The record can be set to send reminders to refill prescriptions and schedule return medical visits. Permission from the patient is required to access the patient's record; however, there are important exceptions noted in the Google Health Terms of Service and Sharing Authorization to which users must agree when they sign on for the service. Google Health is free to users. Experts have long touted electronic medical records as a way to overcome the lack of coordination among health care providers. In addition, electronic records provide patients and providers with search capability linking information in the patient's records with information about health care alternatives, thereby giving patients more control over their health care choices. Access is available to patients, and to providers with patient consent. Google Health allows the patient to determine what information is shared with medical providers and pharmacies. -
Vikas Sindhwani Google May 17-19, 2016 2016 Summer School on Signal Processing and Machine Learning for Big Data
Real-time Learning and Inference on Emerging Mobile Systems Vikas Sindhwani Google May 17-19, 2016 2016 Summer School on Signal Processing and Machine Learning for Big Data Abstract: We are motivated by the challenge of enabling real-time "always-on" machine learning applications on emerging mobile platforms such as next-generation smartphones, wearable computers and consumer robotics systems. On-device models in such settings need to be highly compact, and need to support fast, low-power inference on specialized hardware. I will consider the problem of building small-footprint non- linear models based on kernel methods and deep learning techniques, for on-device deployments. Towards this end, I will give an overview of various techniques, and introduce new notions of parsimony rooted in the theory of structured matrices. Such structured matrices can be used to recycle Gaussian random vectors in order to build randomized feature maps in sub-linear time for approximating various kernel functions. In the deep learning context, low-displacement structured parameter matrices admit fast function and gradient evaluation. I will discuss how such compact nonlinear transforms span a rich range of parameter sharing configurations whose statistical modeling capacity can be explicitly tuned along a continuum from structured to unstructured. I will present empirical results on mobile speech recognition problems, and image classification tasks. I will also briefly present some basics of TensorFlow: a open-source library for numerical computations on data flow graphs. Tensorflow enables large-scale distributed training of complex machine learning models, and their rapid deployment on mobile devices. Bio: Vikas Sindhwani is Research Scientist in the Google Brain team in New York City. -
BRKIOT-2394.Pdf
Unlocking the Mystery of Machine Learning and Big Data Analytics Robert Barton Jerome Henry Distinguished Architect Principal Engineer @MrRobbarto Office of the CTAO CCIE #6660 @wirelessccie CCDE #2013::6 CCIE #24750 CWNE #45 BRKIOT-2394 Cisco Webex Teams Questions? Use Cisco Webex Teams to chat with the speaker after the session How 1 Find this session in the Cisco Events Mobile App 2 Click “Join the Discussion” 3 Install Webex Teams or go directly to the team space 4 Enter messages/questions in the team space BRKIOT-2394 © 2020 Cisco and/or its affiliates. All rights reserved. Cisco Public 3 Tuesday, Jan. 28th Monday, Jan. 27th Wednesday, Jan. 29th BRKIOT-2600 BRKIOT-2213 16:45 Enabling OT-IT collaboration by 17:00 From Zero to IOx Hero transforming traditional industrial TECIOT-2400 networks to modern IoT Architectures IoT Fundamentals 08:45 BRKIOT-1618 Bootcamp 14:45 Industrial IoT Network Management PSOIOT-1156 16:00 using Cisco Industrial Network Director Securing Industrial – A Deep Dive. Networks: Introduction to Cisco Cyber Vision PSOIOT-2155 Enhancing the Commuter 13:30 BRKIOT-1775 Experience - Service Wireless technologies and 14:30 BRKIOT-2698 BRKIOT-1520 Provider WiFi at the Use Cases in Industrial IOT Industrial IoT Routing – Connectivity 12:15 Cisco Remote & Mobile Asset speed of Trains and Beyond Solutions PSOIOT-2197 Cisco Innovates Autonomous 14:00 TECIOT-2000 Vehicles & Roadways w/ IoT BRKIOT-2497 BRKIOT-2900 Understanding Cisco's 14:30 IoT Solutions for Smart Cities and 11:00 Automating the Network of Internet Of Things (IOT) BRKIOT-2108 Communities Industrial Automation Solutions Connected Factory Architecture Theory and 11:00 Practice PSOIOT-2100 BRKIOT-1291 Unlock New Market 16:15 Opening Keynote 09:00 08:30 Opportunities with LoRaWAN for IOT Enterprises Embedded Cisco services Technologies IOT IOT IOT Track #CLEMEA www.ciscolive.com/emea/learn/technology-tracks.html Cisco Live Thursday, Jan. -
Warned That Big, Messy AI Systems Would Generate Racist, Unfair Results
JULY/AUG 2021 | DON’T BE EVIL warned that big, messy AI systems would generate racist, unfair results. Google brought her in to prevent that fate. Then it forced her out. Can Big Tech handle criticism from within? BY TOM SIMONITE NEW ROUTES TO NEW CUSTOMERS E-COMMERCE AT THE SPEED OF NOW Business is changing and the United States Postal Service is changing with it. We’re offering e-commerce solutions from fast, reliable shipping to returns right from any address in America. Find out more at usps.com/newroutes. Scheduled delivery date and time depend on origin, destination and Post Office™ acceptance time. Some restrictions apply. For additional information, visit the Postage Calculator at http://postcalc.usps.com. For details on availability, visit usps.com/pickup. The Okta Identity Cloud. Protecting people everywhere. Modern identity. For one patient or one billion. © 2021 Okta, Inc. and its affiliates. All rights reserved. ELECTRIC WORD WIRED 29.07 I OFTEN FELT LIKE A SORT OF FACELESS, NAMELESS, NOT-EVEN- A-PERSON. LIKE THE GPS UNIT OR SOME- THING. → 38 ART / WINSTON STRUYE 0 0 3 FEATURES WIRED 29.07 “THIS IS AN EXTINCTION EVENT” In 2011, Chinese spies stole cybersecurity’s crown jewels. The full story can finally be told. by Andy Greenberg FATAL FLAW How researchers discovered a teensy, decades-old screwup that helped Covid kill. by Megan Molteni SPIN DOCTOR Mo Pinel’s bowling balls harnessed the power of physics—and changed the sport forever. by Brendan I. Koerner HAIL, MALCOLM Inside Roblox, players built a fascist Roman Empire. -
Testimony of Marc Donner, Director of Engineering, Google Health
Testimony of Marc Donner, Director of Engineering, Google Health National Committee on Vital and Health Statistics Executive Subcommittee on Privacy, Confidentiality & Security Hearing on Personal Health Records May 20, 2009 Good afternoon and thank you for the opportunity to testify before the subcommittee on the important issue of Personal Health Records (PHRs). My name is Marc Donner and I am the Engineering Director for Google Health™. I have over thirty years of experience in engineering of hardware, software, and complex systems, and I hold a Ph.D. in Computer Science from Carnegie-Mellon University. My role on the Google Health team is to supervise the infrastructure and product design of Google Health. The focus of my attention is on ensuring our ability to scale, receive standards-compliant data from as many sources as possible, protect the integrity and privacy of PHR information, and increase the usefulness of Google Health data for our users. In my testimony today, I would like to focus on three main points: First, I'd like to discuss PHRs and their role in the healthcare industry. Second, I'll describe Google's health-related initiatives including Google Health, our own PHR product. Finally, I will make a handful of policy recommendations based on the experience that Google™ has had to date with health information technology generally and PHRs specifically. PHRs and how they fit into the bigger picture Google Health launched its PHR in the spring of 2008. In 2006, it was estimated that were roughly 200 PHRs. 1 In the past three years, many more products have emerged, along with Google’s offering. -
Gmail Smart Compose: Real-Time Assisted Writing
Gmail Smart Compose: Real-Time Assisted Writing Mia Xu Chen∗ Benjamin N Lee∗ Gagan Bansal∗ [email protected] [email protected] [email protected] Google Google Google Yuan Cao Shuyuan Zhang Justin Lu [email protected] [email protected] [email protected] Google Google Google Jackie Tsay Yinan Wang Andrew M. Dai [email protected] [email protected] [email protected] Google Google Google Zhifeng Chen Timothy Sohn Yonghui Wu [email protected] [email protected] [email protected] Google Google Google Figure 1: Smart Compose Screenshot. ABSTRACT our proposed system design and deployment approach. This system In this paper, we present Smart Compose, a novel system for gener- is currently being served in Gmail. ating interactive, real-time suggestions in Gmail that assists users in writing mails by reducing repetitive typing. In the design and KEYWORDS deployment of such a large-scale and complicated system, we faced Smart Compose, language model, assisted writing, large-scale serv- several challenges including model selection, performance eval- ing uation, serving and other practical issues. At the core of Smart ACM Reference Format: arXiv:1906.00080v1 [cs.CL] 17 May 2019 Compose is a large-scale neural language model. We leveraged Mia Xu Chen, Benjamin N Lee, Gagan Bansal, Yuan Cao, Shuyuan Zhang, state-of-the-art machine learning techniques for language model Justin Lu, Jackie Tsay, Yinan Wang, Andrew M. Dai, Zhifeng Chen, Timothy training which enabled high-quality suggestion prediction, and Sohn, and Yonghui Wu. 2019. Gmail Smart Compose: Real-Time Assisted constructed novel serving infrastructure for high-throughput and Writing. In The 25th ACM SIGKDD Conference on Knowledge Discovery and real-time inference. -
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. -
Future of Patient Data Patient of Future Insights from Discussions Multiple Around the Expert World
Future of Patient Data Insights from Multiple Expert Discussions Around the World World Expert the Around Multiple Discussions from Insights FUTURE OF PATIENT DATA Insights from Multiple Expert Discussions Around the World 1 Future of Patient Data Insights from Multiple Expert Discussions Around the World World Expert the Around Multiple Discussions from Insights 2 Future of Patient Data Insights from Multiple Expert Discussions Around the World World Expert the Around Multiple Discussions from Insights FUTURE OF PATIENT DATA Insights from Multiple Expert Discussions Around the World 3 Contents Foreword 6 Acknowledgements 7 Introduction 8 Future of Patient Data Context 16 Shared Challenges 26 Integration 28 Ownership vs. Access 38 Trust 45 Insights from Multiple Expert Discussions Around the World World Expert the Around Multiple Discussions from Insights Security and Privacy 52 Future Opportunities 58 Personalisation 60 Data Marketplaces 68 The Impact of AI 73 New Models 86 Emerging Issues 96 Data Sovereignty 98 Digital Inequality 102 Privatisation of Health Information 111 The Value of Health Data 115 Conclusions 120 Questions 122 Appendix 124 4 Charts Project Summary 10 Healthcare Spend vs Life Expectancy 12 Growth In Healthcare Data 17 Doctors with EHR and Multifunctional Health IT Capacity 30 Consumers Willing To Share Health Data 46 Future of Patient Data Data Breach Cost Per Capita 53 Number of Personalised Medicines (US - 2008 to 2016) 63 Genetic Disorders with Diagnostic Tests Available 65 Number of Artifical-Intelligence Companies -
Google's 'Project Nightingale' Gathers Personal Health Data on Millions Of
11/14/2019 Google’s ‘Project Nightingale’ Gathers Personal Health Data on Millions of Americans - WSJ MEMBER MESSAGE How would you ix college admissions? We want your suggestions on making the process more transparent and less stressful. Share Your Story This copy is for your personal, non-commercial use only. To order presentation-ready copies for distribution to your colleagues, clients or customers visit https://www.djreprints.com. https://www.wsj.com/articles/google-s-secret-project-nightingale-gathers-personal-health-data-on-millions-of-americans-11573496790 ◆ WSJ NEWS EXCLUSIVE | TECH Google’s ‘Project Nightingale’ Gathers Personal Health Data on Millions of Americans Search giant is amassing health records from Ascension facilities in 21 states; patients not yet informed Google launched the eort last year with Ascension, the country’s second-largest health system. PHOTO: DAVID PAUL MORRISBLOOMBERG NEWS By Rob Copeland Updated Nov. 11, 2019 427 pm ET Google is engaged with one of the U.S.’s largest health-care systems on a project to collect and crunch the detailed personal-health information of millions of people across 21 states. The initiative, code-named “Project Nightingale,” appears to be the biggest effort yet by a Silicon Valley giant to gain a toehold in the health-care industry through the handling of patients’ medical data. Amazon.com Inc., AMZN 0.08% ▲ Apple Inc. AAPL -0.69% ▲ and Microsoft https://www.wsj.com/articles/google-s-secret-project-nightingale-gathers-personal-health-data-on-millions-of-americans-11573496790 1/5 11/14/2019 Google’s ‘Project Nightingale’ Gathers Personal Health Data on Millions of Americans - WSJ Corp. -
THE DIGITAL HEALTH DEBATE Ci C
THE DIGITAL i C C NOV 2015 HEALTH DEBATE i A REPORT ON HOW DOCTORS ENGAGE WITH DIGITAL TECHNOLOGY IN THE WORKPLACE THE DIGITAL HEALTH DEBATE 2015 | ©CELLO HEALTH INSIGHT FOREWORD i C C i PAUL MANNU Master Practitioner, Behavioural Insights [email protected] Advances in digital technology have The research explores doctors’ perceptions Online interviews with become ubiquitous within healthcare, of how smart technology such as apps bringing about breakthroughs in diagnosis, and wearables can be used by patients to new treatment options and at the same better manage their health. time heralding the expansion of companies usually associated with technology into the The appendix section also includes our market place. findings on doctors’ preferences when 1,040 participating in research via a mobile app. certified doctors Enter Google Health, Apple Health, and Microsoft HealthVault. These major players Throughout this report, consideration has are accompanied by IBM with ‘Watson’, been given as to what the survey findings a new cognitive system that processes mean for pharmaceutical marketing information more like a human than a strategies. If you would like to know computer. IBM claim Watson will be able more about the specific relevance of this to ‘see’ medical images once its advanced research to marketing, sales and business image analytics and cognitive capabilities intelligence please get in touch. are merged with a newly acquired medical imaging management platform. For more information about the full extent of the survey research, please do not 8 The potential for these new and symbiotic hesitate to contact us. Markets relationships is vast and doctors are at the heart of it.