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Distant Music An autoethnographic study of global songwriting in the digital age. SHEILA SIMMENES SUPERVISOR Michael Rauhut University of Agder, 2020 Faculty of Fine Arts Department of Popular music 2 Abstract This thesis aims to explore the path to music creation and shed a light on how we may maneuver songwriting and music production in the digital age. As a songwriter in 2020, my work varies from being in the same physical room using digital communication with collaborators from different cultures and sometimes even without ever meeting face to face with the person I'm making music with. In this thesis I explore some of the opportunities and challenges of this process and shine a light on tendencies and trends in the field. As an autoethnographic research project, this thesis offers an insight into the songwriting process and continuous development of techniques by myself as a songwriter in the digital age, working both commercially and artistically with international partners across the world. The thesis will aim to supplement knowledge on current working methods in songwriting and will hopefully shine a light on how one may improve as a songwriter and topliner in the international market. We will explore the tools and possibilities available to us, while also reflecting upon what challenges and complications one may encounter as a songwriter in the digital age. 3 4 Acknowledgements I wish to express my gratitude to my supervisor Michael Rauhut for his insight, expertise and continued support during this work; associate professor Per Elias Drabløs for his kind advice and feedback; and to my artistic supervisor Bjørn Ole Rasch for his enthusiasm and knowledge in the field of world music and international collaborations. -
European Practice for Overseas Attorneys
European Practice for Overseas Attorneys European patent law differs in some significant aspects from the law in other countries, in particular the United States. This note sets out some important features of European patent law to remember when preparing patent applications for Europe. For more detailed drafting tips, see our briefing note"Drafting Patents for Europe". Novelty Claiming priority According to European patent law, an invention is considered The European rules on claiming priority are in accordance new if it has not been made available to the public anywhere with the Paris Convention, so that priority can be claimed in the world before the priority date of the patent application. within one year of the first regular national filing in a An invention is "made available to the public" if knowledge Convention country. If a second priority application is filed of the claimed features of the invention was available to any and the European application is filed within one year of the person who was not under an obligation to keep the invention second but not the first application, priority is lost for matter confidential. which was in the first priority application, and it has the date of the European filing only. This most commonly occurs A novelty-destroying disclosure can be in any form, for when the second application is a Continuation-in-Part (CIP) example an oral description or a public display of the relevant application and can be very serious if there is a European features of the invention, as well as printed publications. (or PCT) application corresponding to the US parent, as this This means that public prior use of the invention anywhere in will be at least novelty-only prior art. -
Lecture Note on Deep Learning and Quantum Many-Body Computation
Lecture Note on Deep Learning and Quantum Many-Body Computation Jin-Guo Liu, Shuo-Hui Li, and Lei Wang∗ Institute of Physics, Chinese Academy of Sciences Beijing 100190, China November 23, 2018 Abstract This note introduces deep learning from a computa- tional quantum physicist’s perspective. The focus is on deep learning’s impacts to quantum many-body compu- tation, and vice versa. The latest version of the note is at http://wangleiphy.github.io/. Please send comments, suggestions and corrections to the email address in below. ∗ [email protected] CONTENTS 1 introduction2 2 discriminative learning4 2.1 Data Representation 4 2.2 Model: Artificial Neural Networks 6 2.3 Cost Function 9 2.4 Optimization 11 2.4.1 Back Propagation 11 2.4.2 Gradient Descend 13 2.5 Understanding, Visualization and Applications Beyond Classification 15 3 generative modeling 17 3.1 Unsupervised Probabilistic Modeling 17 3.2 Generative Model Zoo 18 3.2.1 Boltzmann Machines 19 3.2.2 Autoregressive Models 22 3.2.3 Normalizing Flow 23 3.2.4 Variational Autoencoders 25 3.2.5 Tensor Networks 28 3.2.6 Generative Adversarial Networks 29 3.3 Summary 32 4 applications to quantum many-body physics and more 33 4.1 Material and Chemistry Discoveries 33 4.2 Density Functional Theory 34 4.3 “Phase” Recognition 34 4.4 Variational Ansatz 34 4.5 Renormalization Group 35 4.6 Monte Carlo Update Proposals 36 4.7 Tensor Networks 37 4.8 Quantum Machine Leanring 38 4.9 Miscellaneous 38 5 hands on session 39 5.1 Computation Graph and Back Propagation 39 5.2 Deep Learning Libraries 41 5.3 Generative Modeling using Normalizing Flows 42 5.4 Restricted Boltzmann Machine for Image Restoration 43 5.5 Neural Network as a Quantum Wave Function Ansatz 43 6 challenges ahead 45 7 resources 46 BIBLIOGRAPHY 47 1 1 INTRODUCTION Deep Learning (DL) ⊂ Machine Learning (ML) ⊂ Artificial Intelli- gence (AI). -
AI Computer Wraps up 4-1 Victory Against Human Champion Nature Reports from Alphago's Victory in Seoul
The Go Files: AI computer wraps up 4-1 victory against human champion Nature reports from AlphaGo's victory in Seoul. Tanguy Chouard 15 March 2016 SEOUL, SOUTH KOREA Google DeepMind Lee Sedol, who has lost 4-1 to AlphaGo. Tanguy Chouard, an editor with Nature, saw Google-DeepMind’s AI system AlphaGo defeat a human professional for the first time last year at the ancient board game Go. This week, he is watching top professional Lee Sedol take on AlphaGo, in Seoul, for a $1 million prize. It’s all over at the Four Seasons Hotel in Seoul, where this morning AlphaGo wrapped up a 4-1 victory over Lee Sedol — incidentally, earning itself and its creators an honorary '9-dan professional' degree from the Korean Baduk Association. After winning the first three games, Google-DeepMind's computer looked impregnable. But the last two games may have revealed some weaknesses in its makeup. Game four totally changed the Go world’s view on AlphaGo’s dominance because it made it clear that the computer can 'bug' — or at least play very poor moves when on the losing side. It was obvious that Lee felt under much less pressure than in game three. And he adopted a different style, one based on taking large amounts of territory early on rather than immediately going for ‘street fighting’ such as making threats to capture stones. This style – called ‘amashi’ – seems to have paid off, because on move 78, Lee produced a play that somehow slipped under AlphaGo’s radar. David Silver, a scientist at DeepMind who's been leading the development of AlphaGo, said the program estimated its probability as 1 in 10,000. -
Accelerators and Obstacles to Emerging ML-Enabled Research Fields
Life at the edge: accelerators and obstacles to emerging ML-enabled research fields Soukayna Mouatadid Steve Easterbrook Department of Computer Science Department of Computer Science University of Toronto University of Toronto [email protected] [email protected] Abstract Machine learning is transforming several scientific disciplines, and has resulted in the emergence of new interdisciplinary data-driven research fields. Surveys of such emerging fields often highlight how machine learning can accelerate scientific discovery. However, a less discussed question is how connections between the parent fields develop and how the emerging interdisciplinary research evolves. This study attempts to answer this question by exploring the interactions between ma- chine learning research and traditional scientific disciplines. We examine different examples of such emerging fields, to identify the obstacles and accelerators that influence interdisciplinary collaborations between the parent fields. 1 Introduction In recent decades, several scientific research fields have experienced a deluge of data, which is impacting the way science is conducted. Fields such as neuroscience, psychology or social sciences are being reshaped by the advances in machine learning (ML) and the data processing technologies it provides. In some cases, new research fields have emerged at the intersection of machine learning and more traditional research disciplines. This is the case for example, for bioinformatics, born from collaborations between biologists and computer scientists in the mid-80s [1], which is now considered a well-established field with an active community, specialized conferences, university departments and research groups. How do these transformations take place? Do they follow similar paths? If yes, how can the advances in such interdisciplinary fields be accelerated? Researchers in the philosophy of science have long been interested in these questions. -
The Deep Learning Revolution and Its Implications for Computer Architecture and Chip Design
The Deep Learning Revolution and Its Implications for Computer Architecture and Chip Design Jeffrey Dean Google Research [email protected] Abstract The past decade has seen a remarkable series of advances in machine learning, and in particular deep learning approaches based on artificial neural networks, to improve our abilities to build more accurate systems across a broad range of areas, including computer vision, speech recognition, language translation, and natural language understanding tasks. This paper is a companion paper to a keynote talk at the 2020 International Solid-State Circuits Conference (ISSCC) discussing some of the advances in machine learning, and their implications on the kinds of computational devices we need to build, especially in the post-Moore’s Law-era. It also discusses some of the ways that machine learning may also be able to help with some aspects of the circuit design process. Finally, it provides a sketch of at least one interesting direction towards much larger-scale multi-task models that are sparsely activated and employ much more dynamic, example- and task-based routing than the machine learning models of today. Introduction The past decade has seen a remarkable series of advances in machine learning (ML), and in particular deep learning approaches based on artificial neural networks, to improve our abilities to build more accurate systems across a broad range of areas [LeCun et al. 2015]. Major areas of significant advances include computer vision [Krizhevsky et al. 2012, Szegedy et al. 2015, He et al. 2016, Real et al. 2017, Tan and Le 2019], speech recognition [Hinton et al. -
VIRAL ART Exhibition Guide
VIRAL ART Exhibition Guide VIRAL ART is an exhibition focusing on this last year and the universal pandemic (COVID-19) which has affected many different aspects of life, one of which is evident in the artistic world. COVID-19 has forced many artists to open up to new avenues of expression in many different disciplines; visual art, music, performing arts, photography, fashion, and literature. Some of the main goals for our exhibition are to bring light to how the pandemic has affected all corners of life, especially in regard to artistic capability/expression, and further, illustrate how certain artists captured the essence and experience of COVID-19. Introduction by Taylor Weaver I wanted to start by saying how grateful I am to have been able to lead this exhibition project with the help of Mirea Suarez. I am so proud of each and every one of the girls and hope you can see how hard they have all worked to make this possible. So welcome to our exhibition which we have titled Viral Art! I would like to note that some of the pieces, such as music are slightly more interactive, for example one of the music pieces is a live DJ set and is an hour and a half in total in the event you are interested in watching more – we will only briefly show certain pieces We would like to preface this exhibition by giving a small dedication to those whose lives have been affected by COVID-19. We thought it would be most appropriate to say a few words to front line workers such as those in the healthcare industry who have dedicated their lives to fighting this virus, essential workers such as those in the food (and or) agriculture industry who prepared meals for those in need during these stressful times, Research Methods Fall 2020 Taylor Weaver, Mirea Suarez, Cristina Ponce de Leon, Sophie Schaesberg, Sydney Levno, Annamaria Borvice, Marta Belogolova VIRAL ART Exhibition Guide volunteers, and of course, to all who lost their lives to COVID-19 or people who have lost family members. -
The Power and Promise of Computers That Learn by Example
Machine learning: the power and promise of computers that learn by example MACHINE LEARNING: THE POWER AND PROMISE OF COMPUTERS THAT LEARN BY EXAMPLE 1 Machine learning: the power and promise of computers that learn by example Issued: April 2017 DES4702 ISBN: 978-1-78252-259-1 The text of this work is licensed under the terms of the Creative Commons Attribution License which permits unrestricted use, provided the original author and source are credited. The license is available at: creativecommons.org/licenses/by/4.0 Images are not covered by this license. This report can be viewed online at royalsociety.org/machine-learning Cover image © shulz. 2 MACHINE LEARNING: THE POWER AND PROMISE OF COMPUTERS THAT LEARN BY EXAMPLE Contents Executive summary 5 Recommendations 8 Chapter one – Machine learning 15 1.1 Systems that learn from data 16 1.2 The Royal Society’s machine learning project 18 1.3 What is machine learning? 19 1.4 Machine learning in daily life 21 1.5 Machine learning, statistics, data science, robotics, and AI 24 1.6 Origins and evolution of machine learning 25 1.7 Canonical problems in machine learning 29 Chapter two – Emerging applications of machine learning 33 2.1 Potential near-term applications in the public and private sectors 34 2.2 Machine learning in research 41 2.3 Increasing the UK’s absorptive capacity for machine learning 45 Chapter three – Extracting value from data 47 3.1 Machine learning helps extract value from ‘big data’ 48 3.2 Creating a data environment to support machine learning 49 3.3 Extending the lifecycle -
Television Advertising Insights
Lockdown Highlight Tous en cuisine, M6 (France) Foreword We are delighted to present you this 27th edition of trends and to the forecasts for the years to come. TV Key Facts. All this information and more can be found on our This edition collates insights and statistics from dedi cated TV Key Facts platform www.tvkeyfacts.com. experts throughout the global Total Video industry. Use the link below to start your journey into the In this unprecedented year, we have experienced media advertising landscape. more than ever how creative, unitive, and resilient Enjoy! / TV can be. We are particularly thankful to all participants and major industry players who agreed to share their vision of media and advertising’s future especially Editors-in-chief & Communications. during these chaotic times. Carine Jean-Jean Alongside this magazine, you get exclusive access to Coraline Sainte-Beuve our database that covers 26 countries worldwide. This country-by-country analysis comprises insights for both television and digital, which details both domestic and international channels on numerous platforms. Over the course of the magazine, we hope to inform you about the pandemic’s impact on the market, where the market is heading, media’s social and environmental responsibility and all the latest innovations. Allow us to be your guide to this year’s ACCESS OUR EXCLUSIVE DATABASE ON WWW.TVKEYFACTS.COM WITH YOUR PERSONAL ACTIVATION CODE 26 countries covered. Television & Digital insights: consumption, content, adspend. Australia, Austria, Belgium, Brazil, Canada, China, Croatia, Denmark, France, Finland, Germany, Hungary, India, Italy, Ireland, Japan, Luxembourg, The Netherlands, Norway, Poland, Russia, Spain, Sweden, Switzerland, UK and the US. -
A Mission Impossible? an Assessment of the Historical and Current Approaches Mauricio Troncoso
Marquette Intellectual Property Law Review Volume 17 | Issue 2 Article 3 International Intellectual Property Scholars Series: European Union Patents: A Mission Impossible? An Assessment of the Historical and Current Approaches Mauricio Troncoso Follow this and additional works at: http://scholarship.law.marquette.edu/iplr Part of the Intellectual Property Commons Repository Citation Mauricio Troncoso, International Intellectual Property Scholars Series: European Union Patents: A Mission Impossible? An Assessment of the Historical and Current Approaches, 17 Intellectual Property L. Rev. 231 (2013). Available at: http://scholarship.law.marquette.edu/iplr/vol17/iss2/3 This International Intellectual Property Scholars Series is brought to you for free and open access by the Journals at Marquette Law Scholarly Commons. It has been accepted for inclusion in Marquette Intellectual Property Law Review by an authorized administrator of Marquette Law Scholarly Commons. For more information, please contact [email protected]. TRONCOSO FORMATTED FINAL (DO NOT DELETE) 5/24/2013 1:09 PM INTERNATIONAL INTELLECTUAL PROPERTY SCHOLARS SERIES* EUROPEAN UNION PATENTS: A MISSION IMPOSSIBLE? AN ASSESSMENT OF THE 1 HISTORICAL AND CURRENT APPROACHES MAURICIO TRONCOSO** I. INTRODUCTION .......................................................................................... 233 II. THE FIRST APPROACHES ........................................................................... 233 A. Original Design ............................................................................ -
The European Patent Convention, 3 Md
Maryland Journal of International Law Volume 3 | Issue 2 Article 10 The urE opean Patent Convention Follow this and additional works at: http://digitalcommons.law.umaryland.edu/mjil Part of the International Law Commons, and the International Trade Commons Recommended Citation The European Patent Convention, 3 Md. J. Int'l L. 408 (1978). Available at: http://digitalcommons.law.umaryland.edu/mjil/vol3/iss2/10 This Notes & Comments is brought to you for free and open access by DigitalCommons@UM Carey Law. It has been accepted for inclusion in Maryland Journal of International Law by an authorized administrator of DigitalCommons@UM Carey Law. For more information, please contact [email protected]. THE EUROPEAN PATENT CONVENTION The European Patent Convention' (EPC) is an attempt to simplify European patent law. The Convention provides a procedure for securing a single, European patent,2 which has the effect of a national patent in the signatory nations designated in the application. Through this alternative to national procedures, widespread patent coverage should be easier to obtain. Require- patent, however, are rigorous and its ments for a European 3 attraction is primarily the consolidation of the grant procedures. The EPC establishes several organs to handle the various aspects of the patent application procedure. The European Patent Office (EPO), located in Munich, is the international equivalent of a national patent office. Its administrative divisions are the General Search Division, the Examining Division, and the Opposition Division. The Receiving Section is at The Hague. The first procedural step is the filing of an application at either a national patent office or directly with the EPO.4 The application may be in any of the three official languages (English, French, or German) and the applicant's choice becomes the language of the proceedings.5 The Receiving Section subjects the application to both a preliminary6 and a supplementary formal examination to determine whether it is in proper form and all fees are paid. -
Understanding the Unified Patent Court: the Next Rocket-Docket for Patent Owners?
ABA Section of Intellectual Property Law Landslide Magazine March/April 2016 Understanding the Unified Patent Court: The Next Rocket-Docket for Patent Owners? By Kevin R. Greenleaf, Michael W. O’Neill, and Aloys Hüettermann Kevin R. Greenleaf is a counsel at Dentons US LLP where he specializes in PTAB post-grant proceedings. He can be reached at [email protected]. Michael W. O’Neill is of counsel at Dentons US LLP in Washington, DC, and a former Administrative Patent Judge from the United States Patent and Trademark Office. He specializes in PTAB post-grant proceedings. He can be reached at [email protected]. Dr. Aloys Hüttermann is a German and European patent and trademark attorney and a partner at Michalski Hüttermann & Partner. He specializes in chemistry, bioorganic chemistry, and pharma, and can be reached at [email protected]. Much like Americans, Europeans are revising their patent laws to include a new litigation-style proceed- ing to determine patent validity and infringement. These proceedings will take place in the Unified Patent Court (UPC), which will be installed together with the unitary patent (UP), the latter allowing a single patent for nearly all of Europe. Such a revision will be the greatest change in European patent law since the establishment of the European Patent Office (EPO) in the 1970s. American patent practition- ers need to understand how the new UPC will operate. Europeans can learn from the American experi- ence of establishing the Patent Trial and Appeal Board (PTAB) at the United States Patent and Trademark Office (USPTO). The upcoming UPC is based on an international treaty; however, only European Union (EU) member states can join.