ELO 2021 - Abstracts
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Procedural Content Generation for Games
Procedural Content Generation for Games Inauguraldissertation zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften der Universit¨atMannheim vorgelegt von M.Sc. Jonas Freiknecht aus Hannover Mannheim, 2020 Dekan: Dr. Bernd L¨ubcke, Universit¨atMannheim Referent: Prof. Dr. Wolfgang Effelsberg, Universit¨atMannheim Korreferent: Prof. Dr. Colin Atkinson, Universit¨atMannheim Tag der m¨undlichen Pr¨ufung: 12. Februar 2021 Danksagungen Nach einer solchen Arbeit ist es nicht leicht, alle Menschen aufzuz¨ahlen,die mich direkt oder indirekt unterst¨utzthaben. Ich versuche es dennoch. Allen voran m¨ochte ich meinem Doktorvater Prof. Wolfgang Effelsberg danken, der mir - ohne mich vorher als Master-Studenten gekannt zu haben - die Promotion an seinem Lehrstuhl erm¨oglichte und mit Geduld, Empathie und nicht zuletzt einem mir unbegreiflichen Verst¨andnisf¨ur meine verschiedenen Ausfl¨ugein die Weiten der Informatik unterst¨utzthat. Sie werden mir nicht glauben, wie dankbar ich Ihnen bin. Weiterhin m¨ochte ich meinem damaligen Studiengangsleiter Herrn Prof. Heinz J¨urgen M¨ullerdanken, der vor acht Jahren den Kontakt zur Universit¨atMannheim herstellte und mich ¨uberhaupt erst in die richtige Richtung wies, um mein Promotionsvorhaben anzugehen. Auch Herr Prof. Peter Henning soll nicht ungenannt bleiben, der mich - auch wenn es ihm vielleicht gar nicht bewusst ist - davon ¨uberzeugt hat, dass die Erzeugung virtueller Welten ein lohnenswertes Promotionsthema ist. Ganz besonderer Dank gilt meiner Frau Sarah und meinen beiden Kindern Justus und Elisa, die viele Abende und Wochenenden zugunsten dieser Arbeit auf meine Gesellschaft verzichten mussten. Jetzt ist es geschafft, das n¨achste Projekt ist dann wohl der Garten! Ebenfalls geb¨uhrt meinen Eltern und meinen Geschwistern Dank. -
Innk: a Multi-Player Game to Deceive a Neural Network
iNNk: A Multi-Player Game to Deceive a Neural Network Jennifer Villareale1, Ana Acosta-Ruiz1, Samuel Arcaro1, Thomas Fox1, Evan Freed1, Robert Gray1, Mathias Löwe2, Panote Nuchprayoon1, Aleksanteri Sladek1, Rush Weigelt1, Yifu Li1, Sebastian Risi2, Jichen Zhu1 1Drexel University, Philadelphia, USA 2IT University of Copenhagen, Copenhagen, Denmark {jmv85, ava48, saa35, tbf33, emf67, rcg48, pn355, ams939, rw643, yl3374, jichen}@drexel.edu, {malw, sebr}@itu.dk ABSTRACT experiment with different drawing strategies. This paper also sum- This paper presents iNNK, a multiplayer drawing game where hu- marizes the main strategies our players have developed in our man players team up against an NN. The players need to success- playtesting. Certainly, a lot more effort is needed to empower cit- fully communicate a secret code word to each other through draw- izens to be more familiar with AI and to engage the technology ings, without being deciphered by the NN. With this game, we aim critically. Through our game, we have seen evidence that playful to foster a playful environment where players can, in a small way, experience can turn people from passive users into creative and re- go from passive consumers of NN applications to creative thinkers flective thinkers, a crucial step towards a more mature relationship and critical challengers. with AI. CCS CONCEPTS 2 RELATED WORK • Computer systems organization ! Embedded systems; Re- With recent breakthroughs in neural networks (NN), particularly dundancy; Robotics; • Networks ! Network reliability. deep learning, designers are increasingly exploring their use in computer games. For example, researchers use NNs to procedurally KEYWORDS generate game content, which otherwise would have to be created artificial intelligence, game design, machine learning, neural net- by human artists and thus make the game more variable [13, 20]. -
Plagiarism in the Age of Massive Generative Pre-Trained Transformers (GPT- 3): “The Best Time to Act Was Yesterday
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/348583797 Plagiarism in the age of massive Generative Pre-trained Transformers (GPT- 3): “The best time to act was yesterday. The next best time is now.” Article in Ethics in Science and Environmental Politics · January 2021 DOI: 10.3354/esep00195 CITATIONS READS 0 26 1 author: Nassim Dehouche Mahidol University 30 PUBLICATIONS 9 CITATIONS SEE PROFILE Some of the authors of this publication are also working on these related projects: Improving Access to the Bangkok Transit System for Older Adults and Disabled People View project Operational Research on Football View project All content following this page was uploaded by Nassim Dehouche on 13 February 2021. The user has requested enhancement of the downloaded file. Plagiarism in the age of massive Generative Pre-trained Transformers (GPT-3): “The best time to act was yesterday. The next best time is now.” Nassim Dehouche [email protected] Business Administration Division, Mahidol University International College, Salaya, Thailand Abstract As if 2020 were not a peculiar enough year, its fifth month has seen the relatively quiet publication of a preprint describing the most powerful Natural Language Processing (NLP) system to date, GPT-3 (Generative Pre-trained Transformer-3), by Silicon Valley research firm OpenAI. Though the software implementation of GPT-3 is still in its initial Beta release phase, and its full capabilities are still unknown as of the time of this writing, it has been shown that this Artificial Intelligence can comprehend prompts in natural language, on virtually any topic, and generate relevant, original text content that is indistinguishable from human writing. -
Arxiv:2007.12391V6 [Cs.CV] 2 Jul 2021 Techniques for Practical Purposes Has Been Artificial Intelligence (AI)
Artificial Intelligence Review manuscript No. (will be inserted by the editor) Artificial Intelligence in the Creative Industries: A Review Nantheera Anantrasirichai · David Bull Accepted for publication in Artificial Intelligence Review (AIRE), 19 June 2021 Abstract This paper reviews the current state of the art in Artificial Intelligence (AI) tech- nologies and applications in the context of the creative industries. A brief background of AI, and specifically Machine Learning (ML) algorithms, is provided including Convolu- tional Neural Networks (CNNs), Generative Adversarial Networks (GANs), Recurrent Neu- ral Networks (RNNs) and Deep Reinforcement Learning (DRL). We categorize creative applications into five groups, related to how AI technologies are used: i) content creation, ii) information analysis, iii) content enhancement and post production workflows, iv) in- formation extraction and enhancement, and v) data compression. We critically examine the successes and limitations of this rapidly advancing technology in each of these areas. We further differentiate between the use of AI as a creative tool and its potential as a creator in its own right. We foresee that, in the near future, ML-based AI will be adopted widely as a tool or collaborative assistant for creativity. In contrast, we observe that the successes of ML in domains with fewer constraints, where AI is the ‘creator’, remain modest. The potential of AI (or its developers) to win awards for its original creations in competition with human creatives is also limited, based on contemporary technologies. We therefore conclude that, in the context of creative industries, maximum benefit from AI will be derived where its focus is human-centric – where it is designed to augment, rather than replace, human creativity. -
The Future of Storytelling in the Age of AI and Posthuman
The Future of Storytelling in the Age of AI and Posthuman DR. SERDAR TUNCER PROF. BOULOU EBANDA DE B'BÉRI UNIVERSITY OF OTTAWA, AMLAC&S Background Computer scientists are building a vast array of machine learning systems (often called Artificial Intelligence or AI) that can perform daily human tasks reliably, sometimes more so than humans. Indeed, AI is becoming capable of capturing the unique essence that makes us “human”: storytelling. Humans are intrinsically storytellers who express themselves through stories that already exist (Fisher, 1987; Frank, 2012). Moreover, people have always learnt about themselves and made sense of the rest of the world through narratives (Ebanda de B'béri, 2006; Tunçer, 2018). However, in recent years, AI-generated games and articles have already started to emerge (Fitch, 2019). While AI is able to exceed certain functions of natural human intelligence as it gains self- learning capacity in repetitive or analytical tasks, it may have the potential to harness the persuasive capabilities of storytelling. Guiding Questions • What will become of our humanity if AI can write and tell better stories? • Is AI the greatest danger to our humanity as Bramer (2015) has suggested? • Are we already entered the posthuman era (Wolfe, 2010; Braidotti, 2013) with such advances as neural nets that allow biological and silicon-based artificial brain cells to communicate with each other (Serb et al., 2020) – a new form of AI-human being? • What will the future look like if AI can harness the influential potential of storytelling? • What would be the storytelling landscape in such an environment of posthuman? Where we are today We are still in the infant stages of AI with errors happening along the way: ◦ Microsoft had released its AI bot named Tay, which was designed to foster “conversational understanding.” But things did not go as expected. -
Gestalt Manager 1
CHAPTER 1 Gestalt Manager 1 This chapter describes how you can use the Gestalt Manager and other system software facilities to investigate the operating environment. You need to know about the 1 operating environment if your application takes advantage of hardware (such as a Gestalt Manager floating-point unit) or software (such as Color QuickDraw) that is not available on all Macintosh computers. You can also use the Gestalt Manager to inform the Operating System that your software is present and to find out about other software registered with the Gestalt Manager. The Gestalt Manager is available in system software versions 6.0.4 and later. The MPW software development system and some other development environments supply code that allows you to use the Gestalt Manager on earlier system software versions; check the documentation provided with your development system. In system software versions earlier than 6.0.4, you can retrieve a limited description of the operating environment with the SysEnvirons function, also described in this chapter. You need to read this chapter if you take advantage of specific hardware or software features that may not be present on all versions of the Macintosh, or if you wish to inform other software that your software is present in the operating environment. This chapter describes how the Gestalt Manager works and then explains how you can ■ determine whether the Gestalt Manager is available ■ call the Gestalt function to investigate the operating environment ■ make information about your own hardware or software available to other applications ■ retrieve a limited description of the operating environment even if the Gestalt Manager is not available About the Gestalt Manager 1 The Macintosh family of computers includes models that use a number of different processors, some accompanied by a floating-point unit (FPU) or memory management unit (MMU). -
The Hitchhiker's Guide to Technology
The Hitchhiker’s Guide to Technology: A Conversation on Careers in Tech Falaah Arif Khan Email: [email protected] Website: https://falaaharifkhan.github.io/research/ Twitter: @FalaahArifKhan Agenda ❏ The Hacker Mindset: How I pulled off 5 Hackathon wins in 1 year ❏ AI Now: A Critical Overview of Social and Technical challenges ❏ Creativity and Computer Science: Why I created a Scientific Comic about Artificial Intelligence ❏ Alice Through the Looking Glass: What I’ve learned about the IT Industry The Hacker Mindset: My experience May ‘18: Graduated college July ‘18: Joined Dell Sept ‘18: Invoice Correction --- Order Management Dec ‘18: Credit Limit Allocation --- Credit/Finance April ‘19: Network Security ---- Cyber security June ‘19: Ethical Hack of Source code ----- Dev/Ops July ‘19: Content Classification----- Marketing The Hacker Mindset: Hackathon Lessons 1. Develop business acumen: a. understand the business end to end b. gain experience with building different components of a software product/service 2. Develop design thinking and product management skills: a. Understand your client b. MVP (Minimum viable product+iterate) mindset 3. Work in a high pressure environment 4. Gain familiarity with all stages of SDLC (Software Development Lifecycle) The Hacker Mindset: Key Takeaways ❏ Take on challenging problems. Learn to work under constraints ❏ Take on things you don't know and figure it out as you go ❏ Take risks, follow your intuitions ❏ Challenge the tradition/ status quo ❏ Collaborate, build something bigger than yourself Questions? -
Future of Text Book 2020 PDF.Indd
THE FUTURE OF TEXT Edited by Frode Alexander Hegland First Published 2020. All articles are © Copyright of their respective authors. This collected work is © Copyright ‘Future Text Publishing’ and Frode Alexander Hegland. The PDF edition of this work is made available at no cost and the printed book is available from ‘Future Text Publishing’ (futuretextpublishing.com) a trading name of ‘The Liquid Information Company’. This work is freely available digitally, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited. Typeset in Adobe Caslon Pro and Shinglewoode by Timothy Donaldson except for the Kindle version. ISBN: 9798556866782 DOI: future text publishing HOW TO READ THIS BOOK IN READER If you are reading this book in the Augmented Text Tool ‘Reader’ on macOS, which was developed to demonstrate some of the editor’s ideas about interactive text, you can interact with the text in experimental ways: • Copy As Citation: Copy and paste text into a visual-meta aware word processor, such as Author (see the ‘Visual-Meta’ section in this book) and it will paste as a full citation. This includes fields for both author and editor. -
AUSOM News November 2015
AUSOM (established in 1980) Supports Users of Apple Products November 2015 Volume 36, No. 10 AUSOM Recommended retail price $9.00 Print Post Publication No. 339944/00003 ISSN 1329-2641 Reg. No. A0005646X AUSOM News is a publication of AppleN Users' Societyews of Melbourne … Australia's leading Apple User Group AUSOM Incorporated … www.ausom.net.au November 2015 November FC B B S AUSOM Incorporated ABN 63 929 877 630 Contact AUSOM Reg.No: A0005646X Snail Mail to virtual office: 247 Flinders Lane, Melb. 3000 Phone between 9 am and 9 pm only, please, unless other Phone: Mobile: 0421 126 175 times shown. e-mail: [email protected] (e-mail will be forwarded as appropriate) Office AUSOM 0421 126 175 Website: http://www.ausom.net.au Committee of Management Twitter: http://twitter.com/ausominc President: Philip Richardson [email protected] AUSOM News submissions Editor: Pam Doughty Vice President: Ngaire Denne [email protected] Post: Editor, 247 Flinders Lane, Melbourne 3000 Secretary: Isabel Colins [email protected] e-mail: [email protected] Treasurer: Julie Ackland [email protected] Send letters & editorial material to the Editor post or e-mail Peter Carter [email protected] deadline 1st Saturday of month prior to publication month. Douglas Rutter [email protected] NOTE: There is no AUSOM News in January Steve Stretton [email protected] ©Copyright: Articles in AUSOM News are Copyright© by AUSOM Marion Egerton [email protected] Inc, unless otherwise specified, and may be reprinted by non-profit organisations provided credit is given to the source and a copy of the Assistant Volunteers' Co-ordinator publication containing the article is sent to AUSOM Inc. -
HISTORY of APPLE[Tm] MACINTOSH[Tm] OPERATING SYSTEM
HISTORY OF APPLE[tm] MACINTOSH[tm] OPERATING SYSTEM LisaDesk : released, on January 1983, for Apple Lisa computer. On January 1985, Lisa 2-10, outfitted with MacWorks, was renamed Macintoh XL. System 1 (1.0 and 1.1) : released respectively on January 1984 and May 1984, both versions were directly derived from LisaDesk offered less functionality, in favor of being more stable. Certain functions of LisaDesk were included in later versions of Mac[tm] OS, including Mac[tm] OS X. System 2 (1.2 to 2.1) : while integrating new functions, the principal objective of this system was to allow a better management to compensate for the absence of a hard disk on first models of Macintosh. System 3 (2.2 to 3.3) : this system accompanied, on 1986, the new Macintosh models. This system had more facility and was more powerful, it allowed the integration of new file format HFS, of new communications functionality, and laser printer support. System 4 & 5 (4.0 to 5.1) : these systems accompanied the first Macintosh models with colour monitors, and allowed transition between mono-task system and cooperative multi-task system with first generation of Multifinder which made possible to manage several applications simultaneously. System 6 (6.0 to 6.0.8) : improvements to the cooperative multi-task system with second generation of Multifinder. It was released in many specialized versions according to the model which was equipped to meet specific needs, particularly for graphic applications. System 7 (7.0 to 7.6.1) : complete integration of cooperative multi-task processing inside the system, this system gradually integrated increasingly significant functionality concerning multimedia applications and Internet. -
About This Particular Macintosh 6.02
Cover ATPM About This Particular Macintosh™ 6.02: About the personal computing experience™ Volume 6, Number 2 February 1, 2000 Sign up for free subscriptions at: http://www.atpm.com/subscribe or send email to: [email protected] ATPM 6.02 ←→1 Cover Cover Art Copyright © 2000 David Knopfler david@knopfler.com http://www.dkdesigns.co.uk We need new cover art every month! Write to us! Contributors Eric Blair Daniel Chvatik Paul Fatula Scott Feldstein Edward Goss Tom Iov ino Robert Paul Leitao William Lovett Jamie McCornack Grant Osborne David Ozab Mike Shields Brooke Smith David Spencer Evan Trent Michael Tsai Christopher Turner Macintosh users like you Please write for ATPM! Check out the FAQ. ATPM 6.02 ←→2 Cover Editorial Staff Publisher/Editor-in-Chief - Michael Tsai Managing Editor - Daniel Chvatik Associate Editor/Reviews - Paul Fatula Associate Editor/Shareware Reviews - William Lovett Copy Editors - Raena Armitage Paul Fatula Brooke Smith Va c a nt Publicity Manager - Christopher Turner Contributing Editor/Welcome - Robert Paul Leitao Contributing Editors/Opinion - Tom Iovino Scott Feldstein Contributing Editors/Reviews - Eric Blair Evan Trent Va c a nt Contributing Editor/How To’s & Reviews - Jamie McCornack Contributing Editor/Trivia - Edward Goss Contibuting Editor/Music - David Ozab Contributing Editor/Networking - Matthew Glidden Contributing Editor/Web - David Spencer Help Jedi - Christopher Turner Hollywood Guy - Mike Shields Webmaster - Michael Tsai CGI Wizard - Evan Trent Assistant Webmaster - Va c a nt Interviews Managers -
An Exploration of Member Involvement with Online Brand Communities (Obcs)
AN EXLORATION OF MEMBER INVOLVEMENT WITH ONLINE BRAND COMMUNITIES (OBCs) by Mary Loonam A thesis submitted to the University of Birmingham for the degree of DOCTOR OF PHILOSOPHY Department of Marketing Birmingham Business School College of Social Sciences University of Birmingham October 2017 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT Despite growth in research investigating online consumer behaviour there appears to be a lack of study focusing specifically on how consumers are involved within online settings. Involvement is defined as the perceived relevance of a stimulus object such as a product to the individual consumer (Zaichkowsky, 1984). The study of consumer involvement is valuable as it is believed to be important mediator of consumer behaviour in the extant literature (e.g. Slater and Armstrong, 2010; Knox, Walker and Marshall, 1994). Involvement is thought to consist of two forms namely enduring involvement and situational involvement which respectively denote long-term and temporary interest in the stimulus object (Houston and Rothschild, 1978). Components such as personal interest, sign value, hedonic value and perceived risk have been conceptualised as evoking involvement (Kapferer and Laurent, 1993).