When up means down: why do so many video game players invert their controls?

The Guardian

Imagine you are playing a video game where you're looking out over an explorable world. You have a controller in your hand and you want your character to look or move upwards: in what direction do you push the joystick? If the answer is "up", you're in the majority – most players push up on a stick, or slide a mouse upwards, to instigate upward motion in a game. A significant minority of players start every new game they play by going into the options and selecting "Invert Y axis", which means when they push up on the stick, their onscreen avatar looks or moves downwards. To both sets of players, their own choice is logical and natural, and discussions about the subject can get quite fraught – as I found when I tweeted about it a few weeks ago.


How to watch all of Star Wars in order

USATODAY - Tech Top Stories

Purchases you make through our links may earn us a commission. It's an exciting time to be a Star Wars fan. New episodes of The Clone Wars are hitting Disney each week, The Rise of Skywalker arrives on digital March 17, and Lucasfilm just announced an entirely new era of Star Wars--The High Republic--that will explore the universe hundreds of years before the Skywalker saga takes place. There have never been more ways to get into Star Wars--an ever-expanding universe of mythic fantasy and rich spectacle. If you're feeling especially ambitious, check out the timeline of "canon" media on Wookieepedia for a fairly comprehensive overview of everything Star Wars has to offer: comic books, novels, video games.


r/MachineLearning - [N] Call for papers: QOD 2020 Workshop

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The 3rd Workshop on Quality of Open Data will be held in conjunction with BIS conference on June 8-10, 2020 in Colorado Springs, United States. The goal of QOD 2020 workshop is to bring together different communities working on quality in Wikipedia, DBpedia, Wikidata, OpenStreetMap, Wikimapia and other open knowledge bases and data sources. The workshop calls for sharing research experience and knowledge related to quality assessment in open data. We invite papers that provide methodologies and techniques, which can help to verify and enrich various community based services in different languages. Papers approved for presentation at QOD 2020 will be published as a volume in Springer's Lecture Notes in Business Information Processing (LNBIP) series.


r/MachineLearning - [D] Finding the right loss function for matching questions and answers in chat

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I am currently struggling with a NLP task, for which I am unable to find any real relevant literature or other source of information. A chat consists of N messages where each message is sent by either person1 or a person2. In this chat questions from person1 are answered by person2. My goal is to label the individual messages as either a question, answer, or neither. Additionally, I am also trying to find which messages that are labelled as question constitute 1 question and messages that are labelled as answer constitute 1 answer and which questions and answers belong together.


AAAI 2020 Best Papers; Turing Award Winners See a Turning Point for Deep Learning; MIT Reveals…

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A Generative Adversarial Network for AI-Aided Chair Design Researchers present a deep neural network for improving human design of chairs which consists of an image synthesis module and a super-resolution module. They select one of the candidates as a design prototype and create a real-life chair based on it. According to the researcher team, this is the first physical chair created with the help of deep neural networks, which bridges the gap between AI and design. This is the largest NLP model ever trained, with 17 billion parameters. T-NLG has achieved SOTA performance on mainstream NLP tasks.


How Chatbots Hold Power to Revolutionize the Finance Services?

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The days of waiting in a long queue to deposit some amount in your bank accounts are gone. The digitalization of the world has improved many concepts, including the ones from the banking and finance sectors. With the help of online banking, performing transactions has become quick and easier.


Network operators are stepping up investment on Artificial Intelligence

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A new study from Juniper Research has found that wireless and infrastructure network carriers spend on Artificial Intelligence (AI) solutions will exceed $15 billion by 2024. One factor fueling investment in AI and other digital transformation initiatives is the rise of over-the-top (OTT) applications that directly compete with the operators' traditional business. Voice and messaging services such as WhatsApp, Skype, Telegram, and WeChat in China have transformed the way most users communicate, making a dent in voice and SMS revenues. Juniper Research believes that "the lack of regulation in this sector has enabled the staggering rise of OTT messaging and voice services, making it attainable for players such as WhatsApp, Line, WeChat and others to maintain low pricing business models and fast-paced nature of offerings." "Digital transformation has significantly changed operators' business models, which only a decade ago relied predominantly on SMS, MMS and voice calls for revenues."


Knowledge Management joint with Subject Analysis and Access -- IFLA WLIC 2020

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Digital technologies of all its sorts have given rise to wider considerations and applications of Artificial Intelligence (AI) in library and information environments. In particular, the exponential growth of data, information and knowledge can no longer be managed by libraries, research centres and similar institutions via traditional means. AI operates via algorithms that restrict freedom of choice, changing the ways in which public users (externally) and library professionals and workers (internally) access resources. Historically, two important aspects of our profession have been to understand: a) the user's information needs and b) ways in which users interact with resources. AI-based solutions may assist or altogether replace manual procedures traditionally developed and performed by trained, educated professionals.


Data Science Curriculum for self-study - KDnuggets

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As a data science educator, many people interested in getting into data science have contacted me for guidance on how to get into the field of data science. This article will discuss the recommended topics that one has to study to build essential skills in data science. The topics presented here, if studied thoroughly, will provide the minimum background needed to start doing data science. This curriculum could also be used for designing an introductory college-level course in data science. Keep in mind that knowledge acquired from courses alone will not make you a data scientist.


Canada and UK pick winners in joint C$13.6M AI research competition

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Lancaster University, University of Essex and University of Alberta researchers will look at how AI can both lead to, and reduce, unintentional bias in job advertising and recruitment. The researchers will work with industrial partners to understand and mitigate gender and ethnic bias within human resource processes. Sheffield University and Simon Fraser University will use a cross-disciplinary approach to detect and counter abusive language online. The UK government is considering regulating social media platforms, requiring them to address abusive language and hate speech through content moderation. This project aims to develop AI methods to detect automatically and counter abuse and hate speech online.