Search (190 results, page 3 of 10)

  • × year_i:[2020 TO 2030}
  1. Dagher, I.; Soufi, D.: Authority control of Arabic psonal names : RDA and beyond (2021) 0.01 
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  2. Peters, I.: Folksonomies & Social Tagging (2023) 0.01 
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  3. Eibl, M.; Haupt, J.; Kahl, S.; Taubert, S.; Wilhelm-Stein, T.: Audio- und Musik-Retrieval (2023) 0.01 
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    Abstract
    Das Gebiet Audio-Retrieval kann grob in drei Bereiche unterteilt werden: Musik-Retrieval, Retrieval gesprochener Sprache und Retrieval akustischer Ereignisse. Alle drei Bereiche gehen i. d. R. vom Audiosignal als Quelle aus, welches über eine Signalanalyse, meist eine Spektralanalyse über eine Fouriertransformation, weiterverarbeitet und in eine für das Retrieval geeignete Beschreibung gebracht wird. Dabei gibt es auch alternative Ansätze, wie z. B. die Nutzung der hier nicht diskutierten MIDI-Codierung im Musik-Retrieval, die ohne ein akustisches Signal auskommt und bereits eine für das Retrieval geeignete Form der Kodierung als Grundlage hat.
  4. Matt, A.; Schaber, E.; Violet, B.: Vielfältige Formate und dynamische Umsetzung : Mathematik-Kommunikation zu Künstlicher Intelligenz bei IMAGINARY (2023) 0.01 
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    Abstract
    IMAGINARY verfügt über eine große Spannbreite und eine Vielzahl an Ressourcen im Bereich der Mathematik- und Wissenschaftskommunikation. In diesem Artikel werden Formate zum Thema Künstliche Intelligenz (KI) für Zielgruppen mit unterschiedlichem Vor- und Fachwissen vorgestellt. Zwei grundlegende Themen, die eine wichtige Rolle im Maschinellen Lernen bilden, stehen dabei im Vordergrund: Neuronale Netze und Reinforcement Learning. IMAGINARY vermittelt diese beiden Schwerpunkte auf vielfältige Weise. Dieser Beitrag stellt einige der verwendeten Formate vor: Von interaktiven Exponaten in der Ausstellung "I AM A.I." zu "Explorables" in digitalen Programmen, über Online-Kurse auf Lernplattformen bis hin zu Workshops für Schüler*innen oder Mathematiklehrkräfte.
  5. Jha, A.: Why GPT-4 isn't all it's cracked up to be (2023) 0.01 
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    Abstract
    "I still don't know what to think about GPT-4, the new large language model (LLM) from OpenAI. On the one hand it is a remarkable product that easily passes the Turing test. If you ask it questions, via the ChatGPT interface, GPT-4 can easily produce fluid sentences largely indistinguishable from those a person might write. But on the other hand, amid the exceptional levels of hype and anticipation, it's hard to know where GPT-4 and other LLMs truly fit in the larger project of making machines intelligent.
    They might appear intelligent, but LLMs are nothing of the sort. They don't understand the meanings of the words they are using, nor the concepts expressed within the sentences they create. When asked how to bring a cow back to life, earlier versions of ChatGPT, for example, which ran on a souped-up version of GPT-3, would confidently provide a list of instructions. So-called hallucinations like this happen because language models have no concept of what a "cow" is or that "death" is a non-reversible state of being. LLMs do not have minds that can think about objects in the world and how they relate to each other. All they "know" is how likely it is that some sets of words will follow other sets of words, having calculated those probabilities from their training data. To make sense of all this, I spoke with Gary Marcus, an emeritus professor of psychology and neural science at New York University, for "Babbage", our science and technology podcast. Last year, as the world was transfixed by the sudden appearance of ChatGPT, he made some fascinating predictions about GPT-4.
    People use symbols to think about the world: if I say the words "cat", "house" or "aeroplane", you know instantly what I mean. Symbols can also be used to describe the way things are behaving (running, falling, flying) or they can represent how things should behave in relation to each other (a "+" means add the numbers before and after). Symbolic AI is a way to embed this human knowledge and reasoning into computer systems. Though the idea has been around for decades, it fell by the wayside a few years ago as deep learning-buoyed by the sudden easy availability of lots of training data and cheap computing power-became more fashionable. In the near future at least, there's no doubt people will find LLMs useful. But whether they represent a critical step on the path towards AGI, or rather just an intriguing detour, remains to be seen."
  6. Adler, M.: ¬The strangeness of subject cataloging : afterword (2020) 0.01 
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    Abstract
    "I can't presume to know how other catalogers view the systems, information resources, and institutions with which they engage on a daily basis. David Paton gives us a glimpse in this issue of the affective experiences of bibliographers and catalogers of artists' books in South Africa, and it is clear that the emotional range among them is wide. What I can say is that catalogers' feelings and worldviews, whatever they may be, give the library its shape. I think we can agree that the librarians who constructed the Library of Congress Classification around 1900, Melvil Dewey, and the many classifiers around the world past and present, have had particular sets of desires around control and access and order. We all are asked to submit to those desires in our library work, as well as our own pursuit of knowledge and pleasure reading. And every decision regarding the aboutness of a book, or about where to place it within a particular discipline, takes place in a cataloger's affective and experiential world. While the classification provides the outlines, the catalogers color in the spaces with the books, based on their own readings of the book descriptions and their interpretations of the classification scheme. The decisions they make and the structures to which they are bound affect the circulation of books and their readers across the library. Indeed, some of the encounters will be unexpected, strange, frustrating, frightening, shame-inducing, awe-inspiring, and/or delightful. The emotional experiences of students described in Mabee and Fancher's article, as well as those of any visitor to the library, are all affected by classificatory design. One concern is that a library's ordering principles may reinforce or heighten already existing feelings of precarity or marginality. Because the classifications are hidden from patrons' view, it is difficult to measure the way the order affects a person's mind and body. That a person does not consciously register the associations does not mean that they are not affected."
  7. Morris, V.: Automated language identification of bibliographic resources (2020) 0.01 
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    Date
    2. 3.2020 19:04:22
  8. Heisig, P.: Informationswissenschaft für Wissensmanager : Was Wissensmanager von der informationswissenschaftlichen Forschung lernen können (2021) 0.01 
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    Date
    22. 1.2021 14:38:21
  9. Hauff-Hartig, S.: Automatische Transkription von Videos : Fernsehen 3.0: Automatisierte Sentimentanalyse und Zusammenstellung von Kurzvideos mit hohem Aufregungslevel KI-generierte Metadaten: Von der Technologiebeobachtung bis zum produktiven Einsatz (2021) 0.01 
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    Date
    22. 5.2021 12:43:05
  10. Hauff-Hartig, S.: Wissensrepräsentation durch RDF: Drei angewandte Forschungsbeispiele : Bitte recht vielfältig: Wie Wissensgraphen, Disco und FaBiO Struktur in Mangas und die Humanities bringen (2021) 0.01 
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    22. 5.2021 12:43:05
  11. Schrenk, P.: Gesamtnote 1 für Signal - Telegram-Defizite bei Sicherheit und Privatsphäre : Signal und Telegram im Test (2022) 0.01 
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    Date
    22. 1.2022 14:01:14
  12. Bager, J.: ¬Die Text-KI ChatGPT schreibt Fachtexte, Prosa, Gedichte und Programmcode (2023) 0.01 
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    Date
    29.12.2022 18:22:55
  13. Rieger, F.: Lügende Computer (2023) 0.01 
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    Date
    16. 3.2023 19:22:55
  14. Ding, J.: Can data die? : why one of the Internet's oldest images lives on wirhout its subjects's consent (2021) 0.01 
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    Abstract
    In 2021, sharing content is easier than ever. Our lingua franca is visual: memes, infographics, TikToks. Our references cross borders and platforms, shared and remixed a hundred different ways in minutes. Digital culture is collective by default and has us together all around the world. But as the internet reaches its "dirty 30s," what happens when pieces of digital culture that have been saved, screenshotted, and reposted for years need to retire? Let's dig into the story of one of these artifacts: The Lenna image. The Lenna image may be relatively unknown in pop culture today, but in the engineering world, it remains an icon. I first encountered the image in an undergrad class, then grad school, and then all over the sites and software I use every day as a tech worker like Github, OpenCV, Stack Overflow, and Quora. To understand where the image is today, you have to understand how it got here. So, I decided to scrape Google scholar, search, and reverse image search results to track down thousands of instances of the image across the internet (see more in the methods section).
    In the 21st century, the image has remained a common sight in classrooms and on TV, including a feature on Silicon Valley in 2014. Pushback towards the use of the image also grew in the 2010s leading up to 2019, when the Losing Lena documentary was released. Forsén shares her side of the story and asks for her image to be retired: "I retired from modelling a long time ago. It's time I retired from tech, too. We can make a simple change today that creates a lasting change for tomorrow. Let's commit to losing me." After the film's release, many of my female colleagues shared stories about their own encounters with the image throughout their careers. When one of the only women this well referenced, respected, and remembered in your field is known for a nude photo that was taken of her and is now used without her consent, it inevitably shapes the perception of the position of women in tech and the value of our contributions. The film called on the engineering community to stop their spread of the image and use alternatives instead. This led to efforts to remove the image from textbooks and production code and a slow, but noticeable decline in the image's use for research.
    Content
    "Having known Lenna for almost a decade, I have struggled to understand what the story of the image means for what tech culture is and what it is becoming. To me, the crux of the Lenna story is how little power we have over our data and how it is used and abused. This threat seems disproportionately higher for women who are often overrepresented in internet content, but underrepresented in internet company leadership and decision making. Given this reality, engineering and product decisions will continue to consciously (and unconsciously) exclude our needs and concerns. While social norms are changing towards non-consensual data collection and data exploitation, digital norms seem to be moving in the opposite direction. Advancements in machine learning algorithms and data storage capabilities are only making data misuse easier. Whether the outcome is revenge porn or targeted ads, surveillance or discriminatory AI, if we want a world where our data can retire when it's outlived its time, or when it's directly harming our lives, we must create the tools and policies that empower data subjects to have a say in what happens to their data. including allowing their data to die."
  15. Bargmann, S.; Blumesberger, S.; Gruber, A.; Luef, E.; Steltzer, R.: Sacherschließung geschlechtergerecht?! : Rückblick auf den Online-Workshop am 11. Mai 2022 und Aufruf zu gemeinsamen Aktivitäten (2022) 0.01 
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    15. 2.2023 14:30:22
  16. Krüger, N.; Pianos, T.: Lernmaterialien für junge Forschende in den Wirtschaftswissenschaften als Open Educational Resources (OER) (2021) 0.01 
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    22. 5.2021 12:43:05
  17. Manley, S.: Letters to the editor and the race for publication metrics (2022) 0.01 
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    6. 4.2022 19:22:26
  18. Wu, P.F.: Veni, vidi, vici? : On the rise of scrape-and-report scholarship in online reviews research (2023) 0.01 
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    Date
    22. 1.2023 18:33:53
  19. Candela, G.: ¬An automatic data quality approach to assess semantic data from cultural heritage institutions (2023) 0.01 
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    22. 6.2023 18:23:31
  20. Michel, A.: Informationsdidaktik für verschiedene Wissenskulturen (2020) 0.01 
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    Content
    Vgl. auch: Tappenbeck, I.: Zum Transfer der wissenskulturellen Perspektive in die bibliothekarische Praxis: Angebote zur Vermittlung vom Fach her entwickeln. In: Open Password. 2020, Nr.845 vom 30. Oktober 2020.

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