Search (33 results, page 2 of 2)

  • × theme_ss:"Computerlinguistik"
  • × type_ss:"el"
  • × year_i:[2020 TO 2030}
  1. Hahn, S.: DarkBERT ist mit Daten aus dem Darknet trainiert : ChatGPTs dunkler Bruder? (2023) 0.00 
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  2. Siepmann, D.: Auswirkungen von KI auf die Textproduktion in der Wissenschaft (2023) 0.00 
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  3. Weßels, D.: ChatGPT - ein Meilenstein der KI-Entwicklung (2023) 0.00 
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  4. Aizawa, A.; Kohlhase, M.: Mathematical information retrieval (2021) 0.00 
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  5. Zhai, X.: ChatGPT user experience: : implications for education (2022) 0.00 
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    Abstract
    ChatGPT, a general-purpose conversation chatbot released on November 30, 2022, by OpenAI, is expected to impact every aspect of society. However, the potential impacts of this NLP tool on education remain unknown. Such impact can be enormous as the capacity of ChatGPT may drive changes to educational learning goals, learning activities, and assessment and evaluation practices. This study was conducted by piloting ChatGPT to write an academic paper, titled Artificial Intelligence for Education (see Appendix A). The piloting result suggests that ChatGPT is able to help researchers write a paper that is coherent, (partially) accurate, informative, and systematic. The writing is extremely efficient (2-3 hours) and involves very limited professional knowledge from the author. Drawing upon the user experience, I reflect on the potential impacts of ChatGPT, as well as similar AI tools, on education. The paper concludes by suggesting adjusting learning goals-students should be able to use AI tools to conduct subject-domain tasks and education should focus on improving students' creativity and critical thinking rather than general skills. To accomplish the learning goals, researchers should design AI-involved learning tasks to engage students in solving real-world problems. ChatGPT also raises concerns that students may outsource assessment tasks. This paper concludes that new formats of assessments are needed to focus on creativity and critical thinking that AI cannot substitute.
  6. Shree, P.: ¬The journey of Open AI GPT models (2020) 0.00 
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    Abstract
    Generative Pre-trained Transformer (GPT) models by OpenAI have taken natural language processing (NLP) community by storm by introducing very powerful language models. These models can perform various NLP tasks like question answering, textual entailment, text summarisation etc. without any supervised training. These language models need very few to no examples to understand the tasks and perform equivalent or even better than the state-of-the-art models trained in supervised fashion. In this article we will cover the journey of these models and understand how they have evolved over a period of 2 years. 1. Discussion of GPT-1 paper (Improving Language Understanding by Generative Pre-training). 2. Discussion of GPT-2 paper (Language Models are unsupervised multitask learners) and its subsequent improvements over GPT-1. 3. Discussion of GPT-3 paper (Language models are few shot learners) and the improvements which have made it one of the most powerful models NLP has seen till date. This article assumes familiarity with the basics of NLP terminologies and transformer architecture.
    Type
    a
  7. Kurz, C.: Womit sich Strafverfolger bald befassen müssen : ChatGPT (2023) 0.00 
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  8. Bischoff, M.: Wie eine KI lernt, sich selbst zu erklären (2023) 0.00 
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  9. Stieler, W.: Anzeichen von Bewusstsein bei ChatGPT und Co.? (2023) 0.00 
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  10. Szöke, D.: ChatGPT : wie Sie die KI ausprobieren können (2022) 0.00 
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  11. Räwel, J.: Automatisierte Kommunikation (2023) 0.00 
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  12. Donath, A.: Nutzungsverbote für ChatGPT (2023) 0.00 
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  13. Weßels, D.: ChatGPT - ein Meilenstein der KI-Entwicklung (2022) 0.00 
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Authors

Languages

  • d 17
  • e 16

Types

  • a 25
  • p 5