Search (18 results, page 1 of 1)

Bischoff, M.: Wie eine KI lernt, sich selbst zu erklären (2023) 0.05

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Source: https://www.spektrum.de/news/sprachmodelle-auf-dem-weg-zu-einer-erklaerbaren-ki/2132727#Echobox=1682669561?utm_source=pocket-newtab-global-de-DE

Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.05

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Source: https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN

Rieger, F.: Lügende Computer (2023) 0.04

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Date: 16. 3.2023 19:22:55
Source: https://steadyhq.com/de/realitatsabzweig/posts/3ed79605-0650-4725-ab35-43f1243b57ee

Kurz, C.: Womit sich Strafverfolger bald befassen müssen : ChatGPT (2023) 0.02

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Source: https://netzpolitik.org/2023/chatgpt-womit-sich-strafverfolger-bald-befassen-muessen/?utm_source=pocket-newtab-global-de-DE#!

¬Der Student aus dem Computer (2023) 0.01

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Date: 27. 1.2023 16:22:55

Al-Khatib, K.; Ghosa, T.; Hou, Y.; Waard, A. de; Freitag, D.: Argument mining for scholarly document processing : taking stock and looking ahead (2021) 0.01

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Collard, J.; Paiva, V. de; Fong, B.; Subrahmanian, E.: Extracting mathematical concepts from text (2022) 0.01

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Stieler, W.: Anzeichen von Bewusstsein bei ChatGPT und Co.? (2023) 0.01
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Abstract

Ein interdisziplinäres Forschungsteam hat eine Liste von Eigenschaften aufgestellt, die auf Bewusstsein deuten, und aktuelle KI-Systeme darauf abgeklopft. Ein interdisziplinäres Forscherteam hat ein Paper [https://arxiv.org/abs/2308.08708] veröffentlicht, das eine Liste von 14 "Indikatoren" für Bewusstsein enthält, die aus sechs aktuellen Theorien über das Bewusstsein stammen. Aktuelle KI-Modelle wie GPT-3, Palm-E oder AdA von Deepmind weisen demnach einzelne dieser Indikatoren auf. "Es spricht viel dafür, dass die meisten oder alle Bedingungen für das Bewusstsein, die von derzeitigen Theorien vorgeschlagenen Bedingungen für das Bewusstsein mit den bestehenden Techniken der KI erfüllt werden können", schreiben die Autoren. Zum Team gehörte auch der Deep-Learning-Pionier Yoshua Bengio von der Université de Montréal.

Andrushchenko, M.; Sandberg, K.; Turunen, R.; Marjanen, J.; Hatavara, M.; Kurunmäki, J.; Nummenmaa, T.; Hyvärinen, M.; Teräs, K.; Peltonen, J.; Nummenmaa, J.: Using parsed and annotated corpora to analyze parliamentarians' talk in Finland (2022) 0.01

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Siegel, M.: Maschinelle Übersetzung (2023) 0.01

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Bischoff, M.: Was steckt hinter ChatGTP & Co? (2023) 0.01

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Morris, V.: Automated language identification of bibliographic resources (2020) 0.01

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Date: 2. 3.2020 19:04:22

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

Aizawa, A.; Kohlhase, M.: Mathematical information retrieval (2021) 0.01

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Brown, T.B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T.; Child, R.; Ramesh, A.; Ziegler, D.M.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; Amodei, D.: Language models are few-shot learners (2020) 0.01

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Suissa, O.; Elmalech, A.; Zhitomirsky-Geffet, M.: Text analysis using deep neural networks in digital humanities and information science (2022) 0.01

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Park, J.S.; O'Brien, J.C.; Cai, C.J.; Ringel Morris, M.; Liang, P.; Bernstein, M.S.: Generative agents : interactive simulacra of human behavior (2023) 0.01

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Azpiazu, I.M.; Soledad Pera, M.: Is cross-lingual readability assessment possible? (2020) 0.00

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