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240503 ||| eng |
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|a QA76.9.N38
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|a Cappelli, Peter
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| 245 |
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|a Will large language models really change how work is done?
|b even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans
|c Peter Cappelli, Prasanna (Sonny) Tambe, Valery Yakubovich
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| 250 |
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|a [First edition]
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| 260 |
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|a [Cambridge, Massachusetts]
|b MIT Sloan Management Review
|c 2024
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| 300 |
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|a 8 pages
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| 505 |
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|a Includes bibliographical references
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| 653 |
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|a Gestion / Informatique
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| 653 |
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|a Artificial intelligence / http://id.loc.gov/authorities/subjects/sh85008180
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| 653 |
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|a Intelligence artificielle
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| 653 |
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|a Business / Data processing / http://id.loc.gov/authorities/subjects/sh85018264
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| 653 |
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|a artificial intelligence / aat
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| 653 |
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|a Traitement automatique des langues naturelles
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| 653 |
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|a Natural language processing (Computer science) / http://id.loc.gov/authorities/subjects/sh88002425
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| 700 |
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|a Tambe, Prasanna
|e author
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| 700 |
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|a Yakubovich, Valery
|e author
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 500 |
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|a Reprint #65329
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| 856 |
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|u https://learning.oreilly.com/library/view/~/53863MIT65329/?ar
|x Verlag
|3 Volltext
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|a 500
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|a 330
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|a 006.3/5
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|a Generative AI applications like ChatGPT demonstrate how large language models can quickly and cheaply perform some tasks that only humans could do before. Organizations might see an opportunity to use this technology to automate knowledge work, but implementing it comes with practical challenges that still require skilled employees’ involvement. This suggests that while newer AI tools might be better equipped to handle some tasks, they are unlikely to reshape organizations’ reliance on humans
|