Will large language models really change how work is done?: even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans
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 tha...
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| Beteiligte Personen: | , , |
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| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
[Cambridge, Massachusetts]
MIT Sloan Management Review
2024
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| Ausgabe: | [First edition]. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/53863MIT65329/?ar |
| Zusammenfassung: | 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. |
| Beschreibung: | Reprint #65329. - Includes bibliographical references |
| Umfang: | 1 Online-Ressource (8 Seiten) |
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| spelling | Cappelli, Peter VerfasserIn aut Will large language models really change how work is done? even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans Peter Cappelli, Prasanna (Sonny) Tambe, Valery Yakubovich [First edition]. [Cambridge, Massachusetts] MIT Sloan Management Review 2024 1 Online-Ressource (8 Seiten) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Reprint #65329. - Includes bibliographical references 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. Natural language processing (Computer science) Artificial intelligence Business Data processing Traitement automatique des langues naturelles Intelligence artificielle Gestion ; Informatique artificial intelligence Tambe, Prasanna VerfasserIn aut Yakubovich, Valery VerfasserIn aut |
| spellingShingle | Cappelli, Peter Tambe, Prasanna Yakubovich, Valery Will large language models really change how work is done? even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans Natural language processing (Computer science) Artificial intelligence Business Data processing Traitement automatique des langues naturelles Intelligence artificielle Gestion ; Informatique artificial intelligence |
| title | Will large language models really change how work is done? even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans |
| title_auth | Will large language models really change how work is done? even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans |
| title_exact_search | Will large language models really change how work is done? even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans |
| title_full | Will large language models really change how work is done? even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans Peter Cappelli, Prasanna (Sonny) Tambe, Valery Yakubovich |
| title_fullStr | Will large language models really change how work is done? even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans Peter Cappelli, Prasanna (Sonny) Tambe, Valery Yakubovich |
| title_full_unstemmed | Will large language models really change how work is done? even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans Peter Cappelli, Prasanna (Sonny) Tambe, Valery Yakubovich |
| title_short | Will large language models really change how work is done? |
| title_sort | will large language models really change how work is done even as organizations adopt increasingly powerful llms they will find it difficult to shed their reliance on humans |
| title_sub | even as organizations adopt increasingly powerful LLMs, they will find it difficult to shed their reliance on humans |
| topic | Natural language processing (Computer science) Artificial intelligence Business Data processing Traitement automatique des langues naturelles Intelligence artificielle Gestion ; Informatique artificial intelligence |
| topic_facet | Natural language processing (Computer science) Artificial intelligence Business Data processing Traitement automatique des langues naturelles Intelligence artificielle Gestion ; Informatique artificial intelligence |
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