The working limitations of large language models
Large language models (LLMs) can generate convincingly human-sounding responses to queries. This ability can lead users to mistakenly attribute certain human capabilities to these artificial intelligence algorithms, namely reasoning, knowledge, understanding, and execution. Understanding how LLMs wo...
| Otros Autores: | , , |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
[Cambridge, Massachusetts] :
MIT Sloan Management Review
2023.
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| Edición: | [First edition] |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009825894906719 |
| Sumario: | Large language models (LLMs) can generate convincingly human-sounding responses to queries. This ability can lead users to mistakenly attribute certain human capabilities to these artificial intelligence algorithms, namely reasoning, knowledge, understanding, and execution. Understanding how LLMs work and what their limitations are can help users identify where generative AI technology is best applied and where its outputs might be unreliable. |
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| Notas: | Reprint #65233. |
| Descripción Física: | 1 online resource (7 pages) |
