CERN for AI: a theoretical framework for autonomous simulation-based artificial intelligence testing and alignment
Abstract This paper explores the potential of a multidisciplinary approach to testing and aligning artificial intelligence (AI), specifically focusing on large language models (LLMs). Due to the rapid development and wide application of LLMs, challenges such as ethical alignment, controllability, an...
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| Autori principali: | , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
SpringerOpen
2024-08-01
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| Serie: | European Journal of Futures Research |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1186/s40309-024-00238-0 |
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