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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2406.01133 |
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| _version_ | 1866913391116812288 |
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| author | Rychkov, Valentin Picoco, Claudia Caleca, Emilie |
| author_facet | Rychkov, Valentin Picoco, Claudia Caleca, Emilie |
| contents | The rapid development of Large Language Models (LLMs) and Generative Pre-Trained Transformers(GPTs) in the field of Generative Artificial Intelligence (AI) can significantly impact task automation in themodern economy. We anticipate that the PRA field will inevitably be affected by this technology. Thus, themain goal of this paper is to engage the risk assessment community into a discussion of benefits anddrawbacks of this technology for PRA. We make a preliminary analysis of possible application of LLM inProbabilistic Risk Assessment (PRA) modeling context referring to the ongoing experience in softwareengineering field. We explore potential application scenarios and the necessary conditions for controlledLLM usage in PRA modeling (whether static or dynamic). Additionally, we consider the potential impact ofthis technology on PRA modeling tools. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_01133 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Impact of Generative AI (Large Language Models) on the PRA model construction and maintenance, observations Rychkov, Valentin Picoco, Claudia Caleca, Emilie Performance The rapid development of Large Language Models (LLMs) and Generative Pre-Trained Transformers(GPTs) in the field of Generative Artificial Intelligence (AI) can significantly impact task automation in themodern economy. We anticipate that the PRA field will inevitably be affected by this technology. Thus, themain goal of this paper is to engage the risk assessment community into a discussion of benefits anddrawbacks of this technology for PRA. We make a preliminary analysis of possible application of LLM inProbabilistic Risk Assessment (PRA) modeling context referring to the ongoing experience in softwareengineering field. We explore potential application scenarios and the necessary conditions for controlledLLM usage in PRA modeling (whether static or dynamic). Additionally, we consider the potential impact ofthis technology on PRA modeling tools. |
| title | Impact of Generative AI (Large Language Models) on the PRA model construction and maintenance, observations |
| topic | Performance |
| url | https://arxiv.org/abs/2406.01133 |