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| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Thus spoke GPT-3: Interviewing a large-language model on climate finance |
| Organization Unit | |
| Authors |
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| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Journal Title | Finance Research Letters |
| Publisher | Elsevier |
| Geographical Reach | international |
| ISSN | 1544-6123 |
| Volume | 53 |
| Page Range | 103617 |
| Date | 2023 |
| Abstract Text | This paper is an interview with a Large Language Model (LLM), namely GPT-3, on the issues of climate change. The interview should give some insights into the current capabilities of these large models which are deep neural networks with generally more than 100 billion parameters. In particular, it shows how eloquent and convincing the answers of such LLMs can be. However, it should be noted that LLMs can suffer from hallucination and their responses may not be grounded on facts. These deficiencies offer an interesting avenue for future research. |
| Free access at | DOI |
| Official URL | https://www.sciencedirect.com/science/article/pii/S1544612322007930 |
| Digital Object Identifier | 10.1016/j.frl.2022.103617 |
| Other Identification Number | merlin-id:23144 |
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