A Case-Based Persistent Memory for a Large Language Model
Fuente:
arXiv
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| Main Author: | |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866911869073096704 |
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| author | Watson, Ian |
| author_facet | Watson, Ian |
| contents | Case-based reasoning (CBR) as a methodology for problem-solving can use any appropriate computational technique. This position paper argues that CBR researchers have somewhat overlooked recent developments in deep learning and large language models (LLMs). The underlying technical developments that have enabled the recent breakthroughs in AI have strong synergies with CBR and could be used to provide a persistent memory for LLMs to make progress towards Artificial General Intelligence. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_08842 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | A Case-Based Persistent Memory for a Large Language Model Watson, Ian Artificial Intelligence I.2.0 Case-based reasoning (CBR) as a methodology for problem-solving can use any appropriate computational technique. This position paper argues that CBR researchers have somewhat overlooked recent developments in deep learning and large language models (LLMs). The underlying technical developments that have enabled the recent breakthroughs in AI have strong synergies with CBR and could be used to provide a persistent memory for LLMs to make progress towards Artificial General Intelligence. |
| title | A Case-Based Persistent Memory for a Large Language Model |
| topic | Artificial Intelligence I.2.0 |
| url | https://arxiv.org/abs/2310.08842 |