Abstract
In this study, we present an innovative fusion of language models and query analysis techniques to unlock cognition in artificial intelligence. The introduced open-source AI system seamlessly integrates a Chess engine with a language model, enabling it to predict moves and provide strategic explanations. Leveraging a vector database to achieve retrievable answer generation, our AI system elucidates its decision-making process, bridging the gap between machine's computational cognition and human-like understanding. Our choice of Chess as the demonstration environment underscores the versatility of our approach. Beyond Chess, our system holds promise for diverse applications, from medical diagnostics to financial forecasting. Our AI system is available at \href{https://github.com/TheOpenSI/CoSMIC.git}{https://github.com/TheOpenSI/CoSMIC.git}.
Original language | English |
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Title of host publication | ACIS 2024 Proceedings. |
Editors | Shirley Gregor, Craig McDonald, Blooma John, Ahmed Imran, Israr Qureshi, Ghassan Beydoun, Juliana Sutanto, Nilmini Wickramasinghe, Micheal Axelsen, Hamed Sarbazhosseini |
Publisher | AIS Electronic Library (AISeL) |
Pages | 1-13 |
Number of pages | 13 |
Publication status | Published - 10 Dec 2024 |
Event | Australasian Conference on Information Systems 2024: Digital Futures for a Sustainable Society - Canberra, Canberra, Australia Duration: 4 Dec 2024 → 6 Dec 2024 Conference number: 34 https://acis.aaisnet.org/acis2024/ |
Conference
Conference | Australasian Conference on Information Systems 2024 |
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Abbreviated title | ACIS 2024 |
Country/Territory | Australia |
City | Canberra |
Period | 4/12/24 → 6/12/24 |
Internet address |