003 - Human-inspired Perspectives: A Survey on AI Long-term Memory
4 nov 2024 ·
13 min. 59 sec.
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Episode Title: Exploring Human-Inspired Long-Term Memory in AI Authors and Paper Title: Zihong He, Weizhe Lin, Hao Zheng, Fan Zhang, Matt Jones, Laurence Aitchison, Xuhai Xu, Miao Liu, Per Ola...
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Episode Title: Exploring Human-Inspired Long-Term Memory in AI
Authors and Paper Title: Zihong He, Weizhe Lin, Hao Zheng, Fan Zhang, Matt Jones, Laurence Aitchison, Xuhai Xu, Miao Liu, Per Ola Kristensson, Junxiao Shen -
Human-inspired Perspectives: A Survey on AI Long-term Memory.
"This paper begins by systematically introducing the mechanisms of human long-term memory, then explores AI long-term memory mechanisms."
In this episode, we delve into the crucial topic of long-term memory in artificial intelligence, inspired by human cognition. We discuss the mechanisms that underpin human long-term memory and how they can inform the development of AI systems capable of storing and utilizing information over extended periods. Key insights include the proposed Cognitive Architecture of Self-Adaptive Long-term Memory (SALM) and its implications for future AI advancements. Understanding these concepts is vital for professionals seeking to enhance AI performance across various applications.
AI Papers Update serves as your weekly source for the latest research papers in artificial intelligence, providing industry professionals with essential insights into emerging technologies and methodologies. Stay informed and ahead of the curve with our concise and informative episodes. 5. Original Paper
Link to Paper: https://arxiv.org/abs/2411.00489
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Authors and Paper Title: Zihong He, Weizhe Lin, Hao Zheng, Fan Zhang, Matt Jones, Laurence Aitchison, Xuhai Xu, Miao Liu, Per Ola Kristensson, Junxiao Shen -
Human-inspired Perspectives: A Survey on AI Long-term Memory.
"This paper begins by systematically introducing the mechanisms of human long-term memory, then explores AI long-term memory mechanisms."
In this episode, we delve into the crucial topic of long-term memory in artificial intelligence, inspired by human cognition. We discuss the mechanisms that underpin human long-term memory and how they can inform the development of AI systems capable of storing and utilizing information over extended periods. Key insights include the proposed Cognitive Architecture of Self-Adaptive Long-term Memory (SALM) and its implications for future AI advancements. Understanding these concepts is vital for professionals seeking to enhance AI performance across various applications.
AI Papers Update serves as your weekly source for the latest research papers in artificial intelligence, providing industry professionals with essential insights into emerging technologies and methodologies. Stay informed and ahead of the curve with our concise and informative episodes. 5. Original Paper
Link to Paper: https://arxiv.org/abs/2411.00489
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