Lucia: A Temporal Computing Platform for Contextual Intelligence
November 19, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Weizhe Lin, Junxiao Shen
arXiv ID
2411.12778
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
The rapid evolution of artificial intelligence, especially through multi-modal large language models, has redefined user interactions, enabling responses that are contextually rich and human-like. As AI becomes an integral part of daily life, a new frontier has emerged: developing systems that not only understand spatial and sensory data but also interpret temporal contexts to build long-term, personalized memories. This report introduces Lucia, an open-source Temporal Computing Platform designed to enhance human cognition by capturing and utilizing continuous contextual memory. Lucia introduces a lightweight, wearable device that excels in both comfort and real-time data accessibility, distinguishing itself from existing devices that typically prioritize either wearability or perceptual capabilities alone. By recording and interpreting daily activities over time, Lucia enables users to access a robust temporal memory, enhancing cognitive processes such as decision-making and memory recall.
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