AI for Service: Proactive Assistance with AI Glasses

Fuente: arXiv
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Autori principali: Wen, Zichen, Wang, Yiyu, Liao, Chenfei, Yang, Boxue, Li, Junxian, Liu, Weifeng, He, Haocong, Feng, Bolong, Liu, Xuyang, Lyu, Yuanhuiyi, Zheng, Xu, Hu, Xuming, Zhang, Linfeng
Natura: Preprint
Pubblicazione: 2025
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author Wen, Zichen
Wang, Yiyu
Liao, Chenfei
Yang, Boxue
Li, Junxian
Liu, Weifeng
He, Haocong
Feng, Bolong
Liu, Xuyang
Lyu, Yuanhuiyi
Zheng, Xu
Hu, Xuming
Zhang, Linfeng
author_facet Wen, Zichen
Wang, Yiyu
Liao, Chenfei
Yang, Boxue
Li, Junxian
Liu, Weifeng
He, Haocong
Feng, Bolong
Liu, Xuyang
Lyu, Yuanhuiyi
Zheng, Xu
Hu, Xuming
Zhang, Linfeng
contents In an era where AI is evolving from a passive tool into an active and adaptive companion, we introduce AI for Service (AI4Service), a new paradigm that enables proactive and real-time assistance in daily life. Existing AI services remain largely reactive, responding only to explicit user commands. We argue that a truly intelligent and helpful assistant should be capable of anticipating user needs and taking actions proactively when appropriate. To realize this vision, we propose Alpha-Service, a unified framework that addresses two fundamental challenges: Know When to intervene by detecting service opportunities from egocentric video streams, and Know How to provide both generalized and personalized services. Inspired by the von Neumann computer architecture and based on AI glasses, Alpha-Service consists of five key components: an Input Unit for perception, a Central Processing Unit for task scheduling, an Arithmetic Logic Unit for tool utilization, a Memory Unit for long-term personalization, and an Output Unit for natural human interaction. As an initial exploration, we implement Alpha-Service through a multi-agent system deployed on AI glasses. Case studies, including a real-time Blackjack advisor, a museum tour guide, and a shopping fit assistant, demonstrate its ability to seamlessly perceive the environment, infer user intent, and provide timely and useful assistance without explicit prompts.
format Preprint
id arxiv_https___arxiv_org_abs_2510_14359
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle AI for Service: Proactive Assistance with AI Glasses
Wen, Zichen
Wang, Yiyu
Liao, Chenfei
Yang, Boxue
Li, Junxian
Liu, Weifeng
He, Haocong
Feng, Bolong
Liu, Xuyang
Lyu, Yuanhuiyi
Zheng, Xu
Hu, Xuming
Zhang, Linfeng
Artificial Intelligence
Computation and Language
Computer Vision and Pattern Recognition
In an era where AI is evolving from a passive tool into an active and adaptive companion, we introduce AI for Service (AI4Service), a new paradigm that enables proactive and real-time assistance in daily life. Existing AI services remain largely reactive, responding only to explicit user commands. We argue that a truly intelligent and helpful assistant should be capable of anticipating user needs and taking actions proactively when appropriate. To realize this vision, we propose Alpha-Service, a unified framework that addresses two fundamental challenges: Know When to intervene by detecting service opportunities from egocentric video streams, and Know How to provide both generalized and personalized services. Inspired by the von Neumann computer architecture and based on AI glasses, Alpha-Service consists of five key components: an Input Unit for perception, a Central Processing Unit for task scheduling, an Arithmetic Logic Unit for tool utilization, a Memory Unit for long-term personalization, and an Output Unit for natural human interaction. As an initial exploration, we implement Alpha-Service through a multi-agent system deployed on AI glasses. Case studies, including a real-time Blackjack advisor, a museum tour guide, and a shopping fit assistant, demonstrate its ability to seamlessly perceive the environment, infer user intent, and provide timely and useful assistance without explicit prompts.
title AI for Service: Proactive Assistance with AI Glasses
topic Artificial Intelligence
Computation and Language
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2510.14359