Title: Personal LLM Agents: Insights and Survey about the Capability, Efficiency, and Security

Journal: arXiv

Summary: With the proliferation of personal computing devices, Intelligent Personal Assistants (IPAs) have become integral. Foundation models like LLMs offer semantic understanding and reasoning capabilities, which can be leveraged to create Personal LLM Agents. These agents are deeply integrated with personal data and devices. This paper discusses their architecture, efficiency, and security, culminating in a survey of expert opinions and potential solutions for the challenges they pose.

Key Points:

• Personal LLM Agents could redefine software paradigms for end-users.
• The architecture of these agents involves key components and design choices.
• Expert opinions and representative solutions are surveyed to address inherent challenges.
• The paper discusses potential for intelligent, efficient, and secure personal assistants.

Opinion: The emergence of Personal LLM Agents is transformative, providing a pathway towards more intimate and functional AI-user interactions. The analysis and solutions presented here are fundamental for developers and researchers aiming to advance secure and efficient personal AI solutions.

Links: Personal LLM Agents (arXiv) Download PDF