  Seamless integration of physical objects as interactive digital entities
remains a challenge for spatial computing. This paper explores Artificial
Object Intelligence (AOI) in the context of XR, an interaction paradigm that
aims to blur the lines between digital and physical by equipping real-world
objects with the ability to interact as if they were digital, where every
object has the potential to serve as a portal to digital functionalities. Our
approach utilizes real-time object segmentation and classification, combined
with the power of Multimodal Large Language Models (MLLMs), to facilitate these
interactions without the need for object pre-registration. We implement the AOI
concept in the form of XR-Objects, an open-source prototype system that
provides a platform for users to engage with their physical environment in
contextually relevant ways using object-based context menus. This system
enables analog objects to not only convey information but also to initiate
digital actions, such as querying for details or executing tasks. Our
contributions are threefold: (1) we define the AOI concept and detail its
advantages over traditional AI assistants, (2) detail the XR-Objects system's
open-source design and implementation, and (3) show its versatility through
various use cases and a user study.
