Throughout history, cultures have evolved through their technical apparatuses, leaving traces in the physical landscape. In the context of future lived environments, this evolution takes on new dimensions, where augmented intelligenceAugmented intelligence integrates time as a critical element in our interaction with space. The transition from traditional, orthographic architectural practices to post-orthographic, almost-real-time (ART) interfaces mark a shift in how we perceive and engage with our surroundings. Machines gradually become more advanced in perceiving and interpreting space with increasing complexity, imbuing Built Environments (BE) with a level of intelligence that mirrors, yet diverges from, human cognition. This chapter engages with spatial memorySpatial memory, exploring its augmentation through emerging media technologies that facilitate a reconfiguration of archival practices. These tools are not mere extensions, but radical reconfigurations of how spaces can be perceived, recorded, and interacted with across time, spanning past and present. A hybrid 3D framework is proposed: an Extended Reality (XR)Extended Reality (XR) prototype that examines innovations in Computer Vision (CV), where machines hold the capacity to perceive and interpret the size, colour, artifacts, and movements within spaces. This hybrid methodology, which integrates both Deep LearningDeep learning (DL) predictions on spatial semantics and an XR prototype, is structured into Back and Front end components, a borrowing of computer science terminology that is adapted to the context of archives. Together, they form a spatio-temporal archival system, designed to be inhabited and experienced in ART. This chapter aims to re-envision Human-Building InteractionHuman-building interaction (HBI) by exploring future environments that integrate machine intelligence and interactivity, as well as XR-driven spatial memorySpatial memory, allowing buildings to become intelligent, responsive, and connected to human experience in both physical and temporal dimensions. A case study is presented to demonstrate the application of this methodology through the development of an XR-based system that serves as a dynamic archive. Specifically, the Back end focuses on transforming raw data, from 3D scans, into structured information with CV. CV in this case, through machines able to interpret 3D data and structure spatial information, enables the construction of interactive archives. The Front-end transforms this information into knowledge within an interactive XR geo-based environment. By building upon the tradition of archives as repositories of collective memory, it advocates for a BE where the cloud—timeless and boundless—becomes a dynamic spatio-temporal archiveSpatio-temporal archives. This interpretation of HBI seeks to redefine assumptions through digital augmentation within physical environments, while creating immersive, XRExtended Reality (XR)-mediated environments that exist within and interact with the physical world.