Spatials AI Glossary
Definitions for spatial AI, spatial computing, spatial GPS, VR and AR spatials, world models, and geospatial analytics.
3D Scene Understanding 3D Scene Understanding is a core Spatial AI capability that interprets raw depth and imagery to identify objects, surfaces, and layout within an environment. …
Ambient Spatial Computing Ambient Spatial Computing describes a future where Spatial AI quietly runs in the background of everyday environments, coordinating Spatials without …
AR Spatials AR Spatials are digital entities anchored to real-world locations and surfaces through Spatial AI and high-precision localization. They might appear as labels on …
Geospatial AI Geospatial AI focuses on applying machine learning to location-based data: satellite imagery, maps, GPS traces, and 3D city models. It powers use cases like land-use …
Indoor Positioning Indoor Positioning covers techniques for locating people and devices inside buildings, where GPS is weak or unavailable. Methods include Wi-Fi and BLE …
Location-Based Experiences Location-Based Experiences (LBEs) are apps and attractions whose core value depends on where the user is in the physical world-theme parks, museums, …
Mixed Reality Spatials Mixed Reality Spatials bridge full VR and pure AR by blending digital content with a continuously sensed view of the real world. In mixed reality headsets, …
Persistent Spatials Persistent Spatials are Spatials that remain available across sessions, devices, and time rather than existing only for a single user’s experience. A …
Simultaneous Localization and Mapping (SLAM) Simultaneous Localization and Mapping (SLAM) is a family of algorithms that allow devices to build a map of an unknown environment …
Spatial A/B Testing Spatial A/B Testing brings experimentation to the physical world by comparing how different Spatial configurations perform. Variants might include alternative …
