Spranic builds spatial memory for physical AI
Physical AI needs context about its surroundings to adapt beyond a fixed set of instructions. Munich-based Spranic is building a spatial memory layer that records physical spaces and how they change. Connecting that information with knowledge graphs could help robots interpret their environments across different tasks, according to Jordi Spranger (pictured), founder and chief executive […] The…
Physical AI requires contextual knowledge of its surroundings to adapt beyond a fixed set of instructions. Spranic, a Munich-based company, is developing a spatial memory layer that records physical spaces and their changes. By connecting this information with knowledge graphs, Spranic believes it could help robots interpret their environments across different tasks.
Jordi Spranger, founder and CEO of Spranic, discussed these ideas with theCUBE Research’s John Furrier for theCUBE + NYSE Wired: AI Luminaries interview series. Spranger emphasized that robots need "Google Maps on steroids" to operate flexibly across various tasks, similar to how humans navigate environments. Knowledge graphs could help robots access the right information sources and preserve data provenance, enabling them to act in a safe and auditable manner.
Written by urgent.news from SiliconANGLE's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
