Californian startup ZaïNar has raised $100 million to develop an alternative to GPS powered by artificial intelligence (AI).
That $100 million figure includes the $10 million the company recently took in, valuing it at $1 billion, the company said in a statement released Thursday (Feb. 19). press release.
ZaiNar said it solves a persistent problem for robots and other AI-based systems: the ability to obtain exact location data that helps robots detect other people and objects.
The company said it has developed an alternative to GPS that uses Wi-Fi and 5G cellular networks to provide lightning-fast location information without satellites, cameras or battery drain.
“ZaiNar has solved a problem that has bogged down the industry for decades,” said Steve Jurvestonwho sits on the company’s board of directors, as well as that of SpaceX. “Precise positioning without dedicated hardware infrastructure.”
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CEO Daniel Jacker told The Information in a interview released Thursday that the company has attracted professional customers in sectors such as hospitals and construction.
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In the first case, ZaiNar’s technology can alert staff that someone is waiting when a patient enters a hospital room. And on construction sites, technology can inform project managers where workers are located to help drive efficiency.
The company’s financing comes in the middle of rise of “physical AI” or an iteration of robots in which advances in sensing, perception, and large AI models provide machines with capabilities that traditional automation has never supported.
“Earlier robots followed fixed commands and worked only in predictable environments, grappling with the unpredictability of everyday operations such as changing configurations, varying object shapes, mixed lighting, and human movements,” PYMNTS wrote last fall. “This is starting to change as research groups show how simulation, digital twins, and multimodal learning pipelines enable robots to learn adaptive behaviors and transmit those behaviors in real-world installations with minimal retraining.”
One of the clearest examples of physical AI moving from research to frontline use is from Amazon Robot Vulcan, which uses vision and touch to pick and put away items in distribution centers, allowing it to handle flexible fabric storage modules and unpredictable product shapes.
Rival Walmartmeanwhile, is expanding physical AI systems across its entire distribution network, using automation platforms that reduce unit handling costs and increase throughput.
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