US Patent Issued to Maplebear on June 23 for "Computing item findability through a findability machine-learning model" (Canadian, American Inventors)

ALEXANDRIA, Va., July 15 -- United States Patent no. 12,664,477, issued on June 23, was assigned to Maplebear Inc. (San Francisco).

"Computing item findability through a findability machine-learning model" was invented by Amalia Rothschild-Keita (Berkeley, Calif.), Brent Scheibelhut (Toronto), Mark Oberemk (Toronto), Hua Xiao (Toronto), Shaun Navin Maharaj (Vaughan, Canada) and Taha Amjad (Toronto).

According to the abstract* released by the U.S. Patent & Trademark Office: "An online concierge system uses a findability machine-learning model to predict the findability of items within a physical area. The findability model is a machine-learning model that is trained to compute findability scores, which are scores that represent the ease or...