US 12,094,451 B1
Updating machine learning models across devices
Tao Zhang, Eden Prairie, MN (US); Jie Ding, Shanghai (CN); and Huili Chen, San Diego, CA (US)
Assigned to Amazon Technologies, Inc., Seattle, WA (US)
Filed by Amazon Technologies, Inc., Seattle, WA (US)
Filed on Feb. 22, 2022, as Appl. No. 17/677,614.
Int. Cl. G10L 15/05 (2013.01); G06N 20/20 (2019.01); G10L 15/06 (2013.01)
CPC G10L 15/05 (2013.01) [G06N 20/20 (2019.01); G10L 15/063 (2013.01); G10L 2015/0635 (2013.01)] 22 Claims
OG exemplary drawing
 
1. A computer-implemented method for updating machine learning models, the method comprising:
determining first model data corresponding to a first machine learning model corresponding to a first function, the first model data comprising a first value corresponding to a first parameter;
sending the first model data to a first device having a first characteristic;
sending the first model data to a second device having a second characteristic different from the first characteristic;
receiving first variance data corresponding to the first parameter, the first variance data based at least in part on a first range of values corresponding to a first plurality of devices having the first characteristic, wherein the first plurality of devices comprises the first device;
receiving second variance data corresponding to the first parameter, the second variance data based at least in part on a second range of values corresponding to a second plurality of devices having the second characteristic;
based at least in part on the first variance data and the second variance data, determining third variance data corresponding to the first parameter, the third variance data corresponding to at least the first plurality of devices and the second plurality of devices;
sending the third variance data to the first device;
sending the third variance data to the second device;
based at least in part on the first variance data, the second variance data, and the first model data, determining second model data corresponding to a second machine learning model corresponding to the first function, the second model data comprising a second value corresponding to the first parameter;
sending the second model data to the first device, wherein the first device is configured to perform processing of further input data using the second machine learning model; and
sending the second model data to the second device.