US 11,886,999 B2
Artificial neural network training in memory
Saideep Tiku, Fort Collins, CO (US); and Poorna Kale, Folsom, CA (US)
Assigned to Micron Technology, Inc., Boise, ID (US)
Filed by Micron Technology, Inc., Boise, ID (US)
Filed on Jan. 17, 2023, as Appl. No. 18/097,629.
Application 18/097,629 is a continuation of application No. 17/039,243, filed on Sep. 30, 2020, granted, now 11,556,790.
Prior Publication US 2023/0169341 A1, Jun. 1, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 3/08 (2023.01); G06F 11/10 (2006.01)
CPC G06N 3/08 (2013.01) [G06F 11/1076 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A method, comprising:
accessing, from a memory array of a memory device, a bit string of data representing elements of an artificial neural network model, the elements comprising a plurality of weights and a plurality of biases;
identifying a type of the memory device that implements the artificial neural network model;
responsive to identifying the type of the memory device, introducing logical values into the bit string to modify the plurality of weights and the plurality of biases, the logical values representative of a number of expected errors that correspond to the memory device; and implementing the artificial neural network model in the memory device based at least in part on writing the introduced logic values of the bit string to the memory array.