US 11,681,906 B2
Bayesian network in memory
Dmitry Vengertsev, Boise, ID (US); Stewart R. Watson, Boise, ID (US); Jing Gong, Boise, ID (US); and Ameya Parab, Millburn, NJ (US)
Assigned to Micron Technology, Inc., Boise, ID (US)
Filed by Micron Technology, Inc., Boise, ID (US)
Filed on Aug. 28, 2020, as Appl. No. 17/6,602.
Prior Publication US 2022/0067491 A1, Mar. 3, 2022
Int. Cl. G11C 11/54 (2006.01); G06N 3/063 (2023.01); G06N 3/084 (2023.01); H03M 1/36 (2006.01); G11C 13/00 (2006.01); G06N 5/046 (2023.01); G06N 7/01 (2023.01)
CPC G06N 3/063 (2013.01) [G06N 3/084 (2013.01); G06N 5/046 (2013.01); G06N 7/01 (2023.01); G11C 11/54 (2013.01); G11C 13/004 (2013.01); G11C 13/0009 (2013.01); G11C 13/0069 (2013.01); H03M 1/36 (2013.01)] 20 Claims
OG exemplary drawing
 
1. An apparatus, comprising:
a memory array;
a controller coupled to the memory array and configured to:
read data from a first plurality of memory cells of the memory array;
generate, using a second plurality of memory cells of the memory array, a first plurality of weight values and a first plurality of bias values based on a plurality of deterministic values read from the first plurality of memory cells;
generate, using a third plurality of memory cells of the memory array, a second plurality of weight values and a second plurality of bias values based on the first plurality of weight values and the second plurality of bias values; and
transmit output data from a fourth plurality of memory cells of the memory array, the output data comprising a result and a confidence in the result that is based at least on:
an input provided by a host,
the second plurality of weight values, and
the second plurality of bias values of a Bayesian neural network.