US 12,333,796 B2
Bayesian compute unit with reconfigurable sampler and methods and apparatus to operate the same
Srivatsa Rangachar Srinivasa, Hillsboro, OR (US); Tanay Karnik, Portland, OR (US); Dileep Kurian, Portland, OR (US); Ranganath Krishnan, Hillsboro, OR (US); Jainaveen Sundaram Priya, Hillsboro, OR (US); and Indranil Chakraborty, West Lafayette, IN (US)
Assigned to Intel Corporation, Santa Clara, CA (US)
Filed by Intel Corporation, Santa Clara, CA (US)
Filed on Jun. 21, 2022, as Appl. No. 17/845,732.
Prior Publication US 2022/0319162 A1, Oct. 6, 2022
Int. Cl. G06V 10/84 (2022.01); G06F 7/544 (2006.01); G06V 10/82 (2022.01)
CPC G06V 10/84 (2022.01) [G06F 7/5443 (2013.01); G06V 10/82 (2022.01)] 24 Claims
OG exemplary drawing
 
1. An apparatus for an artificial intelligence-based model, the apparatus comprising:
memory to store a variance value and a mean value, the mean value and the variance value resulting from training of the artificial intelligence-based model; and
a plurality of neurons, each neuron including:
number generator circuitry to generate a first random number and a second random number;
multiplier circuitry to:
generate a first product by multiplying the first random number by the variance value; and
generate a second product by multiplying the second random number by the variance value;
adder circuitry to:
generate a first weight by adding the mean value to the first product; and
generate a second weight by adding the mean value to the second product, the first and second weights corresponding to a single probability distribution;
a first processing element to apply the first weight to a first activation; and
a second processing element to apply the second weight to a second activation.