US 12,223,281 B2
Generating content using a generative model without relying on selected training examples
Yair Adato, Kfar Ben Nun (IL); Efrat Taig, Beer Sheva (IL); Nimrod Sarid, Tel Aviv (IL); Ron Mokady, Ramat Hasaron (IL); and Eyal Gutflaish, Beer Sheva (IL)
Assigned to BRIA ARTIFICIAL INTELLIGENCE LTD., Tel Aviv (IL)
Filed by BRIA ARTIFICIAL INTELLIGENCE LTD., Tel Aviv (IL)
Filed on Nov. 7, 2023, as Appl. No. 18/387,701.
Application 18/387,701 is a continuation of application No. PCT/IL2023/051132, filed on Nov. 5, 2023.
Claims priority of provisional application 63/525,754, filed on Jul. 10, 2023.
Claims priority of provisional application 63/444,805, filed on Feb. 10, 2023.
Prior Publication US 2024/0273866 A1, Aug. 15, 2024
Int. Cl. G06F 40/30 (2020.01); G06F 40/279 (2020.01); G06F 40/40 (2020.01); G06T 7/194 (2017.01); G06T 7/70 (2017.01); G06T 11/00 (2006.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G10L 15/06 (2013.01); G10L 15/18 (2013.01); H04N 5/272 (2006.01)
CPC G06F 40/30 (2020.01) [G06F 40/279 (2020.01); G06F 40/40 (2020.01); G06T 7/194 (2017.01); G06T 7/70 (2017.01); G06T 11/001 (2013.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G10L 15/063 (2013.01); G10L 15/18 (2013.01); H04N 5/272 (2013.01); G06T 2207/30196 (2013.01); G10L 2015/0631 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A non-transitory computer readable medium storing a software program comprising data and computer implementable instructions that when executed by at least one processor cause the at least one processor to perform operations for generating content using a generative model, the operations comprising
receiving an input indicative of a desire to generate a new content using a generative model, the generative model is a result of training a machine learning model using all training examples of a plurality of training examples, each training example of the plurality of training examples is associated with a respective content, the generative model includes a plurality of artificial neurons;
obtaining an indication of a particular subgroup of at least one but not all of the plurality of training examples;
identifying a specific subgroup of the plurality of artificial neurons associated with the particular subgroup of at least one but not all of the plurality of training examples;
based on the indication, using the input and the generative model while disregarding the artificial neurons included in the specific subgroup to generate the new content, abstaining, after the training of the machine learning model is completed, from basing the generation of the new content on any training example included in the particular subgroup; and
providing the new content.