Generating content using a generative model without relying on selected training examples

A system for generating content using a generative model without relying on selected training examples, the system comprising:

• at least one processor configured to perform the operations of:
• 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.

A method for generating content using a generative model without relying on selected training examples, the method 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.