Sureel Inc.

Christopher Benjamin Kuhn

Tamay Aykut

In some aspects, a server, after determining that a training of an artificial intelligence has been completed to create a trained artificial intelligence, determines an attribution vector created during the training of the artificial intelligence, determines that the trained artificial intelligence has received an input, and generates, using the trained artificial intelligence, an output based on the input. The server determines an attribution determination for individual content creators of multiple content creators based on the attribution vector and based on identifying one or more of the creators that contributed at least a threshold amount during the training. A particular creator having a contribution less than the threshold amount does not receive a creator attribution. The server initiates providing compensation to one or more of the multiple content creators based at least in part on the attribution determination.

Model-based attribution for content generated by an artificial intelligence (AI)

In some aspects, a device may determine an output embedding associated with an output produced by a generative artificial intelligence and determine a distance measurement between the output embedding and individual content-related embeddings of a plurality of content-related embeddings to create a plurality of distance measurements. The device may correlate the plurality of distance measurements to a plurality of content creators that created multiple content items used to train the generative artificial intelligence to determine one or more creator attributions. The device may determine a creator attribution vector that includes the one or more creator attributions and initiate providing compensation to one or more content creators of the plurality of content creators.

Output-based attribution for content generated by an artificial intelligence (AI)

In some aspects, a server trains an artificial intelligence (AI) to create a trained AI. The training includes: selecting a content creator from multiple content creators to create a selected content creator, selecting a plurality of content items associated with the content creator to create selected content items, training the AI using the selected content items, determining a creator influence of the selected content creator on the trained AI based on an aggregate influence of the selected content items on the AI during the training, and including the creator influence in a static attribution vector. After the training is completed, the trained AI receives an input and generates an output. The server creates an attribution determination based at least in part on the static attribution vector and initiates providing compensation to one or more of the multiple content creators based at least in part on the attribution determination.

Growing community of inventors

Munich, Germany

Christopher Benjamin Kuhn