13. An apparatus for utilizing a user's predicted attributes in a computer system comprising: (a) a computer having a memory; (b) an application executing on the computer, wherein the application is configured to: collect a plurality of sample user behaviors and a plurality of sample user attributes from a service that offers videos for viewing, wherein a sample user behavior is based on a sample user using the service and a sample user attribute is received from the sample user; train a model to be able to produce the plurality of sample user attributes from the plurality of sample user behaviors; after training, input the plurality of sample user behaviors into the trained model to produce predicted sample user attributes; compare the plurality of sample user attributes and the plurality of sample user behaviors to the predicted sample user attributes to determine associated probabilities for the predicted sample user attributes; determine a real user behavior for a second user based on the second user using the service; predict, using the model, that the second user has a predicted user attribute of an associated probability based on the user having the real user behavior, wherein the predicted user attribute of the associated probability is not known for the second user; and utilize that the second user has the predicted user attribute of the associated probability to improve the second user's experience using the service.
13. An apparatus for utilizing a user's predicted attributes in a computer system comprising: (a) a computer having a memory; (b) an application executing on the computer, wherein the application is configured to: collect a plurality of sample user behaviors and a plurality of sample user attributes from a service that offers videos for viewing, wherein a sample user behavior is based on a sample user using the service and a sample user attribute is received from the sample user; train a model to be able to produce the plurality of sample user attributes from the plurality of sample user behaviors; after training, input the plurality of sample user behaviors into the trained model to produce predicted sample user attributes; compare the plurality of sample user attributes and the plurality of sample user behaviors to the predicted sample user attributes to determine associated probabilities for the predicted sample user attributes; determine a real user behavior for a second user based on the second user using the service; predict, using the model, that the second user has a predicted user attribute of an associated probability based on the user having the real user behavior, wherein the predicted user attribute of the associated probability is not known for the second user; and utilize that the second user has the predicted user attribute of the associated probability to improve the second user's experience using the service. 21. The apparatus of claim 13 , wherein the application is configured to utilize by transmitting targeted advertisement to a user based on predicting that the second user has the predicted user attribute of the associated probability.