1. A system comprising: a genetic prediction server comprising: an interface that acquires records that each indicate one or more genetic variants determined to exist within an individual; and a controller that selects one or more machine learning models that utilize genetic variants as input, loads the one or more machine learning models, assigns a dimensional coordinate to each genetic variant used as an input to the one or more machine learning models, and for each individual in the records: predictively assigns at least one characteristic to that individual by operating the one or more machine learning models, utilizing at least one genetic variant indicated in the records for that individual as input to the one or more machine learning models, wherein each of the one or more machine learning models comprises a multi-layer neural network, each layer comprising multiple nodes, nodes in different layers are coupled via weighted connections, each node in an input layer of a neural network corresponds with a genetic variant, each node in an output layer of a neural network corresponds with a characteristic, and each neural network includes a convolutional layer that convolves about genetic variants that are used as input for the neural network, based on the dimensional coordinates of genetic variants; the controller generates a report indicating at least one predictively assigned characteristic for at least one individual, and transmits a command via the interface for presenting the report at a display, the controller analyzes input indicating accuracy of a predictively assigned characteristic, and determines a score for one of the one or more machine learning models based on the analyzed input and a cost function, and the controller revises the weighted connections based on the cost function for each neural network.