Abstract: Examples are described herein for facilitating responses to computing device service requests. In various examples, natural language processing may be performed on a plurality of incoming computing device service requests associated with a plurality of computing devices. A plurality of embeddings corresponding to the plurality of computing device service requests may be generated based on the natural language processing. Based on distances between each of a particular subset of the embeddings in an embedding space, a trending service issue associated with the computing device service requests corresponding to the particular subset may be predicted. The trending service issue may be provided to a computing device servicer associated with resolving a new incoming computing device service request.

Abstract: In some examples, resource availability prediction can include a non-transitory machine-readable medium having instructions thereon executable to receive at the first processing resource, the memory resource, or both, a plurality of input data from a plurality of sources comprising a first plurality of sensors to monitor a plurality of workstations and write from the first processing resource to the memory resource the received input data. The instructions can be executable to identify at the first processing resource or a second processing resource, output data representative of a resource availability prediction based on input data representative of the written data, receive from a mobile device accessible by a user, a request for the resource availability prediction, and transmit the output data to the mobile device via signaling sent via a radio in communication with a third processing resource of the mobile device.

Abstract: Examples are described herein for facilitating responses to computing device service requests. In various examples, natural language processing may be performed on a plurality of incoming computing device service requests associated with a plurality of computing devices. A plurality of embeddings corresponding to the plurality of computing device service requests may be generated based on the natural language processing. Based on distances between each of a particular subset of the embeddings in an embedding space, a trending service issue associated with the computing device service requests corresponding to the particular subset may be predicted. The trending service issue may be provided to a computing device servicer associated with resolving a new incoming computing device service request.