Abstract: A computer-implemented method for streaming multimedia data includes receiving a request to stream, by a first computing device, a first multimedia data file stored on a second computing device. The computer-implemented method further includes determining a first recommendation to skip viewing of a first logical segment included in the multimedia data file, wherein the first recommendation is based, at least in part, on analyzing a set of user insight information corresponding to a first classification associated with the first logical segment. The computer-implemented method further includes determining that a first confidence score associated with the first recommendation is below a predetermined threshold level. The computer-implemented method further includes providing, in response to determining that the first confidence score is below the predetermined threshold level, the first recommendation to a user while streaming the first multimedia data file via the first computing device.

Abstract: An approach is provided in which a fault-injecting system injects a natural language fault into a first text segment to produce a second text segment that are both written in a natural language. The fault-injecting system receives a third text segment from a reviewer that includes at least one correction to the second text segment. The fault-injecting system compares the third text segment against the first text segment and generates an efficacy score. The efficacy score indicates whether the correction in the third text segment corrects the natural language fault. In turn, the fault-injecting system sends the efficacy score to an author of the first text segment.

Abstract: A computer-implemented method for streaming multimedia data includes receiving a request to stream, by a first computing device, a first multimedia data file stored on a second computing device. The computer-implemented method further includes determining a first recommendation to skip viewing of a first logical segment included in the multimedia data file, wherein the first recommendation is based, at least in part, on analyzing a set of user insight information corresponding to a first classification associated with the first logical segment. The computer-implemented method further includes determining that a first confidence score associated with the first recommendation is below a predetermined threshold level. The computer-implemented method further includes providing, in response to determining that the first confidence score is below the predetermined threshold level, the first recommendation to a user while streaming the first multimedia data file via the first computing device.

Abstract: Computer-implemented sending of notifications is disclosed and includes identifying, using natural language understanding and natural language classification, auto-renewing subscription service(s) associated with a user based on content of computing device(s) associated with the user and internet-available sources, the identifying resulting in identified auto-renewing subscription service(s).

Abstract: A location of a target associated with a first system is determined at the first system at a first time. A signal is constructed at the first system where the data of the signal includes an identifier indicative of a collision avoidance nature of the signal. The signal is broadcast from the first system. the broadcasting causes a second system to receive the signal; compute a likelihood of a collision between the first system and the second system using the location from the signal, a velocity of the first system, a location of the second system at the first time, and a velocity of the second system at the first time; and send a notification from the second system about the likelihood of collision when the likelihood of collision exceeding a threshold likelihood.

Abstract: An approach is provided in which a fault-injecting system injects a natural language fault into a first text segment to produce a second text segment that are both written in a natural language. The fault-injecting system receives a third text segment from a reviewer that includes at least one correction to the second text segment. The fault-injecting system compares the third text segment against the first text segment and generates an efficacy score. The efficacy score indicates whether the correction in the third text segment corrects the natural language fault. In turn, the fault-injecting system sends the efficacy score to an author of the first text segment.

Abstract: An approach is provided in which a fault-injecting system injects a natural language fault into a first text segment to produce a second text segment that are both written in a natural language. The fault-injecting system receives a third text segment from a reviewer that includes at least one correction to the second text segment. The fault-injecting system compares the third text segment against the first text segment and generates an efficacy score. The efficacy score indicates whether the correction in the third text segment corrects the natural language fault. In turn, the fault-injecting system sends the efficacy score to an author of the first text segment.

Abstract: A location of a target associated with a first system is determined at the first system at a first time. A signal is constructed at the first system where the data of the signal includes an identifier indicative of a collision avoidance nature of the signal. The signal is broadcast from the first system. the broadcasting causes a second system to receive the signal; compute a likelihood of a collision between the first system and the second system using the location from the signal, a velocity of the first system, a location of the second system at the first time, and a velocity of the second system at the first time; and send a notification from the second system about the likelihood of collision when the likelihood of collision exceeding a threshold likelihood.

Abstract: A location of a target associated with a first system is determined at the first system at a first time. A signal is constructed at the first system where the data of the signal includes a unique identifier, an identifier indicative of a collision avoidance nature of the signal, and the location of the target. The signal is broadcast from the first system. the broadcasting causes a second system to receive the signal; compute a likelihood of a collision between the first system and the second system using the location from the signal, a velocity of the first system, a location of the second system at the first time, and a velocity of the second system at the first time; and send a notification from the second system about the likelihood of collision when the likelihood of collision exceeding a threshold likelihood.

Abstract: A broadcast of a signal is received at a first system from a second system at a first time. From the signal, a location of a target associated with the second system and a velocity of the target are determined relative to a location of the first system and a velocity of the first system. At the first system, using the location and the velocity of the first system and using the location and the velocity of the target, a likelihood is computed of a collision between the first system and the second system. A notification is sent from the first system about the likelihood of collision responsive to the likelihood of collision exceeding a threshold likelihood.

Abstract: A broadcast of a signal is received at a first system from a second system at a first time. From the signal, a location of a target associated with the second system and a velocity of the target are determined relative to a location of the first system and a velocity of the first system. At the first system, using the location and the velocity of the first system and using the location and the velocity of the target, a likelihood is computed of a collision between the first system and the second system. A notification is sent from the first system about the likelihood of collision responsive to the likelihood of collision exceeding a threshold likelihood.

Abstract: A location of a target associated with a first system is determined at the first system at a first time. A signal is constructed at the first system where the data of the signal includes a unique identifier, an identifier indicative of a collision avoidance nature of the signal, and the location of the target. The signal is broadcast from the first system. the broadcasting causes a second system to receive the signal; compute a likelihood of a collision between the first system and the second system using the location from the signal, a velocity of the first system, a location of the second system at the first time, and a velocity of the second system at the first time; and send a notification from the second system about the likelihood of collision when the likelihood of collision exceeding a threshold likelihood.