Abstract: A system can monitor event data corresponding to a current user experience of a requesting user during a current application session with a network service. Based on the event data, the system generates one or more representations corresponding to the current user experience of the requesting user, and executes a machine learning model to process the one or more representations in order to predict a negative user experience for the requesting user within a future time frame during the current application session. In response to predicting the negative user experience, the system implements one or more corrective actions during the current application session through the service application to prevent or mitigate the predicted negative user experience.

Abstract: The disclosed technology provides solutions for generating synthetic 3D environments, In some aspects, the disclosed technology includes a process of synthetic environment generation that includes steps for collecting sensor data corresponding with a three-dimensional (3D) space, generating a 3D mesh based on the sensor data, and generating one or more synthetic 3D objects based on the 3D mesh and the sensor data. In some aspects, the process can further include steps for generating a 3D synthetic environment comprising the one or more synthetic 3D objects, wherein the 3D synthetic environment is generated based on the 3D mesh. Systems and machine-readable media are also provided.

Abstract: Examples of the present disclosure provide a computer-implemented system, comprising instructions for performing operations including: retrieving real-world data comprising skeleton attributes of various skeletons; receiving instructions to generate a simulated skeleton for a scene in a simulation; generating the simulated skeleton according to the scene based on the skeleton attributes, the simulated skeleton comprising a generic skeleton modified by scaling factors according to the scene; building a simulation asset using the simulated skeleton; and determining a reaction of a vehicle to the simulation asset in the scene simulated, the reaction of the vehicle being a function of a configuration of the vehicle.

Abstract: A system can monitor event data corresponding to a current user experience of a requesting user during a current application session with a network service. Based on the event data, the system generates one or more representations corresponding to the current user experience of the requesting user, and executes a machine learning model to process the one or more representations in order to predict a negative user experience for the requesting user within a future time frame during the current application session. In response to predicting the negative user experience, the system implements one or more corrective actions during the current application session through the service application to prevent or mitigate the predicted negative user experience.

Abstract: A computing system can receive event data corresponding to a user's experience with a network service. Based on the event data, the system can generate a set of representations that correspond to the user's experience with the network service. The representations may be analyzed and/or filtered by an artificial intelligence model executing on the computing system, which can predict negative experiences of users at future time intervals. Based on these predictions, the computing system can implement a set of corrective actions to steer the user experience to a more positive path.

Abstract: Systems, methods, and computer-readable media are disclosed for a quick evaluation system for three-dimensional (3D) assets used in simulations for an autonomous vehicle (AV). A disclosed method comprises receiving drive data recorded in a physical environment by a vehicle having a first sensor; simulating the first sensor associated with a virtual autonomous vehicle in a virtual environment of a 3D scene including an object that at least partially corresponds to the physical environment; evaluating simulated data based on the simulation of the first sensor using a machine learning (ML) model; comparing evaluation data recorded during the evaluation of the simulation of the first sensor using the ML model to the drive data recorded in the physical environment; and generating a report based on a comparison of the evaluation data to a portion of the drive data to determine metrics associated with the object in the virtual environment.

Abstract: The disclosed technology provides solutions for generating accurate virtual representations of real-world environments. A process of the disclosed technology can include steps for: aggregating a plurality of images, wherein each of the images is associated with a set of geolocation coordinates, extracting a set of image parameters from the plurality of images, wherein the set of image parameters includes a dynamic range value, and providing the set of image parameters to a three-dimensional (3D) modeling platform. In some aspects, the process can further include generating a virtual environment corresponding with the set of geolocation coordinates, wherein the virtual environment is based on the set of image parameters. Systems and machine-readable media are also provided.

Abstract: A network computer system for managing a network service (e.g., a transport service) can include a voice-assistant subsystem for generating dialogues and performing actions for service providers of the network service. The network computer system can receive, from a user device, a request for the network service. In response, the network computer system can identify a service provider and transmit an invitation to the provider device of the service provider. In response to the identification of the service provider for the request, the voice-assistant subsystem can trigger an audio voice prompt to be presented on the provider device and a listening period during which the provider device monitors for an audio input from the service provider. Based on the audio input captured by the provider device, the network computer system can determine an intent corresponding to whether the service provider accepts or declines the invitation.

Abstract: The disclosed technology provides solutions for generating synthetic 3D environments, In some aspects, the disclosed technology includes a process of synthetic environment generation that includes steps for collecting sensor data corresponding with a three-dimensional (3D) space, generating a 3D mesh based on the sensor data, and generating one or more synthetic 3D objects based on the 3D mesh and the sensor data. In some aspects, the process can further include steps for generating a 3D synthetic environment comprising the one or more synthetic 3D objects, wherein the 3D synthetic environment is generated based on the 3D mesh. Systems and machine-readable media are also provided.

Abstract: A network computer system for managing a network service (e.g., a transport service) can include a voice-assistant subsystem for generating dialogues and performing actions for service providers of the network service. The network computer system can receive, from a user device, a request for the network service. In response, the network computer system can identify a service provider and transmit an invitation to the provider device of the service provider. In response to the identification of the service provider for the request, the voice-assistant subsystem can trigger an audio voice prompt to be presented on the provider device and a listening period during which the provider device monitors for an audio input from the service provider. Based on the audio input captured by the provider device, the network computer system can determine an intent corresponding to whether the service provider accepts or declines the invitation.

Abstract: A network computer system can respond to a call connection signal by making a determination as to whether the call connection is likely to be supported for at least one of the caller or receiver using a first voice communication medium, as compared to an alternative voice communication medium. Based on the determination, the network computer system can cause the call connection to be established using the voice communication medium of the determination.

Abstract: A computing system can receive event data corresponding to a user's experience with a network service. Based on the event data, the system can generate a set of representations that correspond to the user's experience with the network service. The representations may be analyzed and/or filtered by an artificial intelligence model executing on the computing system, which can predict negative experiences of users at future time intervals. Based on these predictions, the computing system can implement a set of corrective actions to steer the user experience to a more positive path.

Abstract: A network computer system for managing a network service (e.g., a transport service) can include a voice-assistant subsystem for generating dialogues and performing actions for service providers of the network service. The network computer system can receive, from a user device, a request for the network service. In response, the network computer system can identify a service provider and transmit an invitation to the provider device of the service provider. In response to the identification of the service provider for the request, the voice-assistant subsystem can trigger an audio voice prompt to be presented on the provider device and a listening period during which the provider device monitors for an audio input from the service provider. Based on the audio input captured by the provider device, the network computer system can determine an intent corresponding to whether the service provider accepts or declines the invitation.

Abstract: A network computer system can respond to a call connection signal by making a determination as to whether the call connection is likely to be supported for at least one of the caller or receiver using a first voice communication medium, as compared to an alternative voice communication medium. Based on the determination, the network computer system can cause the call connection to be established using the voice communication medium of the determination.

Abstract: A network computer system operates to generate synthetic messages based on service-specific information. The network computer system communicates with user devices, including requester devices and provider devices, to match service requests generated by the requester devices to respective service provider entities associated with the provider devices. For a given service request generated by a respective requester device, the network computer system determines service-specific information using device data communicated by at least one of the respective requester device and a respective provider device. The respective provider device is associated with a service provider entity that is matched to the given service request. The network computer system detects a trigger based on the service-specific information.

Abstract: Methods are provided which are useful in assessing drug response data, or response data to other types of clinical treatment, in a group of test subjects, and in predicting responses in other subjects, by defining a population genetic structure comprising one or more genetic clusters. The population genetic structure is obtained by analysis of the genotypes of genetic loci present in nucleic acid samples obtained from members of the group of test subjects. The population genetic structure provides an improved tool for assessing the results of a study, such as a clinical trial, into the effectiveness of a drug or other clinical treatment in different sub-populations as it is based directly on genetic criteria for assigning subjects to sub-populations.