Abstract: Methods and systems of monitoring and managing a facility including a plurality of end point devices. One system includes a first gateway device. The first gateway device includes a first electronic processor configured to receive fixture data from at least one electro-mechanical element of a fixture associated with the facility, the fixture data related to an operation of the fixture, and enable transmission of the fixture data to a remote device for virtual processing. The system also includes a second gateway device communicatively coupled with the first gateway device. The second gateway device includes a second electronic processor configured to receive, from the first gateway device, the processed fixture data. The second electronic processor configured to convert the processed fixture data pursuant to a networking protocol associated with a building management system and transmit the converted fixture data for display via a visual dashboard associated with the building management system.

Abstract: Systems, apparatuses, and methods for detecting a user gesture or eye tracking for selecting of an object, and responding to the selection, are disclosed. A gesture or eye tracker may be placed near a user, along with a camera positioned to share at least a portion of a field of view with the user. The user may look or gesture to an object within the portion of the field of view, indicating its selection. The object may be recognized, and the user presented with one or more actions to take in response to the selected object.

Abstract: A method for operating an autonomous ground vehicle may include: via one or more processors, determining an occupation state of the autonomous ground vehicle; if the occupation state is unoccupied, autonomously initiating a testing routine, the testing routine comprising: determining a test location, determining a safety parameter of the test location; if the safety parameter fulfils a safety criterion, testing an autonomous driving system of the autonomous ground vehicle in the test location.

Abstract: An apparatus of a multiagent system comprises a processing unit to process a unit of analysis on sensor data received from a sensor, and to provide a latency estimate to process the unit of analysis, and a decision system coupled with the processing unit to execute a decision process in response to an event, wherein the decision system utilizes the latency estimate as part of the decision process.

Abstract: A system includes one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the computers to implement a combined machine learning model for processing an input including multiple features to generate a predicted output for the machine learning input. The combined model includes: a deep machine learning model configured to process the features to generate a deep model output; a wide machine learning model configured to process the features to generate a wide model output; and a combining layer configured to process the deep model output generated by the deep machine learning model and the wide model output generated by the wide machine learning model to generate the predicted output, in which the deep model and the wide model have been trained jointly on training data to generate the deep model output and the wide model output.

Abstract: A system includes one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the computers to implement a combined machine learning model for processing an input including multiple features to generate a predicted output for the machine learning input. The combined model includes: a deep machine learning model configured to process the features to generate a deep model output; a wide machine learning model configured to process the features to generate a wide model output; and a combining layer configured to process the deep model output generated by the deep machine learning model and the wide model output generated by the wide machine learning model to generate the predicted output, in which the deep model and the wide model have been trained jointly on training data to generate the deep model output and the wide model output.

Abstract: Systems, apparatuses, and methods for detecting a user gesture or eye tracking for selecting of an object, and responding to the selection, are disclosed. A gesture or eye tracker may be placed near a user, along with a camera positioned to share at least a portion of a field of view with the user. The user may look or gesture to an object within the portion of the field of view, indicating its selection. The object may be recognized, and the user presented with one or more actions to take in response to the selected object.

Abstract: In one example a management system for an autonomous vehicle, comprises a first image sensor to collect first image data in a first geographic region proximate the autonomous vehicle and a second image sensor to collect second image data in a second geographic region proximate the first geographic region and a controller communicatively coupled to the first image sensor and the second image sensor and comprising processing circuitry to collect the first image data from the first image sensor and second image data from the second image sensor, generate a first reliability index for the first image sensor and a second reliability index for the second image sensor, and determine a correlation between the first image data and the second image data. Other examples may be described.

Abstract: Systems, apparatuses, and methods for detecting a user gesture or eye tracking for selecting of an object, and responding to the selection, are disclosed. A gesture or eye tracker may be placed near a user, along with a camera positioned to share at least a portion of a field of view with the user. The user may look or gesture to an object within the portion of the field of view, indicating its selection. The object may be recognized, and the user presented with one or more actions to take in response to the selected object.

Abstract: Technologies for representing alternate reality characters in a real-world environment include receiving sensor data from sensors of a sensor network of a home location of an alternate reality character, determining available response to the stimuli represented by the sensor data, and determining an activity of the alternate reality character for a time period based on the available responses. The technologies may also include generating a video of the alternate reality character performing the determined activity superimposed on an image map of a real-world environment of the home location during the time period. Users may view the video in real time or during a time period subsequent to the time period represented in the video. Additionally, the alternate reality character may be transferred to remote computing devices in some embodiments.

Abstract: Systems, apparatuses, and methods for detecting a user gesture or eye tracking for selecting of an object, and responding to the selection, are disclosed. A gesture or eye tracker may be placed near a user, along with a camera positioned to share at least a portion of a field of view with the user. The user may look or gesture to an object within the portion of the field of view, indicating its selection. The object may be recognized, and the user presented with one or more actions to take in response to the selected object.

Abstract: In one example a management system for an autonomous vehicle, comprises a first image sensor to collect first image data in a first geographic region proximate the autonomous vehicle and a second image sensor to collect second image data in a second geographic region proximate the first geographic region and a controller communicatively coupled to the first image sensor and the second image sensor and comprising processing circuitry to collect the first image data from the first image sensor and second image data from the second image sensor, generate a first reliability index for the first image sensor and a second reliability index for the second image sensor, and determine a correlation between the first image data and the second image data. Other examples may be described.

Abstract: An apparatus of a multiagent system comprises a processing unit to process a unit of analysis on sensor data received from a sensor, and to provide a latency estimate to process the unit of analysis, and a decision system coupled with the processing unit to execute a decision process in response to an event, wherein the decision system utilizes the latency estimate as part of the decision process.

Abstract: A method for operating an autonomous ground vehicle may include: via one or more processors, determining an occupation state of the autonomous ground vehicle; if the occupation state is unoccupied, autonomously initiating a testing routine, the testing routine comprising: determining a test location, determining a safety parameter of the test location; if the safety parameter fulfils a safety criterion, testing an autonomous driving system of the autonomous ground vehicle in the test location.

Abstract: The present disclosure relates to applying techniques similar to those used in neural network language modeling systems to a content recommendation system. For example, by associating consumed media content to words of a language model, the system may provide content predictions based on an ordering. Thus, the systems and techniques described herein may produce enhanced prediction results for recommending content (e.g. word) in a given sequence of consumed content. In addition, the system may account for additional user actions by representing particular actions as punctuation in the language model.

Abstract: A system includes one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the computers to implement a combined machine learning model for processing an input including multiple features to generate a predicted output for the machine learning input. The combined model includes: a deep machine learning model configured to process the features to generate a deep model output; a wide machine learning model configured to process the features to generate a wide model output; and a combining layer configured to process the deep model output generated by the deep machine learning model and the wide model output generated by the wide machine learning model to generate the predicted output, in which the deep model and the wide model have been trained jointly on training data to generate the deep model output and the wide model output.

Abstract: Systems and methods for achieving high utilization of a network link are provided. A first communication protocol can be selected for transmitting network flows of a first type. A first quality of service can be assigned to network flows of the first type. A second communication protocol can be selected for transmitting network flows of a second type. A second quality of service, lower than the first quality of service, can be assigned to network flows of the second type. A first percentage of available bandwidth can be allocated to the network flows of both the first and second types. The remaining bandwidth, plus a second percentage of available bandwidth, can be allocated to the network flows of the second type, such that the total allocated bandwidth exceeds the available bandwidth of the network link.

Abstract: The present disclosure relates to applying techniques similar to those used in neural network language modeling systems to a content recommendation system. For example, by associating consumed media content to words of a language model, the system may provide content predictions based on an ordering. Thus, the systems and techniques described herein may produce enhanced prediction results for recommending content (e.g. word) in a given sequence of consumed content. In addition, the system may account for additional user actions by representing particular actions as punctuation in the language model.

Abstract: Systems and methods may provide for identifying one or more phrases in a conversation between a first user and a second user. In addition, a first visual profile may be generated based on the one or more phrases and a real-time recommendation may be generated based on the first visual profile. In one example, generating the first visual profile includes using the one or more phrases to obtain one or more images and incorporating the one or more images into the first visual profile.

Abstract: Techniques and mechanisms for evaluating a transmission outcome indicium to determine a state of data traffic congestion in a network. In an embodiment, congestion information for a packet of a transmission group is evaluated at a computer device to determine a congestion state, where a size of the transmission group is determined based on a congestion window parameter. In another embodiment, the evaluation to determine the congestion state is performed prior to the computer device detecting a transmission outcome indicium for some other packet of the transmission group.