Abstract: Methods, apparatus, systems and articles of manufacture to provide machine programmed creative support to a user are disclosed. An example apparatus include an artificial intelligence architecture to be trained based on previous inputs of the user; a processor to: implement a first machine learning model based on the trained artificial intelligence architecture; and predict a first action based on a current state of a computer program using the first machine learning model; implement a second machine learning model based on the trained artificial intelligence architecture; and predict a second action based on the current state of the computer program using the second machine learning model; and a controller to select a state based on the action that results in a state that is more divergent from the current state of the computer program.

Abstract: Apparatus, systems, methods, and articles of manufacture for automatic robot perception programming by imitation learning are disclosed. An example apparatus includes a percept mapper to identify a first percept and a second percept from data gathered from a demonstration of a task and an entropy encoder to calculate a first saliency of the first percept and a second saliency of the second percept. The example apparatus also includes a trajectory mapper to map a trajectory based on the first percept and the second percept, the first percept skewed based on the first saliency, the second percept skewed based on the second saliency. In addition, the example apparatus includes a probabilistic encoder to determine a plurality of variations of the trajectory and create a collection of trajectories including the trajectory and the variations of the trajectory.

Abstract: Methods and apparatus to facilitate generation of database queries are disclosed. An example apparatus includes a generator to generate a global importance tensor. The global importance tensor based on a knowledge graph representative of information stored in a database. The knowledge graph includes objects and connections between the objects. The global importance tensor includes importance values for different types of the connections between the objects. The example apparatus further includes an importance adaptation analyzer to generate a session importance tensor based on the global importance tensor and a user query, and a user interface to provide a suggested query to a user based on the session importance tensor.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed for industrial robot code recommendation. Disclosed examples include an apparatus comprising: at least one memory; instructions in the apparatus; and processor circuitry to execute the instructions to at least: generate at least one action proposal for an industrial robot; rank the at least one action proposal based on encoded scene information; generate parameters for the at least one action proposal based on the encoded scene information, task data, and environment data; and generate an action sequence based on the at least one action proposal.

Abstract: System and techniques for vehicle occupant monitoring are described herein. Sensor data, that includes visual image data, is obtained from a sensor array of the vehicle. An object carried by the vehicle is detected from the visual image data. A safety event for the vehicle may be identified based on the object detection and an operational element of the vehicle is altered in response to detecting the safety event.

Abstract: Systems and methods for determining a configuration for a microarchitecture are described herein. An example system includes a proposal generator to generate a first candidate configuration of parameters for the microarchitecture, a machine learning model to process the first candidate configuration of parameters to output estimated performance indicators for the microarchitecture, an uncertainty checker to determine whether the estimated performance indicators are reliable, and a performance checker. In response to a determination that the estimated performance indicators are reliable, the performance checker is to determine whether the estimated performance indicators have improved toward a target. Further, if the estimated performance indicators have improved, the performance checker is to store the first candidate configuration of parameters in a memory as a potential solution for a microarchitecture without performing a full simulation on the first candidate configuration of parameters.

Abstract: Methods and apparatus to facilitate generation of database queries are disclosed. An example apparatus includes a generator to generate a global importance tensor. The global importance tensor based on a knowledge graph representative of information stored in a database. The knowledge graph includes objects and connections between the objects. The global importance tensor includes importance values for different types of the connections between the objects. The example apparatus further includes an importance adaptation analyzer to generate a session importance tensor based on the global importance tensor and a user query, and a user interface to provide a suggested query to a user based on the session importance tensor.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for object manipulation via action sequence optimization. An example method disclosed herein includes determining an initial state of a scene, generating a first action phase sequence to transform the initial state of the scene to a solution state of the scene by selecting a plurality of action phases based on action phase probabilities, determining whether a first simulated outcome of executing the first action phase sequence satisfies an acceptability criterion and, when the first simulated outcome does not satisfy the acceptability criterion, calculating a first cost function output based on a difference between the first simulated outcome and the solution state of the scene, the first cost function output utilized to generate updated action phase probabilities.

Abstract: Disclosed herein are systems and methods for cross-domain training of sensing-system-model instances. In an embodiment, a system receives, via a first application programming interface (API), an input-dataset selection identifying an input dataset, which includes a plurality of dataframes that are in a first dataframe format and that have annotations corresponding to one or more sensing tasks performed with respect to the dataframes. The system executes a plurality of dataframe-transformation functions to convert the plurality of dataframes of the input dataset into a predetermined dataframe format. The system trains an instance of a first machine-learning model using the converted dataframes of the input dataset to perform at least a subset of the one or more sensing tasks. The system outputs, via the first API, one or more model-validation metrics pertaining to the training of the instance of the first machine-learning model.

Abstract: Systems and techniques for simulated vehicle operation modeling with real vehicle profiles are described herein. In an example, a simulated vehicle modeling system is adapted to obtain a vehicle performance fingerprint, such as from a vehicle performance fingerprint that includes vehicle performance data collected from a unique vehicle while experiencing real world driving conditions. The simulated vehicle modeling system may be further adapted to present, in a driving simulator, a simulated driving experience with a simulated vehicle, such as for a simulated vehicle that is constructed based on the vehicle performance fingerprint. The simulated vehicle modeling system may be further adapted to update a set of driving directives for an autonomous vehicle based on the simulated driving experience and upload the set of driving directive to an autonomous vehicle.

Abstract: System and techniques for abandoned object detection are described herein. a fence is established about a person and an object is detected within the fence. An entry is created in an object-person relationship data structure to establish a relationship between the person and the object within the fence. Then, the position of the object is monitored until an indication that the fence is terminated is received. If it is detected that the object is outside the fence during the monitoring, the person is alerted.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for object manipulation via action sequence optimization. An example method disclosed herein includes determining an initial state of a scene, generating a first action phase sequence to transform the initial state of the scene to a solution state of the scene by selecting a plurality of action phases based on action phase probabilities, determining whether a first simulated outcome of executing the first action phase sequence satisfies an acceptability criterion and, when the first simulated outcome does not satisfy the acceptability criterion, calculating a first cost function output based on a difference between the first simulated outcome and the solution state of the scene, the first cost function output utilized to generate updated action phase probabilities.

Abstract: Methods and apparatus to automatically generate code for graphical user interfaces are disclosed. An example apparatus includes a textual description analyzer to encode a user-provided textual description of a GUI design using a first neural network. The example apparatus further includes a DSL statement generator to generate a DSL statement with a second neural network. The DSL statement is to define a visual element of the GUI design. The DSL statement is generated based on at least one of the encoded textual description or a user-provided image representative of the GUI design. The example apparatus further includes a rendering tool to render a mockup of the GUI design based on the DSL statement.

Abstract: Systems and methods for determining a configuration for a microarchitecture are described herein. An example system includes a proposal generator to generate a first candidate configuration of parameters for the microarchitecture, a machine learning model to process the first candidate configuration of parameters to output estimated performance indicators for the microarchitecture, an uncertainty checker to determine whether the estimated performance indicators are reliable, and a performance checker. In response to a determination that the estimated performance indicators are reliable, the performance checker is to determine whether the estimated performance indicators have improved toward a target. Further, if the estimated performance indicators have improved, the performance checker is to store the first candidate configuration of parameters in a memory as a potential solution for a microarchitecture without performing a full simulation on the first candidate configuration of parameters.

Abstract: System and techniques for vehicle-based measurement of signal object integrity are described herein. Sensor data of an environment of the vehicle is obtained. A bound for the sensor data for the sensor data is also obtained. Here, the bound corresponds to a signal object (e.g., sign, light, road marking, etc.). A classifier for the signal object is invoked on the sensor data based on the bound. If the classifier produces a result that indicates a problem with the signal object, a representation of the result is communicated.

Abstract: Systems and techniques for mobility-as-a-service for user experience are described herein. An orchestration log may be maintained that includes current orchestration data. An orchestration backup record may be generated that includes alternate MaaS nodes on the MaaS network. It may be determined that connectivity is lost to a first orchestration container hosted by a first MaaS node. An orchestration container is generated using the orchestration log to maintain orchestration functionality. An available second MaaS node is identified from the alternate MaaS nodes. The orchestration container may be transferred to the second MaaS node.

Abstract: Various systems and methods for collaborative multimodal trip planning are described herein, including receiving a user request for a multi-user transit plan, determining candidate travel paths for first and second users, identifying a merge opportunity in the candidate travel paths to coordinate shared travel between the first and second users, determining adjusted travel paths for the first and second users using the identified merge opportunity, and determining a cost of the adjusted travel paths with respect to the candidate travel paths.

Abstract: Systems and techniques for micro payments in a mobility-as-a-service (MaaS) network are described herein. A mobility task may be received for execution by a MaaS node of the MaaS network. An electronic contract may be established with a requestor of the task. A payment transaction may be initiated based on the mobility task and the electronic contract. The mobility task may be submitted for execution by the MaaS node using resources of the MaaS node. An amount of the payment may be transferred from an electronic account of the requestor to an electronic account of the MaaS node.

Abstract: System and techniques for hands-free deployment of geographically linked applications are described herein. A radio transceiver of a vehicle may detect a beacon. Here, the beacon includes an indication that an application linked to a geographical area covered by the beacon is available. The vehicle may establish a secure communications link with an application server corresponding to the beacon and receive, through the secure communications link, an application. Then, the vehicle may execute the application in a protected execution environment without intervention by a user of the vehicle.

Abstract: Various systems and methods for improving connectivity of a Mobility-as-a-Service (MaaS) node are described herein, including categorizing MaaS communication traffic of a MaaS node into different levels of priority and controlling duplication or repetition of the MaaS communication traffic using the categorized level of priority of the MaaS communication traffic.