Abstract: System and method of generating an executable action item in response to natural language dialogue are disclosed herein. A computing system receives a dialogue message from a remote client device of a customer associated with an organization, the dialogue message comprising an utterance indicative of an implied goal. A natural language processor of the computing system parses the dialogue message to identify one or more components contained in the utterance. The planning module of the computing system identifies the implied goal. The computing system generates a plan within a defined solution space. The computing system generates a verification message to the user to confirm the plan. The computing system transmits the verification message to the remote client device of the customer. The computing system updates an event queue with instructions to execute the action item according to the generated plan upon receiving a confirmation message from the remote client device.

Abstract: Embodiments disclosed herein generally relate to a system and method for proactively generating an intervening message for a remote client device in response to an anticipated user action. A computing system receives one or more streams of user activity. The one or more streams of user activity include interaction with a server of an organization via an application executing on the remote client device. The computing system inputs the one or more streams of user activity into a prediction model. The computing system identifies an anticipated user action based on a prediction output from the prediction model. The computing system determines, based on a solution model, a proposed solution to the anticipated user action. The computing system generates an anticipated message to be transmitted to the remote client device of the user. The computing system transmits the anticipated message to the remote client device of the user.

Abstract: A BAW resonator (RN) with reduced lateral modes is provided. The resonator has an active stack of bottom electrode (BE), piezoelectric material (PM) and top electrode (TE) and at least one element of this active stack has a curved side wall (CSW). Two or more curved side walls may be arranged on spheres, on cylinders or prisms with an elliptical footprint with different radii.

Abstract: Methods and systems are described for generating dynamic interface options using machine learning models. The dynamic interface options may be generated in real time and reflect the likely goals and/or intents of a user. The machine learning model may provide these features by interpreting multi-modal feature inputs. For example, the machine learning model may include a first machine learning model, wherein the first machine learning model comprises a convolutional neural network, and a second machine learning model, wherein the second machine learning model performs a Weight of Evidence (WOE) analysis.

Abstract: In certain embodiments, intent prediction and dialogue generation may be facilitated. In some embodiments, a chat initiation request may be obtained from a user. The latest activity information associated with the user may be provided to a prediction model to obtain a first set of predicted intents of the user. For each intent of the first set of predicted intents, a candidate question may be selected from a question set based on the candidate question matching the intent. In some embodiments, the candidate questions may be simultaneously presented on the chat interface.

Abstract: Methods and systems are described for generating dynamic interface options using machine learning models. The dynamic interface options may be generated in real time and reflect the likely goals and/or intents of a user. The machine learning model may provide these features by interpreting multi-modal feature inputs. For example, the machine learning model may include a first machine learning model, wherein the first machine learning model comprises a convolutional neural network, and a second machine learning model, wherein the second machine learning model performs a Weight of Evidence (WOE) analysis.

Abstract: A door assembly for a motor vehicle is provided having a door body and a door trim panel attached to the door body on the vehicle inside, with a first impact region and a second impact region formed integrally therewith, wherein at each of the impact regions, an intermediate space is formed between the door trim panel and the door body. In order to allow an optimized protection of an occupant's pelvic region from impact by a vehicle door in a side impact, it is provided that a nominal break line is formed between the first impact region and the second impact region, along which the first impact region or seat impact region can be separated from the second impact region by a force acting in the vehicle transverse direction.

Abstract: In certain embodiments, pre-chat intent prediction and dialogue generation may be facilitated. In some embodiments, a chat initiation request may be obtained from a user. The latest activity information associated with the user may be provided to a prediction model to obtain a first set of predicted intents of the user. For each intent of the first set of predicted intents, a candidate question may be selected from a question set based on the candidate question matching the intent. Within ten seconds of the chat initiation request, the candidate questions may be simultaneously presented on the chat interface. Based on negative feedback obtained via the chat interface with respect to the candidate questions, additional candidate questions matching the second set of predicted intents may be presented on the chat interface. In some embodiments, the negative feedback may be provided to the prediction model to update configurations of the prediction model.

Abstract: A filament production device, in particular a filament reaction-spinning production device, comprising at least one spinning nozzle unit, which is provided for producing at least one filament formed as a hollow fibre membrane from at least one polymer solution, and comprising a polymerisation unit, which is provided for initiating a polymerisation of the polymer solution, wherein the polymerisation unit is provided for initiating the polymerisation at least partially within the spinning nozzle unit.

Abstract: Radio frequency shielding within a semiconductor package is described. In one example, a multiple chip package has a digital chip, a radio frequency chip, and an isolation layer between the digital chip and the radio frequency chip. A cover encloses the digital chip and the radio frequency chip.

Abstract: A system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to perform steps of providing automated natural dialogue with a customer. The system may generate one or more events and commands temporarily stored in queues to be processed by one or more of a dialogue management device, an API server, and an NLP device. The dialogue management device may create adaptive responses to customer communications using a customer context, a rules-based platform, and a trained machine learning model.

Abstract: A door assembly for a motor vehicle is provided having a door body and a door trim panel attached to the door body on the vehicle inside, with a first impact region and a second impact region formed integrally therewith, wherein at each of the impact regions, an intermediate space is formed between the door trim panel and the door body. In order to allow an optimized protection of an occupant's pelvic region from impact by a vehicle door in a side impact, it is provided that a nominal break line is formed between the first impact region and the second impact region, along which the first impact region or seat impact region can be separated from the second impact region by a force acting in the vehicle transverse direction.

Abstract: Systems and methods are provided herein for autonomously determining and resolving a customer's perceived discrepancy during a customer service interaction. The method can include receiving an incoming communication from a customer; extracting, by a Natural Language Processing (NLP) device, a perceived state and an expected state of a product or service based on the incoming communication; determining by a discrepancy determination device, a discrepancy between the perceived and expected state of the product or service; verifying, by a rule-based platform, the discrepancy; generating a response based on the discrepancy, the response comprising one or more of: a fact pattern response related to the perceived discrepancy and a confirmation or correction of a verified discrepancy; and outputting, for presentation to the customer, the response.

Abstract: Various embodiments may be generally directed to the use of an adversarial learning framework for persona-based dialogue modeling. In some embodiments, automated multi-turn dialogue response generation may be performed using a persona-based hierarchical recurrent encoder-decoder-based generative adversarial network (phredGAN). Such a phredGAN may feature a persona-based hierarchical recurrent encoder-decoder (PHRED) generator and a conditional discriminator. In some embodiments, the conditional discriminator may include an adversarial discriminator that is provided with attribute representations as inputs. In some other embodiments, the conditional discriminator may include an attribute discriminator, and attribute representations may be handled as targets of the attribute discriminator. The embodiments are not limited in this context.

Abstract: Aspects of the present disclosure relate to a shared image sensor. An example device includes a first lens configured to direct light along a first path in the device, a second lens configured to direct light along a second path in the device, an image sensor configured to receive light from a third path in the device, and an optical element configured to direct the light from the first path to the third path during a first mode. The image sensor is configured to receive the light from the first path during the first mode, and the image sensor is configured to receive the light from the second path during a second mode.

Abstract: In certain embodiments, pre-chat intent prediction and dialogue generation may be facilitated. In some embodiments, a chat initiation request may be obtained from a user. The latest activity information associated with the user may be provided to a prediction model to obtain a first set of predicted intents of the user. For each intent of the first set of predicted intents, a candidate question may be selected from a question set based on the candidate question matching the intent. Within ten seconds of the chat initiation request, the candidate questions may be simultaneously presented on the chat interface. Based on negative feedback obtained via the chat interface with respect to the candidate questions, additional candidate questions matching the second set of predicted intents may be presented on the chat interface. In some embodiments, the negative feedback may be provided to the prediction model to update configurations of the prediction model.

Abstract: Radio frequency shielding within a semiconductor package is described. In one example, a multiple chip package has a digital chip, a radio frequency chip, and an isolation layer between the digital chip and the radio frequency chip. A cover encloses the digital chip and the radio frequency chip.

Abstract: A system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to perform steps of a method. A method can include receiving observations and a corresponding class label, determining a candidate key based on the observations, determining a current memory state of a memory module based on a similarity of stored keys to the candidate key, generating a measurement vector based on the current memory state, concatenating the candidate key and measurement vector to form a state vector, determining, based on the state vector and an action distribution policy, an action of a plurality of actions such that the determined action maximizes an expected reduction in entropy as compared to the remaining actions of the plurality actions, executing the determined action, determining a value of the determined action, and updated, based on the value, the action distribution policy.

Abstract: A system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to perform steps of providing automated natural dialogue with a customer. The system may generate one or more events and commands temporarily stored in queues to be processed by one or more of a dialogue management device, an API server, and an NLP device. The dialogue management device may create adaptive responses to customer communications using a customer context, a rules-based platform, and a trained machine learning model.

Abstract: Systems and methods are provided herein for autonomously determining and resolving a customer's perceived discrepancy during a customer service interaction. The method can include receiving an incoming communication from a customer; extracting, by a Natural Language Processing (NLP) device, a perceived state and an expected state of a product or service based on the incoming communication; determining by a discrepancy determination device, a discrepancy between the perceived and expected state of the product or service; verifying, by a rule-based platform, the discrepancy; generating a response based on the discrepancy, the response comprising one or more of: a fact pattern response related to the perceived discrepancy and a confirmation or correction of a verified discrepancy; and outputting, for presentation to the customer, the response.