Abstract: Disclosed herein are switching or other active FET configurations that implement a branch design with one or more interior FETs of a main path coupled in parallel with one or more auxiliary FETs of an auxiliary path. Such designs include a circuit assembly for performing a switching function that includes a branch with a plurality of auxiliary FETs coupled in series and a main FET coupled in parallel with an interior FET of the plurality of auxiliary FETs. The body nodes of the FETs can be interconnected and/or connected to a body bias network. The body nodes of the FETs can be connected to body bias networks to enable individual body bias voltages to be used for individual or groups of FETs.

Abstract: An online concierge system receives multiple images of an item from a first client device associated with a shopper associated with the online concierge system, in which each of the images of the item is captured from a different angle and/or position and the item is included among an inventory of a warehouse associated with a retailer associated with the online concierge system. Based in part on the images of the item, the online concierge system generates a three-dimensional image of the item, in which the three-dimensional image of the item includes a dimension of the item and/or a color of the item. The online concierge system then sends the three-dimensional image of the item to a second client device associated with a customer of the online concierge system, in which a perspective of the three-dimensional image is modifiable within a display area of the second client device.

Abstract: A stateful chatbot system leverages generative AI to provide an interface by which users can retrieve information from backend IoT databases of a security provider via natural language queries. Upon receiving a natural language query that corresponds to a request for information from the database, the chatbot generates a corresponding database query having a format compatible with the database. The chatbot comprises a generative model adapted to generate database queries based on natural language queries via prompt engineering using natural language and database query pairs. The chatbot queries the database with the generated database query, retrieves results comprising data/metadata that satisfy the query, and generates a summary of the results, both of which it presents as a response to the user's query. The chatbot also has access to a vulnerability database from which it can obtain information about known vulnerabilities documented therein to respond to user queries.

Abstract: The present disclosure relates to determining a first illumination level corresponding to an area based at least on a first illumination detection obtained using a first illumination detector corresponding to a machine. A second illumination level corresponding to the area may be determined based at least on a second illumination detection obtained using a second illumination detector corresponding to the machine. Based at least on the first illumination level and the second illumination level, a scene illumination state of the area may be determined. Based at least on the scene illumination state, one or more lights of the machine may be controlled.

Abstract: An interactive Pepper's Ghost system includes a sensor configured to detect a parameter indicative of an orientation of a handheld device. The Pepper's Ghost system also includes a controller configured to receive, from the sensor, sensor feedback corresponding to the parameter indicative of the orientation of the handheld device. The controller is configured to control a Pepper's Ghost visual effect based on the sensor feedback.

Abstract: A software bill of materials (SBOM) and vulnerability management system (“system”) disclosed herein extracts software component-related identifiers for Internet of Things (IoT) devices using deep packet inspection. The system filters the identifiers by removing identifiers that match a blacklist of identifiers known to not correspond to software components. The system then populates SBOM fields using a database storing the filtered identifiers with a schema that is uniform across SBOM file formats and queries a vulnerability database with software components indicated in the filtered identifiers to identify vulnerabilities for each IoT device for security risk assessment.

Abstract: An online concierge system generates order batches for pickers and offers those order batches. The online concierge system generates a set of candidate order batches, which are subsets of a received set of orders. The online concierge system generates a set of order batch scores for each of a set of candidate pickers, and offers the candidate order batches to the candidate pickers for the candidate pickers to service based on the set of order batch scores. If a candidate picker accepts the offered order batch, the online concierge system identifies candidate order batches with overlapping orders with the order batch accepted by the candidate picker, and rescinds the offer for each of the candidate pickers to service the order batches.

Abstract: An online concierge system iteratively makes a batch of one or more orders available to an increasing number of shoppers to choose to fulfill. Each shopper may choose to accept or reject a batch for fulfillment. To improve batch acceptance and matching between batches and shoppers, the batches are scored with respect to expected resource costs, likelihood of acceptance by the shopper, and/or other quality metrics to iteratively offer the batch to an increasing number of shoppers (prioritizing the scoring factors) until a shopper accepts. The number of shoppers notified of the batch and the frequency that additional shoppers are selected may vary based on characteristics of the batch and likelihood the batch will be accepted by a shopper.

Abstract: When an online system receives an order from a customer, the online system can fulfill the order (for example, using a picker to acquire and deliver the ordered items) and use audio verification to verify delivery. When using audio verification, a customer or picker's mobile device plays verification audio including a verification code specific to the order. If the mobile devices (and, by proxy, the customer and picker) are nearby (for example, within 10 feet), the other party's mobile device can detect the verification audio through a microphone and decode the verification code from the captured audio. In some implementations, audio verification can also be performed using a smart doorbell or smart home without the presence of the customer.

Abstract: An online concierge system receives multiple images of an item from a first client device associated with a shopper associated with the online concierge system, in which each of the images of the item is captured from a different angle and/or position and the item is included among an inventory of a warehouse associated with a retailer associated with the online concierge system. Based in part on the images of the item, the online concierge system generates a three-dimensional image of the item, in which the three-dimensional image of the item includes a dimension of the item and/or a color of the item. The online concierge system then sends the three-dimensional image of the item to a second client device associated with a customer of the online concierge system, in which a perspective of the three-dimensional image is modifiable within a display area of the second client device.

Abstract: When an online system receives an order from a customer, the online system can fulfill the order (for example, using a picker to acquire and deliver the ordered items) and use audio verification to verify delivery. When using audio verification, a customer or picker's mobile device plays verification audio including a verification code specific to the order. If the mobile devices (and, by proxy, the customer and picker) are nearby (for example, within 10 feet), the other party's mobile device can detect the verification audio through a microphone and decode the verification code from the captured audio. In some implementations, audio verification can also be performed using a smart doorbell or smart home without the presence of the customer.