Abstract: A system for ANN training through processing power of parked vehicles. The system can include a master computing device having a controller configured to control training of an ANN. The training can be performed at least partially in separate parts by computing devices of parked vehicles. The controller can be configured to separate computing tasks of training the ANN into separated tasks. Also, the controller can be configured to assign at least some of the separated tasks to selected computing devices of parked vehicles. The controller can also be configured to receive and assemble results of the separated tasks to train the ANN. The controller can also be configured to train the ANN according to the results. The master computing device can be configured to send the assigned tasks to the selected devices of the vehicles as well as receive, from the selected devices, the results of the assigned tasks.

Abstract: Methods, systems, and apparatuses related to edge processing of sensor data using a neural network to reduce network traffic to and/or from a server. In one approach, a cloud server processes sensor data from a vehicle using an artificial neural network (ANN). The ANN has several layers. Based on analyzing at least one characteristic of the sensor data received from the vehicle and/or a context associated with processing the sensor data, the cloud server determines to send one or more of the layers of the ANN for edge processing on the vehicle itself. In other cases, the cloud server decides to send the one or more layers to an edge server device located on a communication path between the vehicle and the cloud server. The edge processing reduces network data traffic.

Abstract: Systems and methods for selecting content based on an event associated with a device identifier are provided. One or more processors can receive a request to serve content. The processors can identify a device identifier associated with the request. The processors can determine, from the device identifier, an event for which to serve content. The processors can determine, from the request, a length of time between a time the request to serve content is received and a time at which the event is scheduled to occur. The processors can select, based on the determined length of time and event parameters associated with the event, content for display and provide the selected content for display at a computing device associated with the device identifier.

Abstract: Systems, methods and apparatuses of radar Electronic Control Units (ECUs) of autonomous vehicles. A radar ECU can include: a memory configured to store a radar image and an Artificial Neural Network (ANN); an inference engine configured to use the (ANN) to analyze the radar image and generate inference results; and a communication interface coupled to a computer system of a vehicle to implement an advanced driver assistance system to operate the controls according to the inference results and a sensor data stream generated by sensors configured on the vehicle.

Abstract: A controller of a vehicle detects persons that are approaching the vehicle and uses sensors to collect data regarding the persons to determine whether a security risk exists. In one approach, the collected data is used to determine whether each person is associated with the vehicle. In response to determining that at least one of the persons is unknown, a security risk is evaluated based on data from monitoring of the environment of the vehicle. In response to determining that a security risk score exceeds a threshold, one or more actions for the vehicle are performed to make the vehicle more secure.

Abstract: A vehicle having one or more cameras, configured to record one or more images of a driver of the vehicle. The camera(s) can be configured to send biometric image data derived from the image(s). The vehicle can include a computing system configured to receive the biometric data and to determine a risk score of the driver based on the received biometric data and an AI technique, such as an ANN or a decision tree. The received biometric data or a derivative thereof can be input for the AI technique. The computing system can also be configured to transmit the risk score of the driver to the customer so that the customer can decide whether to book the vehicle for a ride.

Abstract: Systems, methods and apparatus of intelligent write-amplification reduction for data storage devices configured on autonomous vehicles. For example, a data storage device of a vehicle includes: one or more storage media components; a controller configured to store data into and retrieve data from the one or more storage media components according to commands received in the data storage device; an address map configured to map between: logical addresses specified in the commands received in the data storage device, and physical addresses of memory cells in the one or more storage media components; and an artificial neural network configured to receive, as input and as a function of time, operating parameters indicative a data access pattern, and generate, based on the input, a prediction to determine an optimized data placement scheme. The controller is configured to adjust the address map according to the optimized data placement scheme.

Abstract: The present invention relates to treatment compositions containing polymer systems that provide stability and benefit agent deposition as well as methods of making and using same. Such treatment compositions may be used for example as through the wash and/or through the rinse fabric enhancers as well as unit dose treatment compositions.

Abstract: Systems, methods and apparatus of communications with a data storage device in neural network computations. For example, a vehicle can have a set of sensors configured to generate a sensor data stream for predictive Maintenance. One or more processors of the vehicle generates inputs to artificial neurons based on the sensor data. The inputs are written into the data storage device, which is configured with a neural network accelerator and stores model data of an artificial neural network (ANN). The neural network accelerator applies the inputs to the ANN to generate outputs. The data storage device reports the availability of the outputs (e.g., using a response to the request to write the inputs into the data storage device). The processor(s) of the vehicle can selectively read the outputs from the data storage device and/or request the data storage device to store the outputs from buffer to non-volatile memory.

Abstract: Systems, methods and apparatuses to classify and/or control content passing through a memory device. For example, a portion of a media stream received from a content source can be buffered in a memory device a predetermined time before presentation. An artificial neural network (ANN) in the memory device can identify a region in the buffered portion and analyze the region to determine a classification of content in the region. Within the memory device, the content in the region can be transformed according to a preference specified for the classification. For example, unwanted or objectionable content can be masked, distorted, skipped, replaced, and/or filtered. A modified version of the portion is generated from transforming the content in the region as output for presentation.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for distributing content based on context are disclosed. In one aspect, a method includes identifying, in a single resource, multiple different content item slots that are available for presentation of multiple different content items. A determination is made that a first content item slot is located in a first portion of the single resource, and that a second content item slot is located in a second different portion of the resource. A first content item is selected for presentation in the first content item slot based on terms that correspond to a first topic of the first portion of the resource. A second content item is selected for presentation in the second content item slot based on terms that correspond to a second topic of the second portion of the resource.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for distributing content based on context are disclosed. In one aspect, a method includes identifying, in a single resource, multiple different content item slots that are available for presentation of multiple different content items. A determination is made that a first content item slot is located in a first portion of the single resource, and that a second content item slot is located in a second different portion of the resource. A first content item is selected for presentation in the first content item slot based on terms that correspond to a first topic of the first portion of the resource. A second content item is selected for presentation in the second content item slot based on terms that correspond to a second topic of the second portion of the resource.

Abstract: An emergency lighting system that includes a storage device, an emergency lighting device, an area control device and an external device. The emergency lighting device includes a light, a first controller having a first electronic processor configured to perform a self-diagnostic test, and a first input/output (I/O) device configured to transmit data associated with the self-diagnostic test. The area control device includes a second I/O device configured to receive data associated with the first self-diagnostic test form the first I/O device and transmit the data associated with the self-diagnostic test to the storage device.

Abstract: A system for ANN training through processing power of parked vehicles. The system can include a master computing device having a controller configured to control training of an ANN. The training can be performed at least partially in separate parts by computing devices of parked vehicles. The controller can be configured to separate computing tasks of training the ANN into separated tasks. Also, the controller can be configured to assign at least some of the separated tasks to selected computing devices of parked vehicles. The controller can also be configured to receive and assemble results of the separated tasks to train the ANN. The controller can also be configured to train the ANN according to the results. The master computing device can be configured to send the assigned tasks to the selected devices of the vehicles as well as receive, from the selected devices, the results of the assigned tasks.

Abstract: Systems and methods for assigning personalities to autonomous vehicles are disclosed. In one embodiment, a method is disclosed comprising receiving data from an autonomous vehicle; generating a vector representing the autonomous vehicle based on the data; classifying the vector into one or more personalities; receiving a search query from a user; identifying one or more autonomous vehicles responsive to the search query based on personalities assigned to the one or more autonomous vehicles, the one or more autonomous vehicles including the autonomous vehicle; and transmitting the one or more autonomous vehicles to the user.

Abstract: A device having a plurality of pins configured to connect circuits within an integrated circuit package to circuits outside of the integrated circuit package. A driver enclosed within the package is programmable to generate a spread spectrum signal to represent data being transmitted from a pin of the device. Frequency distribution of the signal spreading over a bandwidth in a frequency domain can be programmed to customize the electromagnetic emission caused by the communication of data through the pin. The frequency spreading can be programmed to reduce energy consumption, electromagnetic interference, and/or errors in receiving the data transmitted via the pin. The settings can be programmed into registers enclosed in the integrated circuit package to control the driver and/or dynamically adjusted using an artificial intelligent engine to optimize a cost function.

Abstract: A device having a plurality of pins configured to connect circuits within an integrated circuit package to circuits outside of the integrated circuit package. A driver, enclosed within the package, is programmable to adjust the strength, delay, and/or slew rate of the signals driven onto a pin of the device to represent a predetermined bit of data. Such aspects of the signals driven by the driver according to the programmed settings can be adjusted to reduce energy consumption, electromagnetic interference, and/or errors in receiving the data transmitted via the pin. The settings can be programmed into registers enclosed in the integrated circuit package to control the driver and/or dynamically adjusted using an artificial intelligent engine to optimize a cost function.

Abstract: A device having a plurality of pins configured to connect circuits within an integrated circuit package to circuits outside of the integrated circuit package. Circuitry in the device is configured to automatically adapt settings of a pin driver to a system in which the device is installed. For example, the driving strength of the pin driver can be automatically reduced to an optimized level that is just above a level that can cause errors in communications. For example, the delay of a signal driving by the pin driver can be set to a midpoint between an upper boundary of delays between failed and successful transmissions and a lower boundary of delays between successful and failed transmissions.

Abstract: Methods, systems, and apparatuses related to edge processing of sensor data using a neural network to reduce network traffic to and/or from a server. In one approach, a cloud server processes sensor data from a vehicle using an artificial neural network (ANN). The ANN has several layers. Based on analyzing at least one characteristic of the sensor data received from the vehicle and/or a context associated with processing the sensor data, the cloud server determines to send one or more of the layers of the ANN for edge processing on the vehicle itself. In other cases, the cloud server decides to send the one or more layers to an edge server device located on a communication path between the vehicle and the cloud server. The edge processing reduces network data traffic.

Abstract: Systems, methods and apparatus of optimizing neural network computations of predictive maintenance of vehicles. For example, a data storage device of a vehicle includes: a host interface configured to receive a sensor data stream from at least one sensor configured on the vehicle; at least one storage media component having a non-volatile memory; and a controller. The non-volatile memory is configured into multiple partitions (e.g., namespaces) having different sets of memory operation settings configured for different types of data related to an artificial neural network (ANN). The partitions include a model partition configured to store model data of the ANN. The sensor data stream is applied in the ANN to predict a maintenance service of the vehicle. The memory units of the model partition can be configured for read, infrequent updates, improved storage capacity, and/or for access in parallel with input/output for the ANN.