Abstract: Described are systems and method directed to generation of a dimensionally accurate three-dimensional (“3D”) model of a body, such as a human body, based on two-dimensional (“2D”) images of that body. A user may use a 2D camera, such as a digital camera typically included in many of today's portable devices (e.g., cell phones, tablets, laptops, etc.) and obtain a series of 2D body images of their body from different views with respect to the camera. The 2D body images may then be used to generate a plurality of predicted body parameters corresponding to the body represented in the 2D body images. Those predicted body parameters may then be further processed to generate a dimensionally accurate 3D model or avatar of the body of the user.

Abstract: Methods for securing image, video and/or audio media data captured by a media recording device are disclosed. Various embodiments may include determining whether media data captured by the media recording device should be secured in response to the media recording device activating a media recording application, obtaining an encryption key in response to determining that media data captured by the media recording device should be secured, encrypting media data (e.g., image, video and/or audio data) captured by the media recording device using the obtained encryption key, and storing the encrypted media data. In some embodiments, determining that media data should be secured and obtaining the encryption key may be based on user inputs in response to prompts. In some embodiments, determining that media data should be secured may be based on whether the media recording device satisfies a geo-location criterion and the encryption key may be provided by a server.

Abstract: A method for producing a bonded magnet, comprising: (i) low-shear compounding of a thermoplastic polymer and magnetic particles to form an initial homogeneous mixture thereof; (ii) feeding the initial homogeneous mixture into a plasticator comprising a low-shear single screw rotating unidirectionally toward a die orifice and housed within a heated barrel to result in heating of the initial homogeneous mixture until the thermoplastic polymer melts and forms a further homogeneous mixture, wherein said further homogeneous mixture is transported within threads of the single screw towards the die orifice and exits the die orifice as a solid pellet; (iii) conveying the solid pellet into a mold and compression molding the pellet in the mold, to form the bonded magnet, wherein the bonded magnet possesses a magnetic particle loading of at least 80 vol % and exhibits one or more magnetic properties varying by less than 5% throughout the bonded magnet.

Abstract: A three dimensional neural network accelerator that includes a first neural network accelerator tile that includes a first transmission coil, and a second neural network accelerator tile that includes a second transmission coil, wherein the first neural network accelerator tile is adjacent to and aligned vertically with the second neural network accelerator tile, and wherein the first transmission coil is configured to wirelessly communicate with the second transmission coil via inductive coupling.

Abstract: The present invention relates to a method of validating a memory device. The method includes validating a second memory device based on one or more first microcode instructions stored in a validated predetermined part of a first memory device to detect the operational status of the second memory device. Further, the method includes receiving one or more second microcode instructions upon validating the second memory device. Finally, validating the first memory device based on the one or more second microcode instructions stored in the second memory device to detect the operational status of the first memory device.

Abstract: The present invention relates to a method of validating a memory device. The method includes validating a second memory device based on one or more first microcode instructions stored in a validated predetermined part of a first memory device to detect the operational status of the second memory device. Further, the method includes receiving one or more second microcode instructions upon validating the second memory device. Finally, validating the first memory device based on the one or more second microcode instructions stored in the second memory device to detect the operational status of the first memory device.

Abstract: A digital assistant platform may receive a query relating to a target data file. The target data file may be associated with a standardized data set. The standardized data set may include data files that are aggregated based on data elements associated with the data files, and may be configured to enable a plurality of services. The digital assistant platform may extract, based on the query, one or more keywords, and identify an intent classification and an entity associated with the query. The digital assistant platform may analyze the plurality of services to identify a target service to enable, and analyze the data elements to identify the target data file. The digital assistant platform may determine, using the target service, analytical information associated with a data element of the target data file, and generate a response to the query based on the analytical information.

Abstract: A device may receive a data input that is associated with an event. The device may parse the data input to identify an input value that is associated with the event. The device may determine a probability that the input value corresponds to a feature of the event based on a configuration of the input value. The device may classify the input value as being associated with an element of the event based on the probability. The device may determine a rule profile of the input value based on the feature and the element. The device may determine a profile score associated with the data input based on the rule profile. The device may ingest, based on the profile score, the data input into a data structure. The device may determine a validation score based on a random factorization analysis of the rule profile and the input value.

Abstract: Described are systems and methods directed to generation of a personalized three-dimensional (“3D”) body model of a body, such as a human body, based on two-dimensional (“2D”) images of that body and the generation and presentation of predicted personalized 3D body models of the body when one or more body measurements (e.g., body fat, body weight, muscle mass) are changed. For example, a user may provide a target body measurement value and the implementations will generate one or more predicted personalized 3D body models representative of a predicted appearance of the body with the target body measurement value.

Abstract: Methods, systems, and apparatus, including computer-readable media, are described for a hardware circuit configured to implement a neural network. The circuit includes multiple super tiles. Each super tile includes a unified memory for storing inputs to a neural network layer and weights for the layer. Each super tile includes multiple compute tiles. Each compute tile executes a compute thread that is used to perform the computations to generate an output for the neural network layer. Each super tile includes arbitration logic coupled to the unified memory and each compute tile. The arbitration logic is configured to: pass inputs stored in the unified memory to the compute tiles; pass weights stored in the unified memory to the compute tiles; and pass, to the unified memory, the output generated for the layer based on computations performed at the compute tiles using the inputs and the weights for the layer.

Abstract: Methods, systems and computer program products are provided for automated runtime configuration for dataflows to automatically select or adapt a runtime environment or resources to a dataflow plan prior to execution. Metadata generated for dataflows indicates dataflow information, such as numbers and types of sources, sinks and operations, and the amount of data being consumed, processed and written. Weighted dataflow plans are created from unweighted dataflow plans based on metadata. Weights that indicate operation complexity or resource consumption are generated for data operations. A runtime environment or resources to execute a dataflow plan is/are selected based on the weighted dataflow and/or a maximum flow. Preferences may be provided to influence weighting and runtime selections.

Abstract: Apparatus and methods for processing neural network models are provided. The apparatus can comprise a plurality of identical artificial intelligence processing dies. Each artificial intelligence processing die among the plurality of identical artificial intelligence processing dies can include at least one inter-die input block and at least one inter-die output block. Each artificial intelligence processing die among the plurality of identical artificial intelligence processing dies is communicatively coupled to another artificial intelligence processing die among the plurality of identical artificial intelligence processing dies by way of one or more communication paths from the at least one inter-die output block of the artificial intelligence processing die to the at least one inter-die input block of the artificial intelligence processing die.

Abstract: Methods for securing image, video and/or audio media data captured by a media recording device are disclosed. Various embodiments may include determining whether media data captured by the media recording device should be secured in response to the media recording device activating a media recording application, obtaining an encryption key in response to determining that media data captured by the media recording device should be secured, encrypting media data (e.g., image, video and/or audio data) captured by the media recording device using the obtained encryption key, and storing the encrypted media data. In some embodiments, determining that media data should be secured and obtaining the encryption key may be based on user inputs in response to prompts. In some embodiments, determining that media data should be secured may be based on whether the media recording device satisfies a geo-location criterion and the encryption key may be provided by a server.

Abstract: Described are systems and methods directed to generation of a personalized three-dimensional (“3D”) body model of a body, such as a human body, based on two-dimensional (“2D”) images of that body and the generation and presentation of predicted personalized 3D body models of the body when one or more body measurements (e.g., body fat, body weight, muscle mass) are changed. For example, a user may provide a target body measurement value and the implementations will generate one or more predicted personalized 3D body models representative of a predicted appearance of the body with the target body measurement value.

Abstract: The present application relate to a process for preparation of 4-Methylene tetrahydrofuran compound of formula II, which is useful as an intermediate for the preparation of halichondrin B analogues such as Eribulin.

Abstract: A DC-DC converter operates in a burst mode having at least one charge cycle with a charging phase followed by a discharging phase. A charging phase is terminated when an inductor current flowing through an inductance connected to the DC-DC converter reaches a compensated peak-current threshold, wherein the compensated peak-current threshold compensates for charging-phase loop delay. A discharging phase is terminated when the inductor current reaches a compensated valley-current threshold, wherein the compensated valley-current threshold compensates for discharging-phase loop delay.

Abstract: A DC-DC converter operates in a burst mode having at least one charge cycle with a charging phase followed by a discharging phase. A charging phase is terminated when an inductor current flowing through an inductance connected to the DC-DC converter reaches a compensated peak-current threshold, wherein the compensated peak-current threshold compensates for charging-phase loop delay. A discharging phase is terminated when the inductor current reaches a compensated valley-current threshold, wherein the compensated valley-current threshold compensates for discharging-phase loop delay.

Abstract: A test automation platform may receive a test case for testing a data ingestion pipeline. The test automation platform may determine a test intent of the test case using a test intent identification model. The test automation platform may determine a type of entity associated with the data ingestion pipeline that the test case is to test using a test entity identification model. The test automation platform may generate a prediction of a data ingestion scenario for which the test case is to be applied based at least in part on the test intent of the test and the type of entity. The test automation platform may generate a mapping file representing the prediction of the data ingestion scenario. The test automation platform may execute, using test cases of the mapping file, a set of tests on a new data ingestion pipeline.

Abstract: A test automation platform may receive a test case for testing a data ingestion pipeline. The test automation platform may determine a test intent of the test case using a test intent identification model. The test automation platform may determine a type of entity associated with the data ingestion pipeline that the test case is to test using a test entity identification model. The test automation platform may generate a prediction of a data ingestion scenario for which the test case is to be applied based at least in part on the test intent of the test and the type of entity. The test automation platform may generate a mapping file representing the prediction of the data ingestion scenario. The test automation platform may execute, using test cases of the mapping file, a set of tests on a new data ingestion pipeline.

Abstract: Described are systems and methods directed to generation of a personalized three-dimensional (“3D”) body model of a body, such as a human body, based on two-dimensional (“2D”) images of that body and the generation and presentation of predicted personalized 3D body models of the body when one or more body measurements (e.g., body fat, body weight, muscle mass) are changed. For example, a user may provide a target body measurement value and the implementations will generate one or more predicted personalized 3D body models representative of a predicted appearance of the body with the target body measurement value.