Abstract: An electronic device (400) on an artificial intelligence (AI) platform side, the AI platform is capable of interacting with an application side to perform at least one AI intelligentialization process with the same application configuration, the electronic device (400) includes a processing circuitry (402) which is configured to: receive a configuration request for the at least one AI intelligentialization process from an application side, the configuration request including information indicating the application configuration; and when the application configuration is satisfied, assign the application configuration for usage by the at least one AI intelligentialization process during execution.

Abstract: Rendering systems that can use combinations of rasterization rendering processes and ray tracing rendering processes are disclosed. In some implementations, these systems perform a rasterization pass to identify visible surfaces of pixels in an image. Some implementations may begin shading processes for visible surfaces, before the geometry is entirely processed, in which rays are emitted. Rays can be culled at various points during processing, based on determining whether the surface from which the ray was emitted is still visible. Rendering systems may implement rendering effects as disclosed.

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: Disclosed are methods and systems to improve the time synchronization of power distribution systems and/or other distributed device networks. The disclosure relates to nesting selection algorithms to elect a grand master clock from among groups of devices in a network.

Abstract: A method, executable by a processor, of generating a 3D digital model associated with a given tooth is disclosed. The method includes obtaining a preliminary root 3D digital model of a root portion the given tooth, and then generating an augmented root 3D digital model therefrom by obtaining data of a longitudinal axis of the given tooth, and data indicative of a tooth gingiva segmentation contour between the crown and root portions; determining for each root vertex, a respective new position relative to the longitudinal axis in which the respective new position is defined by a shift distance value and a shift direction vector; moving each of the root vertices to their respective new position by applying their respective shift distance values along their respective shift direction vector; and storing the augmented root 3D digital model for determining an orthodontic treatment for the subject.

Abstract: A system includes primary and secondary devices (e.g., camera controllers that drive voice coil motors) each having respective outputs and a communication link. The primary device includes first and second hardware timers, each of which expires at a time derived from a periodic control loop trigger. At first timer expiration, the primary transmits first updated values to the secondary. At second timer expiration, primary device hardware picks up and applies second updated values to the primary device outputs. In response to receiving the first updated values from the primary device, the secondary device applies the received first updated values to its outputs. The primary/secondary device combination provide a sufficient number of total outputs that they could not individually provide and further synchronize the outputs with small skew through the timers, which are programmable to also accommodate processing of inputs (e.g., from voice coil motor sensors) to compute the outputs.

Abstract: Disclosed are techniques for a power management integrated circuit (PMIC) to support a power-up sequence from a powered-down state to a powered-up state when both a main supply voltage and a backup supply voltage are present or when only the backup supply voltage is present. The PMIC may monitor the two supply voltages to identify the supply voltages that are present. The PMIC may be configured with a power-up initialization mode of operation through an EFUSE/MTP register, including a first bit to control power up of a voltage regulator of the PMIC with the main supply voltage or the backup supply voltage. Another bit may control power up of the voltage regulator with the backup supply voltage in the dual-supply or the single-supply configuration. The PMIC may execute one of four power-up sequences based on the monitored status of the supply voltages and the configured power-up initialization mode of operation.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using generative design processes. A method includes obtaining one or more load cases and one or more design criteria for a modeled object, the one or more design criteria comprising a build material strength model indicating strength relationships between thickness of an object feature and build angle for that object feature resulting from additive manufacturing; iteratively modifying a three dimensional shape of the modeled object in accordance with the one or more design criteria and the one or more load cases, including applying the strength relationships between the thickness of the object feature and the build angle for that object feature on a per-element basis during numerical simulation of the modeled object; and providing the three dimensional shape of the modeled object for use in manufacturing a physical structure.

Abstract: A system includes a video device for capturing, at a viewing time, a first video image corresponding to a foundation scene at a setting, the foundation scene viewed at the viewing time from a vantage position. A memory stores a library of image data including media generated at a time prior to the viewing time. A vantage position monitor tracks the vantage position and generating vantage position of a human viewer. A digital video data controller selects from the image data in the library, at the viewing time and based on the vantage position data, a plurality of second images corresponding to a modifying scene at the setting, the modifying scene further corresponding to the vantage position. A combiner combines the first video image and the plurality of second images to create a composite image for display.

Abstract: An electronic device is disclosed. The electronic device comprises a first clock configured to operate at a frequency. First circuitry of the electronic device is configured to synchronize with the first clock. Second circuitry is configured to determine a second clock based on the first clock. The second clock is configured to operate at the frequency of the first clock, and is further configured to operate with a phase shift with respect to the first clock. Third circuitry is configured to synchronize with the second clock.

Abstract: A computer-implemented method for designing a patient-specific orthopedic implant can include creating a user account associated with a patient. A patient-specific orthopedic implant can be designed based on patient data and imaging data. A healthcare provider can provide feedback for a design of the patient-specific orthopedic implant, treatment protocol, or other aspects of treatment. The patient can provide data and feedback.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to optimize a guard band of a hardware resource. An example apparatus includes at least one storage device, and at least one processor to execute instructions to identify a phase of a workload based on an output from a machine-learning model, the phase based on a utilization of one or more hardware resources, and based on the phase, control a guard band of a first hardware resource of the one or more hardware resources.

Abstract: The analysis apparatus includes a calculation unit configured to calculate a transformation parameter used to transform a reference model indicating a three-dimensional shape of a target object into a three-dimensional shape indicated by three-dimensional sensing data indicating a result of sensing a target object after an elapse of a predetermined period of time since the reference model is generated; an update unit configured to update the reference model using the transformation parameter and three-dimensional sensing data; and a communication unit configured to transmit difference data between vertices of a reference model after the update and vertices of a reference model before the update, difference data between a representative point of the reference model after the update having the transformation parameter and a representative point of the reference model after the update, and a transformation parameter to a terminal device that shares a reference model.

Abstract: A system for processing patient data associated with a joint of a patient. The system comprising a computing device executing instructions to generate a 3D patient bone model of the joint in a non-weighted pose. The instructions rearrange 3D first and second bone models in order to mimic a weighted pose of the joint of the patient from a 2D image of the joint of the patient in a weighted pose by performing the steps of: generating a plurality of 2D projections of poses of the 3D patient bone model; comparing the plurality of 2D projections to contour lines of the first bone and the second bone in the 2D image; identifying particular 2D projections that best-fit a shape and size of the contour lines; and arranging the 3D first and second bone models relative to each other according to orientations represented by the particular 2D projections that were identified.

Abstract: The present disclosure provides a method for syncing data of a computing task across a plurality of groups of computing nodes, each group comprising a set of computing nodes A-D, a set of intra-group interconnects that communicatively couple computing node A with computing nodes B and C and computing node D with computing nodes B and C, and a set of inter-group interconnects that communicatively couple a computing node A of a first group of the plurality of groups with a computing node A of a second group neighboring the first group, a computing node B of the first group with a computing node B of the second group, a computing node C of the first group with the computing node C of the second group, and a computing node D of the first group with a computing node D of the second group, the method comprising: syncing across a first dimension of computing nodes using a first set of ring connections, wherein the first set of ring connections are formed using inter-group and intra-group interconnects that communica

Abstract: The present disclosure provides techniques for automatically modifying shape features related to overhangs such that support structures can be reduced or avoided. In an example, a shape modification processing device may obtain an initial shape and relevant production information (e.g., overhang angle threshold). The shape modification processing device may modify the shape to improve various aspects of production, including reduction or removal of the need for support materials or structures during additive manufacturing, with considerations that allow the modified portion (e.g., added features) be accessible for removal by subtractive manufacturing. For example, the shape modification processing device may modify a model to reduce or remove support structures needed during production. The added features may later be removed by subtractive manufacturing to restore any functional or desired shape.

Abstract: The disclosure relates to technology for generating multi-phase signals. An apparatus includes 2{circumflex over (?)}n phase signal generation stages. The apparatus also includes a controller configured to provide a mode input of each of the 2{circumflex over (?)}n stages with an active periodic binary signal with remaining inputs of each of the 2{circumflex over (?)}n stages provided with another periodic binary signal to collectively generate a 2{circumflex over (?)}n phase signal in a first mode.

Abstract: One embodiment provides a graphics processor comprising an interface to a system interconnect and a graphics processor coupled to the interface, the graphics processor comprising circuitry configured to compact sample data for multiple sample locations of a pixel, map the multiple sample locations to memory locations that store compacted sample data, the memory locations in a memory of the graphics processor, apply lossless compression to the compacted sample data, and update a compression control surface associated with the memory locations, the compression control surface to specify a compression status for the memory locations.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for training and utilizing generative machine learning models to generate embeddings from phenomic images (or other microscopy representations). For example, the disclosed systems can train a generative machine learning model (e.g., a masked autoencoder generative model) to generate predicted (or reconstructed) phenomic images from masked version of ground truth training phenomic images. In some cases, the disclosed systems utilize a momentum-tracking optimizer while reducing a loss of the generative machine learning model to enable efficient training on large scale training image batches. Furthermore, the disclosed systems can utilize Fourier transformation losses with multi-stage weighting to improve the accuracy of the generative machine learning model on the phenomic images during training.

Abstract: A system-on-chip (SoC) may comprise a semi-conductor substrate; a first circuitry, disposed on the semi-conductor substrate, provided for a first neural processing unit (NPU) configured to perform operations of an artificial neural network model (ANN); a second circuitry, disposed on the semi-conductor substrate, provided for a second NPU configured to perform operations of an ANN model, each of the first NPU and the second NPU including a plurality of processing elements (PEs), the plurality of PEs including an adder, a multiplier, and an accumulator; and a clock signal supply circuit, disposed on the semi-conductor substrate, configured to output one or more clock signals, wherein a first clock signal among the one or more clock signals may be supplied to the first NPU, and a second clock signal among the one or more clock signals may be supplied to the second NPU.