Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

Abstract: Embodiments include semiconductor processing methods to form low-? films on semiconductor substrates are described. The processing methods may include flowing one or more deposition precursors to a semiconductor processing system. The one or more deposition precursors may include a silicon-containing precursor that may be a cyclic compound. The methods may include generating a deposition plasma from the one or more deposition precursors. The methods may include depositing a silicon-and-carbon-containing material on the substrate from plasma effluents of the deposition plasma. The silicon-and-carbon-containing material as-deposited may be characterized by a dielectric constant less than or about 3.0.

Abstract: Embodiments include semiconductor processing methods to form low-K films on semiconductor substrates are described. The processing methods may include flowing one or more deposition precursors to a semiconductor processing system, wherein the one or more deposition precursors include a silicon-containing precursor. The silicon-containing precursor may include a carbon chain. The methods may include generating a deposition plasma from the one or more deposition precursors. The methods may include depositing a silicon-and-carbon-containing material on the substrate from plasma effluents of the deposition plasma. The silicon-and-carbon-containing material as-deposited may be characterized by a dielectric constant less than or about 3.0.

Abstract: Exemplary semiconductor processing methods may include providing one or more deposition precursors to a processing region of a semiconductor processing chamber. A semiconductor substrate may be positioned within the processing region. The methods may include forming a layer of low dielectric constant material on the semiconductor substrate. The methods may include purging the processing region of the one or more deposition precursors. A plasma power may be maintained at less than or about 750 W while purging the processing region. The methods may include forming an interface layer on the layer of low dielectric constant material. The methods may include forming a cap layer on the interface layer.

Abstract: Disclosed is use of 5?-androst-3?,5,6?-triol or an analogue, a deuterated compound or a pharmaceutically acceptable salt thereof in the manufacture of a medicament for the treatment of cerebral small vessel disease in a patient. The cerebral small vessel disease is preferably cerebral microbleed. The cerebral microbleed is spontaneous cerebral microbleed, drug-related cerebral microbleed, or traumatic cerebral microbleed. The present invention demonstrates that these compounds significantly enhance the clearance of extravascular hemoglobin, and thus can be used to treat cerebral small vessel disease.

Abstract: Apparatuses and methods for providing resources are provided that include receiving power statuses of resources of a system capable of providing the resources; quantifying the power statuses of the resources; calculating an available soft capacity of the system based on the quantified power statuses and a total capacity of the system; and providing an assigning amount of the resources beyond the calculated available soft capacity to one or more users.

Abstract: System and methods may include receiving a request for assigning resources to a first application associated with a first entity, the first application having a plurality of levels of performance each corresponding to a different power consumption; and determining a particular level of performance of the first application to run on the resource under a first constraint that a sum of a power consumption of the first application running at the particular level of performance and power consumptions of one or more other resources running other applications associated with the first entity is less than or equal to a power budget associated with the first entity.

Abstract: Systems and methods for a hybrid system-on-chip usable for predicting performance and power requirements of a host server include a big cores module, including central processing units, for receiving and pre-processing performance and power metrics data of the host server and to allocate computing resources, a small cores module, including massively parallel processing units, for mapping each instance associated with host server in the performance and power metrics data to a corresponding massively parallel processing unit based on the allocated computing resources for a per-instance metrics calculation, and an artificial intelligence (AI) accelerator for calculating performance and power prediction results based on the per-instance calculations from the small cores module.

Abstract: A distributed data storage system may implement determining indexing progress for a table stored in the distributed data storage system. A table may be stored in multiple table partitions. When a secondary index is created for the table, each partition may independently index the items stored within the table partition in order to identify those items in the partition that should be stored in the secondary index. During creation of the secondary index, creation progress points that indicate the progress of the indexing across the table partitions may be determined. The creation progress points may be provided via a programmatic, textual, or graphical interface to the distributed data storage system.

Abstract: One or more table partitions may communicate with an index partition that may be a master of a replication group. A communications channel may exist between table partitions and the index partition. Upon splitting the index partition, communications between the table partitions and the index partition may be suspended. Upon completion of the split, communications may be reestablished between the table partitions and a partition, of the replication group of index partitions, designated to be a master following the split. Messages accumulated by the table partitions during the split may be sent to the index partition upon reestablishing communications.

Abstract: A method and device for allocating a distributed lock is provided. A globally unique service process ID (SPI) is introduced for each distributed application service process while guaranteeing correctness of a distributed lock, and the SPI is used to directly manage ownership of the distributed lock. The service replacement process sends to the server a request for inheriting ownership of the distributed lock before the lifecycle of the lock file expires, the inherit request including the SPI.

Abstract: Embodiments of the present disclosure provide a method comprising: adding a second set of one or more servers to a first set of servers of a consensus system to form an expanded set of servers, performing a capacity-expanding operation on one of the second set of one or more servers. The capacity-expanding operation comprises: pausing a service process related to distributed services, updating configuration information of the first set of servers in response to the second set of one or more servers being added, and resuming the service process and initiating master server election for the expanded set of servers, wherein one of the expanded set of servers is elected as a master server, the rest of the expanded set of servers are considered as slave servers.

Abstract: Apparatuses and methods for providing resources are provided that include receiving power statuses of resources of a system capable of providing the resources; quantifying the power statuses of the resources; calculating an available soft capacity of the system based on the quantified power statuses and a total capacity of the system; and providing an assigning amount of the resources beyond the calculated available soft capacity to one or more users.

Abstract: System and methods may include receiving a request for assigning resources to a first application associated with a first entity, the first application having a plurality of levels of performance each corresponding to a different power consumption; and determining a particular level of performance of the first application to run on the resource under a first constraint that a sum of a power consumption of the first application running at the particular level of performance and power consumptions of one or more other resources running other applications associated with the first entity is less than or equal to a power budget associated with the first entity.

Abstract: Apparatus and methods are provided for improving thermal control, including collecting data of a plurality of systems, each of the plurality of systems including at least one first cooling element and at least one first heat-generating element; conducting a first simulation using a simulation model based on the collected data to generate a first set of simulation results; conducting a first training on a control system using the first set of simulation results to obtain a first trained control system; and using the first trained control system to monitor a field system with a space having at least one second cooling element and at least one second heat-generating element and to control the at least one second cooling element and the at least one second heat-generating element.

Abstract: Methods and apparatus for token-based admission control for replicated writes are disclosed. Data objects are divided into partitions, and corresponding to each partition, at least a master replica and a slave replica are stored. A determination as to whether to accept a write request directed to the partition is made based at least in part on one or more of (a) available throughput capacity at the master replica, and (b) an indication, obtained using a token-based protocol, of available throughput capacity at the slave replica. If the write request is accepted, one or more data modification operations are initiated.

Abstract: Providers of web services and other types of software as a service may be subject to service-level agreements requiring that response times be within a defined range. For efficiency, multiple services may be hosted on the same set of computing nodes, which may jeopardize adherence to service-level agreements. A control system may involve classifying service requests and determining desired values for measurements such as latency. An error value may be calculated based on the difference between measured and desired values. A controller may adjust a rate of capacity utilization for the computing nodes based on the current error, a history of past errors, and a prediction of future errors.