Abstract: A method performed by a Cloud Access Security Broker (CASB) service includes scanning data stored in one of a cloud provider and a Software-as-a-Service (SaaS) application, wherein the data is for a user associated with a company of a plurality of companies; detecting an incident in a file or email in the data during the scanning; maintaining details of the incident in an in-memory data store, including a current snapshot of the file or email; and providing a notification to the tenant of the incident. The method can further include, subsequent to the incident and while the file or email is being updated, updating the details of the incident in the in-memory data store.

Abstract: A solid ion conductive material can include a complex metal halide. The complex metal halide can include at least one alkali metal element. In an embodiment, the solid ion conductive material including the complex metal halide can be a single crystal. In another embodiment, the ion conductive material including the complex metal halide can be a crystalline material having a particular crystallographic orientation. A solid electrolyte can include the ion conductive material including the complex metal halide.

Abstract: A solid electrolyte material can include a halide-based material having a crystalline structure including a disorder. In an embodiment, the solid electrolyte material can include a crystalline structure include stacking faults. In another embodiment, the solid electrolyte material can include a crystalline phase including a crystalline structure represented by a space group of the hexagonal crystal system or a space group of a rhombohedral lattice system. In another embodiment, the solid electrolyte material can include a crystalline phase including a crystalline structure represented by a monoclinic space group and a unit cell containing a reduced number of halogen atoms.

Abstract: Mat locking pins include a pin body and a wheel housed within the pin body, the wheel configured to be movable from a first position to a second position, wherein in the first position the wheel is housed within the pin body and in the second position at least a portion of the wheel extends from the pin body. Mat systems include such mat locking pins to enable movement of the may system and/or secure two mats together.

Abstract: The present disclosure provides methods, devices and systems for route deviation quantification and vehicular route learning based thereon. In some examples, there is provided a method for route deviation quantification of a suggested route. The method comprises: obtaining a ground truth route based on a filtered trajectory, the filtered trajectory including an inferred location of origin and an inferred location of destination; obtaining a suggested route generated based on the inferred location of origin and the inferred location of destination; quantifying a deviation of the suggested route from the ground truth route by calculating an off course ratio based on a combined length of road segments in the suggested route that are matched to corresponding road segments in the ground truth route and a combined length of road segments in the ground truth route.

Abstract: A method for selecting a target cell by a user equipment (UE), includes: detecting a movement of the UE based on a change in a location of the UE and a change in a measured signal power of a serving cell; determining personalized data of a user based on a plurality of user contextual parameters; predicting a destination of the user, and one or more target cells across a path of the user to the destination based on the determined personalized data of the user and the detected movement of the UE; and selecting the target cell from the one or more target cells, based on an artificial intelligence (AI) model. The AI model is configured to update weights of one or more network quality parameters.

Abstract: A system includes a memory device a processing device, operatively coupled to the memory device. The processing device is configured to receive a request to identify a target key in a key-value store based on a specified key; identify, in at least one of a plurality of sequences of memory keys, the target key based on the specified key, where the plurality of sequences of memory keys includes a sequence of memory keys and a sequence of media keys that comprises designated media keys, where each of the designated media keys is designated as being deleted, where the identifying comprises comparing each of the designated media keys to the specified key; and perform a database operation using the target key.

Abstract: A solid ion conductive material can include a complex metal halide. The complex metal halide can include at least one alkali metal element. In an embodiment, the solid ion conductive material including the complex metal halide can be a single crystal. In another embodiment, the ion conductive material including the complex metal halide can be a crystalline material having a particular crystallographic orientation. A solid electrolyte can include the ion conductive material including the complex metal halide.

Abstract: The disclosure features novel lipids and compositions involving the same. Nanoparticle compositions include an ionizable lipid, a phospholipid, a first sterol or a tocopherol, and optionally a second sterol different from the first sterol. Nanoparticle compositions further including therapeutic and/or prophylactics such as RNA are useful in the delivery of therapeutic and/or prophylactics to mammalian cells or organs to, for example, regulate polypeptide, protein, or gene expression.

Abstract: A system may receive enterprise information associated with a client enterprise. The system may select, using an industry analysis model, a set of queries associated with obtaining status information that is associated with a technology profile of the client enterprise. The system may generate client data that is associated with the enterprise information and the status information. The system may convert, using a matrix factorization technique, the client data associated with the client enterprise to a client matrix. The system may convert, using the matrix factorization technique, reference data associated with reference enterprises to a reference matrix. The system may determine, based on a comparison of the client matrix and the reference matrix, a set of scores associated with technology metrics of the technology profile. The system may perform an action associated with the client enterprise based on the set of scores.

Abstract: Systems and methods for information retrieval are described. Embodiments generate a dense embedding for each of a plurality of media objects to be searched, generate a sparse embedding for each of the media objects using an encoder that takes the dense embedding as an input, wherein the sparse embedding satisfies a sparsity constraint that is applied to at least one layer of the encoder during training, and perform a search on the plurality of media objects based at least in part on the sparse embedding.

Abstract: A domain processing system is enhanced with a first-pass domain filter configured for loading character strings representing a pair of domains consisting of a seed domain and a candidate domain in a computer memory, computing a similarity score and a dynamic threshold for the pair of domains, determining whether the similarity score exceeds the dynamic threshold, and iterating the loading, the computing, and the determining for each of a plurality of candidate domains paired with the seed domain. A similarity score between the seed domain and the candidate domain and a corresponding dynamic threshold for the pair are computed. If the similarity score exceeds the corresponding dynamic threshold, the candidate domain is provided to a downstream computing facility. Otherwise, it is dropped. In this way, the first-pass domain filter can significantly reduce the number of domains that otherwise would need to be processed by the downstream computing facility.

Abstract: A microservice storage device system includes a computing device. A storage device is coupled to the computing device and includes storage device compute hardware coupled to a storage subsystem that is configured to store data. The storage device uses the storage device compute hardware to provide a storage device operating system. The storage device then uses the storage device operating system to provide a storage device management microservice that it uses to manage the storage subsystem. The storage device also uses the storage device operating system to provide at least one compute microservice that it uses to perform at least one compute operation. The storage device management microservice and the at least one compute microservice may each be provided in a respective container generated by the storage device operating system for each of the storage device management microservice and the at least one compute microservice.

Abstract: An autonomous compute storage device system includes a computing device and a storage device that is coupled to the computing device. The storage device receives a read instruction from a host processing system in the computing device that identifies data stored in a storage subsystem included in the storage device and, in response, performs a read operation to copy the data from the storage subsystem to a memory subsystem accessible to the storage device and provide the data to the host processing system. If the storage device determines that an autonomous compute signature matches the data that was copied to the memory subsystem during the performance of the read operation, it executes an autonomous compute application to perform compute operations that are associated with the data that was copied to the memory subsystem during the performance of the read operation and generate compute operation result(s).

Abstract: An autonomous compute storage device system includes a computing device and a storage device that is coupled to the computing device. The storage device identifies a storage operation for a storage subsystem that is included in the storage device and, in response, performs the storage operation and stores data in a memory subsystem that is accessible to the storage device as part of the performance of the storage operation. If the storage device determines that an autonomous compute signature matches the data that was stored in the memory subsystem, it executes an autonomous compute application to perform compute operations that are associated with the data that was stored in the memory subsystem and generate at least one compute operation result.

Abstract: Methods and systems for managing data access based threats are disclosed. To manage the data access based threats, a data processing system may include a network interface controller (NIC). The network interface controller may present emulated storages that may be used for data storage. The emulated storage devices may utilize storage resources of storage devices. The NIC may actively screen for access patterns in use of the emulated storage devices that indicate compute complexes may be compromised. When doing so, the processing may be done locally on the NIC.

Abstract: A zoned namespace storage device system includes a zoned namespace storage device coupled to a computing device. The zoned namespace storage device includes a zoned namespace storage subsystem that is configured to store data, and storage device compute hardware that is coupled to the zoned namespace storage subsystem and that is configured to provide a storage device operating system that includes a storage device management microservice. The storage device management microservice presents a non-zone storage service to a host subsystem in the computing device and receives, via the non-zone storage service presented to the host subsystem, a storage command from the host subsystem that is associated with a storage operation. The storage device management microservice then utilizes a zone storage service presented to the storage device management microservice by the zoned namespace storage subsystem to perform the storage operation on the zoned namespace storage subsystem.

Abstract: An autonomous compute storage device system includes a computing device and a storage device that is coupled to the computing device. The storage device receives a write instruction from a host processing system in the computing device that includes data for storage in a storage subsystem that is included in the storage device and, in response, performs a write operation to provide the data in a memory subsystem that is accessible to the storage device and store the data in the storage subsystem. If the storage device determines that an autonomous compute signature matches the data that was provided in the memory subsystem during the performance of the write operation, it executes an autonomous compute application to perform compute operations that are associated with the data that was provided in the memory subsystem during the performance of the write operation and generate at least one compute operation result.

Abstract: Adjusting workload execution based on workload similarity. A processor may determine a similarity of a first workload to a second workload. The processor may adjust execution of the first workload based on execution parameters of the second workload and the similarity of the first workload to the second workload.

Abstract: Implementations described herein relate to a cluster namespace for a memory device. In some implementations, a memory device may receive a cluster namespace instruction, from a host device, that instructs the memory device to create a cluster namespace using memory resources of the memory device that are spread across a plurality of namespaces of the memory device. The memory device may identify namespace storage information that indicates memory resources associated with a plurality of namespaces of the memory device. The memory device may create the cluster namespace based on creating a plurality of extents that respectively map sets of logical block address ranges from the plurality of namespaces to the cluster namespace.