Abstract: Various example embodiments described herein provide for systems, methods, devices, instructions, and the like for using AI model cascades to filter data on a data system, such as a database system, based on an artificial intelligence model prompt (e.g., user-provided prompt). In particular, various example embodiments enable a database system to use cascaded AI models and adaptive bounds to optimize data filtering operations based on an artificial intelligence model prompt (also referred to herein as just a prompt) while balancing computational cost and accuracy, which can be useful in processing large-scale data queries.

Abstract: A system receives a message that includes a change event associated with a source dataset for replication to a destination in a cloud environment. The system accesses a replication tag associated with the message. The replication tag includes a tag element that is mapped a destination key that identifies a destination dataset, corresponding to the destination, where the change event is to be replicated. The system determines that the tag element of the replication tag is mapped to the destination key. Responsive to determining that the tag element is mapped to the destination key, the system directs the message to the destination to replicate the change event to the destination dataset.

Abstract: A distributed system includes multiple servers that various client devices access. Each server maintains a copy of a data object for access to the data object regardless of which server is accessed. Each server may modify a local copy of the data object, with the modifications propagated to other servers. A server generates a local version vector that includes pairs of a server identifier from whom modifications were received and a server-specific version identifier for the modifications. When a client device retrieves the data object, the client device transmits a client version vector for the data object including pairs of server identifiers and server-specific version identifiers from which the client device received version events for modifications to the data object. The server compares the local version vector to the client version vector to determine whether to transmit a local copy of the data object to the client device.

Abstract: An apparatus is described that includes an execution unit to execute a first instruction and a second instruction. The execution unit includes input register space to store a first data structure to be replicated when executing the first instruction and to store a second data structure to be replicated when executing the second instruction. The first and second data structures are both packed data structures. Data values of the first packed data structure are twice as large as data values of the second packed data structure. The execution unit also includes replication logic circuitry to replicate the first data structure when executing the first instruction to create a first replication data structure, and, to replicate the second data structure when executing the second data instruction to create a second replication data structure.

Abstract: A system is configured to receive messages from an external device hosting a database. A replicator processes a selected message using one of a plurality of jobs that analyze the target data in the selected message to determine target databases to record data associated with the selected message. The job stores the associated record data in the appropriate target databases, and a message processing rate is determined for that job. Using the message processing rate for all of the jobs, the total number of messages that the jobs are able to process in a predetermined period is determined. The current number of pending messages is also determined. An efficiency parameter is determined by subtracting the total number of messages that the jobs are able to process from the current number of pending messages. An additional job is started when the efficiency parameter is less than a predetermined threshold.

Abstract: Systems and methods are provided for generating a listing of equivalent snapshot objects referenced by a set of object-based snapshots representing data of a corresponding block-storage volume at a point-in-time. Generating the listing comprises: retrieving a set of main manifests corresponding to the set of object-based snapshots, retrieving a set of co-pair manifests corresponding to the set of object-based snapshots, each co-pair manifest corresponding to an object-based snapshot and including a listing of encrypted snapshot objects with equivalencies to unencrypted snapshot objects, identifying data duplication in the set of main manifests based on listings of encrypted snapshot objects with equivalencies to unencrypted snapshot objects found in the set of co-pair manifests, and removing identified data duplication in the set of main manifests.

Abstract: One or more genetic family trees are formed that connect a plurality of individuals based on measures of genetic relatedness between the individuals. A plurality of the individuals are grouped into a cluster that comprises those individuals who are genetically related to (1) a target individual according to first data and (2) each other according to second data. The first data comprises genetic relatedness measures for a plurality of the individuals relative to the target individual, and the second data comprises genetic relatedness measures between a plurality of the individuals. The cluster is deconstructed into a tree structure based on the first data, and family tree(s) are iteratively formed based on pairs of adjacent nodes from the tree structure until the nodes are positioned in family tree(s) based on the second data. The family tree(s) can be connected to the target individual based on the first data.

Abstract: A method, computer system, and a computer program product are provided for a context-aware relevancy modelling in conversational systems. A user query is received. A latent static content d is selected from a corpus of content D. A latent set of context C from a set of external context Cu is also selected. A result is generated using a scoring function and using the latent static content d from a corpus D and the latent set of context C from the set of external contexts CU so as to provide a most relevant context-base search response to said user query q. The result provides a most relevant context-base search response to said user query q. A response is then generated based on said result using said scoring function result to said user query q.

Abstract: A centralized database management system performs data synchronization with lower bandwidth consumption and higher efficiency using a resizable invertible bloom filter. The system may include a resizable invertible bloom filter module that constructs and maintains invertible bloom filters that are resizable based on a number of differences between different snapshots. The resizable invertible bloom filter module may maintain a list of possible sizes for a resizable invertible bloom filter. The resizable invertible bloom filter module may determine and maintain a list of applicable partition sizes, each partition size being a product of a divisor and a resizing factor. If the number of differences exceeds the number of expected differences and results in failure in decoding, the system may retry a larger size in a set of predetermined sizes. The system may continue to try larger sizes until a minimal size required for successful decoding is found.

Abstract: A computer-implemented method for efficiently estimating the number of unique elements in a collection of elements comprises generating, via hash logic, hash values for each element of the collection of elements. The method further comprises specifying, in a sketch-frequency table, a set of discrete statistical values associated with the hash values and, for each discrete statistical value of the set of discrete statistical values, information indicative of a frequency at which binary representations of the hash values are associated with the discrete statistical value. The cardinality of the collection of elements is estimated based on the sketch-frequency table.

Abstract: A method includes receiving a user query identifying one or more criteria associated with logs or log-related information. The method also includes sending queries identifying the one or more criteria to multiple logging systems associated with different computing or networking systems. The method further includes obtaining responses from the logging systems, where at least some of the responses contain one or more logs or log-related information satisfying the one or more criteria. In addition, the method includes presenting the one or more logs or log-related information satisfying the one or more criteria to a user.

Abstract: A highly available database system includes a first instance of a database server on a first cluster of a virtual computing system, a second instance of the database server on a second cluster of the virtual computing system, a first instance of an administration database on the first cluster, and a second instance of the administration database on the second cluster. The first instance of the database server and the second instance of the database server form a highly available database server, the first instance of the administration database and the second instance of the administration database form a highly available administration database, and the first instance of the database server, the second instance of the database server, the first instance of the administration database, and the second instance of the administration database are configured to manage at least one customer database.

Abstract: Techniques are disclosed relating to storing database extents in physical storage nodes. To store the extents, a physical storage node of a computer system first accesses assignment metadata, which includes determining 1) virtual groupings of database extents assigned to the physical storage node and 2) database extents associated with the determined one or more virtual groupings. For a given database extent, a corresponding virtual grouping is determinable by performing a first hashing operation that uses an identifier for the given database extent. The physical storage node then accesses and stores the determined database extents. The physical storage node can now service requests for data of the database system that are stored at the first physical storage node.

Abstract: Systems and methods for using a scalable collection within a balanced tree data structure are provided herein. In particular, techniques for generating scalable collections and using scalable collections for fetching data corresponding to an application using balanced chunked data tree structures are provided herein. In an example, the method may include determining a document defined by a balanced tree data structure having a root chunk, reference chunks, and chunks each having nodes each corresponding to a document attribute. The nodes may include a scalable collection containing a list node and child nodes associated with the list node, and a placeholder node that provides a reference to another chunk based on a position of the placeholder node within a respective chunk. The method may also include navigating to content within the document based on the balanced tree data structure.

Abstract: It is provided a procedure for managing and updating regulatory digital textual documents, wherein the documents each define a textual structure including at least one or more textual portions, one or more reference parameters defined by at least one article and/or one paragraph, and one or more metadata, and wherein the process comprises acquiring a plurality of different documents from at least one external database, extracting the textual portions, the reference parameters and the metadata from each of the textual structures, recognising each textual structure by means of a first logic implementing an artificial intelligence based on a machine learning approach of supervised or zero-shot type, performing a multimodal analysis of the textual structure, by means of the first logic, labelling each of the textual portions, the reference parameters and the metadata to validate the extraction phase, identify the reference parameters and/or the metadata by means of a second logic implementing an artificial intell

Abstract: Provided is a determination apparatus including a planning data acquisition unit configured to acquire planning data representing a logging plan for logging of standing timber for a target area, a first image data acquisition unit configured to acquire first image data representing a first image captured before the logging for the target area, a second image data acquisition unit configured to acquire second image data representing a second image captured after the logging for the target area, a determination unit configured to perform a determination on whether the logging is appropriate or inappropriate based on the planning data, the first image data, and the second image data, and an output unit configured to perform an output according to a result of the determination.

Abstract: This disclosure relates to a method and system for data scrubbing in very-large-databases (VLDB) within regulated industries. The method involves segmenting a copy of a production database into manageable chunks based on row identifiers, allowing for parallel processing without database contention. Each chunk is processed by concurrently executing instances of a data scrubbing component, which replaces sensitive data with anonymous data of the same type using specified scrubbing algorithms. The system ensures that scrubbed data maintains the same structure and statistical properties as the original data while preventing the restoration of sensitive information. The process is meticulously documented to meet regulatory standards and facilitate audits, making it a robust solution for data scrubbing in environments with stringent compliance requirements.

Abstract: Systems, methods, and other embodiments described herein relate to encouraging exploration within a computing application. In one embodiment, a system includes a processor and a memory storing machine-readable instructions. The instructions, when executed by the processor, cause the processor to identify when a user is stuck in a repetitive pattern within a computing application. When the user is stuck in the repetitive pattern the instructions, the instructions when executed by the processor, cause the processor to encourage the user to further explore the computing application by 1) intervening in user activity within the computing application and 2) presenting attention-capturing content that is targeted to the user and unrelated to a domain of content accessed by the user within the computing application.

Abstract: Techniques used by an observability system for facilitating near real-time analytics using structures representing or summarizing data distributions, such as histograms. An observability system receives a set of datapoints in which each received datapoint includes data for a structure representing a data distribution. For example, each of the datapoints may include data for a histogram including at least two dimensions. A processing pipeline is disclosed for processing the received data and making the results of the processing available to a user in near real-time. The processing includes identifying, from the datapoints received by the observability system, a subset of datapoints that fall within a time window, generating aggregate data based upon data in the identified subset of datapoints, computing one or more statistical measures based upon the aggregate data, and enabling querying of the subset of datapoints, the aggregate data, and the statistical measures computed for the first minute.

Abstract: An information pushing method includes a server side that stores, in a target cache space after a cloud database successfully performs an operation, a type of the operation and an identifier of data associated with the operation. Then, when pushing to a client, the server side pushes related information of the data to the client based on the identifier of the data, the type of the operation, and whether the data exists in the cloud database currently, where the related information of the data is used by the client to determine a change between the data in the cloud database currently and that before the operation is performed such that an impact on performance of the cloud database can be reduced, and the client can obtain data information consistent with that in the cloud database.