Abstract: The present disclosure provides a system for providing virtual assistant for generating customized query for retrieving data from a database. The system comprises a processor and a memory storing program instructions, which, when executed by the processor, causes the processor to provide one or more index of categories of the data, for efficient retrieval of the data from the database based on a customer's query. The processor is also configured to provide one or more few-shot prompts for use by the customer for generating an output in a predetermined format corresponding to the customer's query. The processor is configured to receive a query from the one or more customer, wherein said query is a text and is based on at least one of index of categories and the few-shot prompt. The processor, based on indexes and few-shot prompt processes the query using natural language processing to extract one or more textual content from the query and sends the query to the database for retrieval of the data.

Abstract: A method for backing up data includes: determining a storage tier for storing the data; determining a data access frequency of the data, where the data access frequency indicates a frequency at which the data is accessed; and taking information of the storage tier and the data access frequency of the data as metadata, and sending the metadata and the data to a backup server. By sending the information including the storage tier for storing the data and the data access frequency as the metadata to the backup server, the computing device is enabled to recover the data by using the information in the metadata during the data recovery process, so that the data tiering layout can be maintained in the storage region to maintain the storage service performance, and thus a seamless storage service is provided to improve the user experience.

Abstract: Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and/or request bodies, structuring user-generated content, and/or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and/or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

Abstract: Provided is a method including obtaining a prompt, determining a prompt embedding vector representing the prompt in an embedding space, modifying the prompt embedding vector using a trained model configured to adjust prompt embedding vectors to decrease proximity to vectors of blocks in a data set from which data is retrieved to augment generation by the generative AI model, determining that the modified prompt embedding vector is within a threshold distance to vectors in the embedding space corresponding to one or more blocks in the data set, selecting the one or more blocks in the data set, generating a response using the generative AI model based on the selected one or more blocks in the data set, quantifying an amount of influence of the respective block on corresponding text in the generated response, and providing the response and a representation of the quantified amount of influence as an output.

Abstract: A storage manager maintains metadata for a plurality of graph components including, for each given graph component, a memory-state indicator that indicates whether the given graph component is stored in memory. The storage manager identifies a set of graph components required to execute a graph processing operation and identifies, based on the metadata, a first subset of the set of graph components that are stored in the memory and a second subset of the set of graph components that are not stored in the memory. The storage manager loads the second subset of graph components into memory and initiates execution of the graph processing operation using the set of graph components in memory.

Abstract: A system and method for continual learning in a provider network. The method is configured to implement or interface with a system which implements a semi-automated or fully automated architecture of continual machine learning, the semi-automated or fully automated architecture implementing user-configurable model retraining or hyperparameter tuning, which is enabled by a provider network. This functions to adapt a model over time to new information in the training data while also providing a user-friendly, flexible, and customizable continual learning process.

Abstract: A method of generating and storing metadata in a data processing system includes defining metadata sets of process definition metadata based on a process definition of the data processing system. The metadata sets include a first set of metadata corresponding to a processing step of the data processing system, a second set of metadata corresponding to a processing step successor, and a third set of metadata corresponding to a data object that is produced or consumed by the processing step in the data processing system. The method further includes executing one or more steps of the data processing system according to the process definition and generating runtime metadata during an execution of the one or more data processing system steps. The method further includes storing the runtime metadata and forming a metadata data store that integrates the runtime metadata and the metadata sets of process definition metadata.

Abstract: A device and a method for collecting, analyzing and integrating log data of an in-vehicle infotainment (IVI) system are disclosed. The method for collecting, analyzing and integrating log data of an IVI system includes identifying model information of a vehicle to be a target of digital forensics, hardware information and software information related to the IVI system of the vehicle, collecting target data for the digital forensics based on the model information, the hardware information and the software information, and storing the collected target data in an integrated database.

Abstract: Systems and methods are provided for replicating data between different services used to update databases. One example system includes a database and a computing device coupled in communication with the database, wherein the computing device is configured to perform a create, update or delete operation on the data included in the database and to post an entry representative of the operation to an outbox data structure. The computing device is also configured to retrieve the entry from the outbox data structure; publish the entry as a first message to a message bus, thereby informing a different data system of the operation in the database; receive a second message from the message bus indicative of a create, update or delete operation at a database included in a different data system; and direct a service of the system to perform the create, update or delete operation of the second message.

Abstract: Systems and methods for using prompt dissection to prompts one or more machine learning models for a set of one or more documents are disclosed. Exemplary implementations may: store a set of document segments from the set of one or more documents; present a user interface to obtain a compound query that includes a first subquery and a second subquery; create subquery vectors that semantically represent the subqueries; determine a subset of a set of semantic vectors based on comparisons with the subquery vectors; create a combination of the individual document segments that are associated with the subset; provide one or more prompts to the one or more machine learning models, using the combination of the individual document segments as context; present replies from the one or more machine learning models, and/or perform other steps.

Abstract: A deduplicated storage system storing objects receives a search term. Storage includes metadata and segments into which the objects have been split and deduplicated. Metadata includes fingerprint sequences according to which the segments should be assembled. A partial match is found when a prefix of the term is found at an end of a segment or a suffix is found at a beginning of the segment. The partial matches are recorded and merged to form full matches. Each full match includes a first fingerprint of a first segment in which the prefix was found and a second fingerprint of a second segment in which the suffix was found. A check is made of whether a fingerprint and a next fingerprint from a first sequence of fingerprints associated with a first object have been recorded in the database. If so, the first object is reported as having the search term.

Abstract: Method, computer program product, and computer system are provided. A controller component verifies the state of all file sets. The controller component initiates a sub-controller component, based on successfully verifying the state of the file sets. The sub-controller component suspends write operations to all databases at the primary site computer. Based on the suspending completing without error, the sub-controller executes point-in-time copy processes for each of the databases and for application non-database files at the primary site computer. Applications using the databases and non-database files are not suspended. Based on all of the point-in-time copy processes completing without error, the sub-controller component resumes write operations to all databases at the primary site computer. The point-in-time copies are automatically sent to the secondary site computer so that the applications can operate at the secondary site computer if the primary site computer becomes unavailable.

Abstract: An embodiment of the present invention is directed to a Metadata-Driven Data Quality Framework and Engine that enables dynamic generation of code for assessing data quality based on qualified metadata content. The Data Quality Framework may be directed to an enterprise scaled application that embodies Data Quality disciplines for good/optimal Data Governance. An embodiment of the present invention may be integrated into a Metadata Management process of an overall Data Governance Program so the data user's meaning and understanding may become part of the automated data quality process.

Abstract: In general, the subject matter described in this disclosure can be embodied in methods, systems, and program products for linking to a search result. A computing system receives a query and provides, to a first computing device, multiple results that are responsive to the query. The computing system provides, to the first computing device, information that identifies a web address of a user selected result of multiple results that are responsive to query. The computing system receives a request from a second computing device for content responsive to the web address of the user selected result. The computing system provides, to the second computing device, information to cause the second computing device to present the multiple results that are responsive to the query in distinction to the user selected result, responsive to the second computing device not being authorized to access the user selected result.

Abstract: Media content may be recommended based on feedback weightings. Input data describing the presentation of a media content items in association with content management accounts may be represented as data points. Each data point may identify feedback data for a media content item previously recommended for presentation in association with a content management account. The feedback data may identify a viewer reaction to the recommended media content item. A weighting factor based on the feedback data for the media content item presented in association with the content management account may be applied to produce a recommendation.

Abstract: Data selection systems and techniques are described. For instance, a system receives a data set with a plurality of data elements. The system generates a plurality of random values. The system generates a ranking of the plurality of random values. The system selects a subset of the plurality of data elements based on a comparison between the ranking and a predetermined threshold. The predetermined threshold is based on a predetermined proportion of the plurality of data elements to be included in the subset. The system outputs a randomization scheme that includes the ranking and the predetermined proportion, wherein a second selection of a second subset of the plurality of data elements is based on the randomization scheme. The system output an indication of the subset and the second subset.

Abstract: Dashboard loading using a filtering query from a cloud-based data warehouse cache, including determining that a filtered result for a first filtering query is stored in a cache of a cloud-based data warehouse; sending, in response to the filtered result being stored in the cache, to the cloud-based data warehouse, a request for the filtered result from the cache; and providing, based on the filtered result for the first filtering query, one or more dashboard visualizations.

Abstract: A computer-implemented method to intelligently compare a database in resumable batch mode is provided. A number of processor units reallocate a plurality of available threads among at least one of the tPartitioner, the plurality of tCombiners, and the diffReporter using an ArrayList of a threadManager of a TablePair Container. According to other illustrative embodiments, a computer system and computer program product for intelligently comparing a database in resumable batch mode are provided.

Abstract: Systems and methods are described for unified processing of indexed and streaming data. A system enables users to query indexed data or specify processing pipelines to be applied to streaming data. In some instances, a user may specify a query intended to be run against indexed data, but may specify criteria that includes not-yet-indexed data (e.g., a future time frame). The system may convert the query into a data processing pipeline applied to not-yet-indexed data, thus increasing the efficiency of the system. Similarly, in some instances, a user may specify a data processing pipeline to be applied to a data stream, but specify criteria including data items outside the data stream. For example, a user may wish to apply the pipeline retroactively, to data items that have already exited the data stream. The system can convert the pipeline into a query against indexed data to satisfy the users processing requirements.

Abstract: Aspects of the invention include systems and methods configured to extract enriched target-oriented common sense from grounded graphs to support efficient next step decision making of an autonomous agent. A non-limiting example computer-implemented method includes extracting common sense from a source. The extracted common sense can include a first knowledge graph. An environment state can be extracted from an observation. The extracted environment state can include a second knowledge graph. The second knowledge graph can include an interactive object and a state of the interactive object. A difference graph including the extracted common sense and the extracted environment state can be generated. A next action is selected based on the difference graph and the next action is taken by an autonomous agent.