Dell Products Inc.

Emc IP Holding Company LLC

Qi Bao

Min Gong

Himabindu Tummala

Qicheng Qiu

Gaurav Chawla

Jing Liu

John T Cardente

Flavio Junqueira

Zijia Wang

ChunXi Chen

Shuangchen Huang

Daniel Wu

Methods, apparatus, and processor-readable storage media for artificial intelligence-based techniques for automated visual data searching using edge devices are provided herein. An example computer-implemented method includes obtaining visual data from one or more edge devices; generating at least one automated searching tool by processing at least a portion of the obtained data using one or more artificial intelligence techniques; deploying the at least one automated searching tool to at least a portion of the one or more edge devices; and performing one or more automated actions based at least in part on data received, from at least a portion of the one or more edge devices, in connection with operation of the at least one automated searching tool.

Artificial intelligence-based techniques for automated visual data searching using edge devices

A method for managing a framework includes: receiving, by a GUI, a query that is sent to a first module; analyzing, by the first module, the query to infer intention; making, by the first module, a determination that the intention is not searching for an object in a database; sending, by the first module, the query to a second module; transforming, by the second module, the query into a vector that is sent to a third module; performing, by the third module and using the vector, a search for a nearest image in the database; identifying, by the third module, a path associated with the nearest image, which is sent to an analyzer, in which the analyzer further sends the path to a fourth module; and fetching, by the fourth module and based on the path, an image from a store, which is sent to the GUI.

Method and system for a text-vision retrieval framework

A method for performing vector similarity search (VSS) includes: performing, based on a set of thresholds, a sparse partitioning of n-dimensional hyperspace into a plurality of grid bins to generate a hyperspace partition map, in which (i) only grid bins to which vectors mapped to are managed by the hyperspace partition map and (ii) each grid bin of the plurality of grid bins points to a storage location in a storage; ingesting a vector; using the hyperspace partition map to identify a grid bin of the plurality of grid bins for the vector and to identify coordinates of the grid bin; mapping the vector to the grid bin; and hashing the coordinates to generate a storage location key associated with a second storage location, in which the vector is stored to the second storage location using the storage location key.

Method and system for hyperspace sparse partition vector similarity search

Techniques described herein relate to a method for managing metadata for unstructured data. The method includes identifying a first storage event associated with a first unstructured data object; streaming, from a storage resource, first system metadata associated with the first unstructured data object; identifying, using a first system metadata processor, a first object type associated with the first unstructured data object based on the first system metadata; storing the first system metadata in a first entry of a first metadata table; streaming second system metadata associated with a second unstructured data object; identifying, using the first system metadata processor, a second object type associated with the second unstructured data object based on the second system metadata; and storing the second system metadata in a second entry of a second metadata table, wherein the second metadata is queried to obtain the first unstructured data object.

Method and system for extracting metadata from unstructured data

Techniques described herein relate to a method for managing training data. The method includes monitoring, by a training data stream manager (TDSM), a cache comprising a plurality of training data examples associated with streams of mini-batch sequences scheduled to be transmitted to a machine learning training environment; making a first determination that a cache eviction is required; in response to the first determination: selecting a training data example of the plurality of training data examples; making a second determination that the training data example is eligible for cache eviction; in response to the second determination: evicting the training data example from the cache; and updating a training data example database entry to indicate that the training data example is evicted from the cache.

Method and system for evicting and reloading a cache for machine learning training data streams

A peer-to-peer global namespace for storage system metadata federations. Specifically, the disclosure proposes a peer-to-peer metadata federation architecture, where enterprise storage metadata for any and all geo-distributed sites may be distributed across and continually reconciled by a network of nodes, instead of being maintained by a single node assigned to a given geographic location. In implementing a federation, the network of nodes may lack exploitable, centralized points of vulnerability, and therefore, may exhibit no central point of failure. Furthermore, the disclosure proposes the implementation of a global metadata namespace for the enterprise storage metadata spanning the entirety of an enterprise (across all geographic locations). The global metadata namespace may be maintained on each node through event-based synchronization.

Peer-to-peer global namespace for storage system metadata federations

This disclosure provides systems, methods, and media for creating a data graph database from various unstructured and unstructured data items for use by various services. The method comprises the operations of identifying unstructured data items in data subjects; recognizing regions of interest (ROIs) in the unstructured data items; and extracting the ROIs from the unstructured data items. The method further comprises encoding the extracted ROIs into ROI vectors; creating a data graph to represent the data subjects, the data items, and the ROI vectors; and storing the data graph into a graph database. The various embodiments can manage data items of different data formats together rather than separately, thus creating a data management system for managing data across data formats. The data management system can also store structured data items into the graph database, thus complementing the existing ETL procedure for structured data items.

ROI-based data content graph for wide data management

A method for joining an association that includes receiving, by a first cluster, an association access credential and a unique address of an association manager, generating, based on the association access credential, an association access request, sending, to the unique address, the association access request, receiving, in response to the sending, association information, and initiating, based on the association information, a connection to a second cluster in the association.

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Acton, MA, United States of America

Qi Bao