A skill-gap analysis and recommender system and method is described that serves as a personalized education and skill (PES) map. It provides a comprehensive presentation of the opportunities afforded by the University along with a detailed analysis of trends for placements and career goals. It conducts a comprehensive analysis of past student data and current market trends to make recommendations that are adapted to each student's profile in line with their individual career goals. This is accomplished using an algorithm for adaptive association pattern mining with a built-in mechanism for creation of meta-categories and drill-down for specifics, so as to meet the needs of every student and not miss infrequent patterns or rare opportunities afforded by the system. For the recommendations generated, the system also provides an assessment of the time-sensitivity of a goal and a mechanism for students to track their progress through prioritizing short and long term goals.

An information processing apparatus that analyzes video data obtained from an image capture apparatus to detect an article that has been pre-registered is disclosed. The apparatus, in a case where an article that is determined to be a property of an article holder that has been pre-registered is detected, searches for an advertisement viewer located within a range of a predetermined distance from the article holder from among advertisement viewers that have registered the article as an article they are interested in. The apparatus then informs an advertisement viewer found by the search of location information of the article.

In a method for operating a machine tool and a corresponding machine tool system, a generic first data model and engineering data are provided in an external server device. The engineering data contain information relating to a machine tool. After a user query regarding an operation of the machine tool, the first data model is translated and/or modified to become a second data model. This occurs in accordance with the engineering data and technical data of the user query by the external server device. The second data model is transferred from the external server device to the machine tool, and a control unit of the machine tool can operate the machine tool according to the second data model. The machine tool can thus be adapted outside the running time of the machine tool.

Certain aspects of the present disclosure provide techniques for enumerating relationships in an object graph using traversal context objects that are decoupled from the implementation details of an object graph and the objects stored therein. An example method generally includes receiving a request to traverse an object graph, the object graph including a plurality of objects. A root context object is generated, and a traversal context object associated with a root node of the object graph is generated. The traversal context object is linked to the root context object and added to a traversal data structure. The graph is traversed by adding and removing traversal context objects to and from the traversal data structure until a terminating event occurs.

Systems, devices, and methods for automating network account transfers based on predicted inactivity are disclosed. In one embodiment, the system comprises a mail server providing access to an email account of a user; a social graph monitor configured to: periodically query, over a network, a social graph associated with the user to retrieve at least one social network feed associated with the user, calculate a sentiment score for the social network feed based on parsing the social network feed using a natural language parser, and determining that a transfer condition has occurred if the sentiment score exceeds a pre-defined sentiment score threshold; and a condition processor configured to: transmit, via the mail server, a password reset request to a network application associated with the transfer condition, intercept an email from the network application, via the mail server, transmitted in response to the password reset request, forward, via the mail server, the email to a recipient associated with the transfer condition, determine that the recipient has reset a password associated with the network application, and forward, to the recipient via the mail server, subsequent emails from the network application.

In one embodiment, a computer-implemented method of a data processing (DP) accelerator obtaining a watermark of a watermark-enable artificial intelligence (AI) model includes receiving, by the DP accelerator, input data to the DP accelerator that causes the watermark-enabled AI model to extract the watermark from the watermark-enabled AI model; and providing the watermark of the watermark-enabled AI model to the host device. The DP accelerator can receive the model from the host device. The DP accelerator can further receive a command to digitally sign the watermark and call a security unit of the DP accelerator to digitally sign the watermark.

Techniques are disclosed for storing an arranging data in a database. A method includes a computer system storing, in a database, data indicative of a graph data structure having a plurality of nodes connected by a plurality of edges. The method further includes the computer system determining that a number of edges connected to a first node satisfies a threshold number. In response to the determining, the computer system may store an index in an index row associated with the first node. The index identifies a first row having first and second ranges of values stored in first and second rows, respectively. The values in the first and second rows correspond to edges connected to the first node. The values in the first and second ranges are usable to indicate properties of corresponding ones of the plurality of edges.

Methods for generating data models using a generative adversarial network can begin by receiving a data model generation request by a model optimizer from an interface. The model optimizer can provision computing resources with a data model. As a further step, a synthetic dataset for training the data model can be generated using a generative network of a generative adversarial network, the generative network trained to generate output data differing at least a predetermined amount from a reference dataset according to a similarity metric. The computing resources can train the data model using the synthetic dataset. The model optimizer can evaluate performance criteria of the data model and, based on the evaluation of the performance criteria of the data model, store the data model and metadata of the data model in a model storage. The data model can then be used to process production data.

The present disclosure is directed to systems and methods for performant data matching. Entities maintain large amounts of data and desire to reconcile duplicative records. One way to solve this problem is through data matching. However, standard data matching at the record level can be laborious and inefficient. To remedy these inefficiencies in data matching, the present disclosure describes a system where the token records are tokenized a second time into token sets based on the token records satisfying at least one token set rule. A token set rule may be based on the common presence of multiple tokens in a token record. If multiple token records have the required tokens from the set rule, then those token records can be hashed and rolled-up into the token set (i.e., tokenized a second time into the token set). The token set allows for more efficient data matching.

Methods to reduce agent effort and improve customer experience quality through artificial intelligence. The Agent Assist tool provides contact centers with an innovative tool designed to reduce agent effort, improve quality and reduce costs by minimizing search and data entry tasks The Agent Assist tool is natively built and fully unified within the agent interface while keeping all data internally protected from third-party sharing.