Abstract: Methods, systems, and devices for supporting security for private data inputs to artificial intelligence models are described. A device (e.g., an application server) may receive a request to run an artificial intelligence model. The device may run the artificial intelligence model on a public data set and an extended set of data that includes both the public data set and a private data set. The device may determine a first set of outcomes based on running the artificial intelligence model on the public data set and a second set of outcomes based on rerunning the model on the extended set of data. The device may then compare the two sets of outcomes to determine whether a private data value is identifiable based on the second set of outcomes. If a private data value is identifiable, the device may obfuscate the results prior to transmitting the results to the requestor.

Abstract: A method for using a distributed ledger (DL) of a blockchain applicable to a network of blockchain nodes is provided.

Abstract: A system performs optical character recognition (OCR) on an image displaying a portion of an object. An image classification system identifies the object in the image, based on which one or more object detection models identify labels associated with the object within the image. The system determines text of the identified labels using OCR, and analyzes the OCR resultant text for discrepancies and/or inaccuracies. In response to identifying a discrepancy, the system provides a recommendation for improving the accuracy of the OCR resultant text.

Abstract: Systems, methods, and apparatuses for implementing a behavioral responsive adaptive context engine for emotionally-responsive experiences are disclosed.

Abstract: Artificial intelligence (AI) oversight may be added to a multiparty engagement, such as a conference between devices having user interfaces. The AI may apply visual indicators, e.g., informational elements, recommendations, or other data, on one or more user interface. Visual indicators assist with presenting or participating in a conference. Visual indicators may highlight, e.g., AI-determined attributes of participants in the conference. Attributes may be derived physiological characteristics of participants, such as mood, apparent interest, paying attention, as well as AI-derived data from analyzing data sources, such as data about the participant, past engagements, time zone, name/title and other information to facilitate interaction with the participant. The AI may also review data for past deals, resume, project plans, social media, customer relationship manager data, and the like and develop models to allow it to monitor a conference and provide recommendations to facilitate conference goals.

Abstract: Methods, systems, and devices for supporting security for private data inputs to artificial intelligence models are described. A device (e.g., an application server) may receive a request to run an artificial intelligence model. The device may run the artificial intelligence model on a public data set and an extended set of data that includes both the public data set and a private data set. The device may determine a first set of outcomes based on running the artificial intelligence model on the public data set and a second set of outcomes based on rerunning the model on the extended set of data. The device may then compare the two sets of outcomes to determine whether a private data value is identifiable based on the second set of outcomes. If a private data value is identifiable, the device may obfuscate the results prior to transmitting the results to the requestor.

Abstract: Methods, systems, and devices for supporting security for private data inputs to artificial intelligence models are described. A device (e.g., an application server) may receive a request to run an artificial intelligence model. The device may run the artificial intelligence model on a public data set and an extended set of data that includes both the public data set and a private data set. The device may determine a first set of outcomes based on running the artificial intelligence model on the public data set and a second set of outcomes based on rerunning the model on the extended set of data. The device may then compare the two sets of outcomes to determine whether a private data value is identifiable based on the second set of outcomes. If a private data value is identifiable, the device may obfuscate the results prior to transmitting the results to the requestor.

Abstract: A method and a cloud-computing architecture for enabling dynamic access of an artificial intelligence engine are described. A record that includes a set of one or more fields is stored in a database. A first field from the set of fields includes an identification of an artificial intelligence (AI) engine and one or more additional fields from the set of fields respectively include one or more parameters for the AI engine. The record is accesses causing the AI engine to run with the one or more parameters. As a result of the AI engine running with the one or more parameters upon access of the record, a desired predicted output is obtained.

Abstract: A system performs optical character recognition (OCR) on an image displaying a portion of an object. An image classification system identifies the object in the image, based on which one or more object detection models identify labels associated with the object within the image. The system determines text of the identified labels using OCR, and analyzes the OCR resultant text for discrepancies and/or inaccuracies. In response to identifying a discrepancy, the system provides a recommendation for improving the accuracy of the OCR resultant text.

Abstract: System and methods are described for performing message language analysis based on target recipient profile data. In one implementation, a method comprises receiving proposed content to be transmitted to a target recipient; computing one or more semantic factors descriptive of the proposed content; comparing the one or more semantic factors with data stored in a profile associated with the target recipient; and generating, based on the comparison, one or more recommended edits to the proposed content to customize the proposed content to the target recipient.

Abstract: Systems and methods for generating customized content based on a streaming content are described. A server computing system streams content from an online content provider to an output device, the content including one or more programs. The computing system receives a first voice command while the one or more programs is being streamed to the output device. The computing system stores information associated with a program being streamed to the output device responsive to receiving the first voice command from a user associated with the output device during a first time interval. The computing system generates customized content based at least on the stored information associated with the program being streamed to the output device. The computing system delivers the customized content to the user during a second time interval.

Abstract: A system performs optical character recognition (OCR) on an image displaying a portion of an object. An image classification system identifies the object in the image, based on which one or more object detection models identify labels associated with the object within the image. The system determines text of the identified labels using OCR, and analyzes the OCR resultant text for discrepancies and/or inaccuracies. In response to identifying a discrepancy, the system provides a recommendation for improving the accuracy of the OCR resultant text.

Abstract: A method of targeting a promotion to an appropriate audience includes: performing clustering analysis on anonymized customer data using artificial intelligence to segment the anonymized data into a plurality of audience clusters; applying a matching algorithm to match a personalized promotion to a first audience cluster; sending the personalized promotion using a digital display channel to a plurality of individuals matching characteristics of the first audience cluster; receiving and recording results from the personalized promotion; and iteratively adjusting the personalized promotion based on the results from the personalized promotion.

Abstract: A system performs optical character recognition (OCR) on an image displaying a portion of an object. An image classification system identifies the object in the image, based on which one or more object detection models identify labels associated with the object within the image. The system determines text of the identified labels using OCR, and analyzes the OCR resultant text for discrepancies and/or inaccuracies. In response to identifying a discrepancy, the system provides a recommendation for improving the accuracy of the OCR resultant text.

Abstract: Disclosed embodiments are related to blockchain asset token management systems, and in particular, to Multiple Decentralized Tokenization with Personal Control (MDTPC). MDTPC allows users to determine how and when asset token evaluation is performed, and also allows users to determine which token management services they wish to use to manage and store their asset token and related data. In embodiments, multiple blockchain token management services are utilized in conjunction with individual digital wallets to share token data and validate ownership of tokens. A registry service is used to ensure visibility of tokens across multiple token management services, which increases the likelihood of identifying the rightful owner of asset tokens. Other embodiments may be described and/or claimed.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for managing access to data based on information associated with a physical location of a user. These mechanisms and methods for managing access to systems, products, or data based on information associated with a physical location of a user can enable improved data management efficiency, enhanced data management accuracy, decreased data management costs, decreased licensing costs, increased security, additional marketing opportunities, etc.

Abstract: Methods, systems, and devices for supporting security for private data inputs to artificial intelligence models are described. A device (e.g., an application server) may receive a request to run an artificial intelligence model. The device may run the artificial intelligence model on a public data set and an extended set of data that includes both the public data set and a private data set. The device may determine a first set of outcomes based on running the artificial intelligence model on the public data set and a second set of outcomes based on rerunning the model on the extended set of data. The device may then compare the two sets of outcomes to determine whether a private data value is identifiable based on the second set of outcomes. If a private data value is identifiable, the device may obfuscate the results prior to transmitting the results to the requestor.

Abstract: In various embodiments, a method of verifying a multi-factor administrator action may be performed. The method may include receiving, from a first user, an authentication request that indicates a requested access, where the first user has administrative privileges to perform the requested access. The method may further include identifying a second user that has administrative privileges to approve the requested access. A verification request may be to the second user. In response to receiving an approval message from the second user within a particular amount of time, an authentication response that indicates that the first user is authorized to perform the requested access may be sent to the first user.

Abstract: A host organization writes a smart contract and an associated plurality of assets to a distributed ledger via a distributed ledger services interface of the host organization, which operates as a first one of a plurality of nodes that has access to the assets via the distributed ledger. The host receives a request message from a second one of the plurality of nodes to access an asset associated with the smart contract written to the distributed ledger. The request message generates a distributed ledger transaction including a first event or trigger associated with the smart contract. An event listener executing within the host organization detects the first event or trigger, and initiates a pre-programmed action within the host organization in response thereto.

Abstract: Digital data systems and methods support data retrieval with bias reduction. In some embodiments, these minimize the effect of bias in artificial intelligence-based business intelligence engines by preventing reporting of models that are based on “bias-sensitive” predictor variables such as race, sex and political affiliation, and so forth. In other embodiments, e.g., where the AI engine returns measures (or degrees) of correlation, such censure can be with respect to models where those measures are above a designated quantitative or qualitative high water mark values. Alternatively, or in addition, the systems and methods hereof can minimize the effect of data bias by reducing such a measure of correlation so that the corresponding model appears inferior to ones that are not based on bias-sensitive predictor variables.