Salesforce Com, Inc.

International Business Machines Corporation

Salesforce, Inc.

Daniel Thomas Harrison

Karl J Cama

Michael A Salem

Christopher Anthony Kemp

Abigail Reyes Knox

Kenneth J Muckenhaupt

Dennis Schultz

Jeffrey DiMuro

Arastun Efendiyev

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.

Security for private data inputs to artificial intelligence models

A method for using a distributed ledger (DL) of a blockchain applicable to a network of blockchain nodes is provided. The method reduces a time period between an assertion placed on the blockchain by an assertor blockchain node and execution of one or more action items dependent on a consensus of the assertion, by: creating an Artificial Intelligence (AI) model, by one of the blockchain nodes of the network, using historical data stored by the DL, wherein the network of blockchain nodes further comprises the assertor blockchain node; calculating an index value indicating a probability that the consensus is true, based on the AI model and the historical data stored by the DL, by the one of the blockchain nodes, wherein each of the blockchain nodes comprises a computer system including at least a processor, a system memory element, and a communication device configured to send and receive data transmissions between the blockchain nodes of the network; and when the index value exceeds a predefined threshold, initiating the execution of the one or more action items dependent on the consensus, by the one of the blockchain nodes.

Systems and methods for accelerating execution of processes based on artificial intelligence (AI) prediction of blockchain consensus

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.

Object detection and image classification based optical character recognition

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.

Dynamic access of artificial intelligence engine in a cloud computing architecture

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.

System, method and computer program product for managing access to systems, products, and data based on information associated with a physical location of a user

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.

Multi-factor administrator action verification system

Detection of fraud in financial transactions is facilitated. A financial transaction is initiated by a user, and based on the financial transaction, information is obtained by an electronic device of the user. Using the information, the electronic device evaluates a set of rules personalized for the user; the set of rules to be used to determine whether the financial transaction is to be approved for the user. The electronic device provides an initial indication, based on the evaluating, of whether the financial transaction is to be approved.

Fraud detection employing personalized fraud detection rules

A method of predictively provisioning cloud resources based on human behaviors and heuristics includes monitoring a collection of events relating to a customer application as well as monitoring an infrastructure load on resources for the customer application. A causal relationship is evaluated between an event and the infrastructure load. A predictive rule is then constructed based on the causal relationship. Resource requirements are anticipated based on the predictive rule and a provisioning of resources in a service domain is requested for the anticipated resource requirements.

Predictive cloud provisioning based on human behaviors and heuristics

A system for predictively provisioning cloud resources based on human behaviors and heuristics includes a computer processor and logic executable by the computer processor. The logic is configured to implement a method. The method includes monitoring a collection of events relating to a customer application as well as monitoring an infrastructure load on resources for the customer application. A causal relationship is evaluated between an event and the infrastructure load. A predictive rule is then constructed based on the causal relationship. Resource requirements are anticipated based on the predictive rule and a provisioning of resources in a service domain is requested for the anticipated resource requirements, according to exemplary embodiments.

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Newmarket, Canada

Daniel Thomas Harrison